Podcasts about finops

What does a rising cloud bill actually tell you about the value your business is creating? Eight years after our first conversation, I welcome Kunal, co-founder and CEO of Unravel Data, back to Tech Talks Daily. We compare the data infrastructure he was optimizing during the Hadoop era with today's enterprise stacks built around Databricks, Snowflake, BigQuery, AI pipelines, and autonomous agents. Kunal says Unravel Data has analyzed over 10 billion workloads across hundreds of enterprises. From that work, he argues that data platforms and infrastructure can account for up to 60% of cloud spending at some global businesses, while 30% to 40% of data platform spending may produce no business value. These are company claims, but they frame a problem many technology and finance leaders will recognize. The cloud bill arrives after thousands of individual engineering decisions have already been made. We discuss where cloud waste hides, including oversized clusters, hot storage holding cold data, abandoned pipelines, inefficient queries, duplicate datasets, and development jobs consuming production-level resources. The people creating those workloads seldom see the price attached to their decisions, leaving technology leaders with an aggregated bill that explains what was purchased but not why it was needed. AI adds another complication. Humans create workloads at human speed, while agents can generate queries, launch infrastructure, and consume tokens around the clock. An agent is designed to complete its task, not worry about whether a single query costs $5 or $5,000. Kunal argues that machine-speed consumption cannot be governed through monthly human reviews. We also discuss the difference between cost cutting and cost optimization, why aggressive reductions can damage performance and reliability, and how FinOps must connect cost with business outcomes. Kunal explains why leaders should measure cost per pipeline, model, agent, successful run, customer report, and business result. Finally, we consider the benefits and risks of autonomous data platform optimization. Kunal describes autonomy as a dial, with bounded, reversible, and validated actions earning wider authority as trust develops. Does your cloud bill show healthy growth, or is expensive waste hiding behind the headline number? Share your thoughts with me.

In this episode of the podcast, members of the InfoQ editorial staff and friends of InfoQ will discuss current trends in the cloud and DevOps domains as part of our annual trends report. These reports provide InfoQ readers with a high-level overview of key topics to watch and also help the editorial team focus on innovative technologies. In addition to the report and the trends graph available on InfoQ.com, this podcast offers a chance to hear our raw conversation and the stories shared by our expert practitioners. Read a transcript of this interview: https://bit.ly/4ggpO8h Newsletter: Subscribe to the Software Architects' Newsletter, a monthly roundup of the patterns and technologies senior practitioners are working through, with the news and lessons from people doing the work: https://www.infoq.com/software-architects-newsletter InfoQ Online Certification Programs: 5-week online cohorts for senior engineers and architects, built around QCon talks. Programs now cover software architecture, AI engineering, and organizational architecture. Each week you join a four-hour live session with a confidential peer group of practitioners from other companies, apply frameworks from QCon talks to the decisions you're making at work, and earn an InfoQ certification. You leave with new approaches, or confirmation that the calls you're already making are the right ones. Learn more: https://certification.qconferences.com/ Upcoming Events: QCon San Francisco 2026 (November 16-20, 2026) https://qconsf.com/ QCon London 2027 (April 13-16, 2027) https://qconlondon.com/ The InfoQ Podcasts: Weekly conversations with senior software leaders about how they build systems and teams, including what they'd do differently. Listen to all our podcasts and read interview transcripts: The InfoQ Podcast: https://www.infoq.com/podcasts/ Engineering Culture Podcast by InfoQ: https://www.infoq.com/podcasts/#engineering_culture Generally AI: https://www.infoq.com/generally-ai-podcast/ Follow InfoQ: Mastodon: https://techhub.social/@infoq X: https://x.com/InfoQ LinkedIn: https://www.linkedin.com/company/infoq/ Facebook: https://www.facebook.com/InfoQdotcom Instagram: https://www.instagram.com/infoqdotcom/ YouTube: https://www.youtube.com/infoq Bluesky: https://bsky.app/profile/infoq.com Write for InfoQ: Share what you've learned building software with a community of senior practitioners, and get your work in front of the people who read InfoQ. https://www.infoq.com/write-for-infoq

O próximo papo é com Fabrício Carraro (https://www.linkedin.com/in/fabriciocarraro/), AI Developer Advocate e Research Engineer no Barcelona Supercomputing Center (BSC), Program Manager na Alura, autor de livros sobre Inteligência Artificial, palestrante TEDx e apresentador do podcast IA Sob Controle.Mas este episódio não é apenas sobre Inteligência Artificial.É sobre a construção de uma carreira completamente fora do padrão.O Fabrício saiu da engenharia de software, passou por marketing, gestão de produtos, educação, aprendeu diversos idiomas e, sem seguir um caminho tradicional, chegou a um dos maiores centros de pesquisa em supercomputação da Europa.Conversamos sobre como a curiosidade e a capacidade de aprender constantemente abriram portas para oportunidades internacionais e permitiram que ele atuasse hoje diretamente com pesquisa aplicada em IA.Durante o episódio falamos sobre:* Como construir uma carreira internacional sem seguir um roteiro tradicional* A transição da engenharia de software para Inteligência Artificial* O trabalho com modelos de IA no Barcelona Supercomputing Center* Open Source e o futuro dos modelos abertos* O impacto da IA no mercado de tecnologia* Como estudar Inteligência Artificial de forma prática* Aprendizado contínuo, idiomas e desenvolvimento de carreira* O que esperar dos próximos anos da IAMais do que um episódio sobre tecnologia, esse é um papo sobre reinvenção, curiosidade e como diferentes experiências podem levar a oportunidades que muita gente nem imagina.Se você gosta de Inteligência Artificial, desenvolvimento de software, carreira internacional ou quer entender como a IA está sendo construída por quem trabalha diretamente na área, esse episódio vai valer o play.https://open.spotify.com/show/5xLCMHJ6eGWzdu8JaIDkuP?si=f3ab627acf2e4ca1

Chris Fabes, president of TD SYNNEX Canada Chris Fabes is two weeks into his new role as president of TD SYNNEX Canada, and he brings a perspective almost nobody else in the Canadian channel can match: senior leadership experience on all three sides of the ecosystem. Fabes spent a decade at Lenovo Canada, where as channel chief he tripled channel revenue to $1.2 billion in three years. He then moved to SHI International, where he led the Canadian operation with a focus on enterprise and public sector. Now he’s at the distributor side, taking over from Mitchell Martin, who ran the business for 35 years through multiple mergers and industry transformations. In this conversation, Fabes discusses what he learned from seeing the channel from the vendor, reseller, and distributor sides – and how each perspective informs what partners should expect from TD SYNNEX going forward. He talks about the booming Quebec market (he’s Montreal-based and bilingual), the role of MSPs as “AI ambassadors” for 1.3 million Canadian SMBs, and the shift from traditional SaaS consumption toward tokenomics. He’s candid about needing more time to assess TD SYNNEX’s internal AI readiness, and he closes with a challenge to the Canadian channel: be “proud and loud” about what the ecosystem has accomplished. Read Full Transcript **Robert Dutt:** Hello and welcome to In The Channel from ChannelBuzz.ca, bringing news and information to the Canadian IT channel community for the last 16 years. I’m Robert Dutt, editor at ChannelBuzz.ca, and your host for the show. Today I’m joined by Chris Fabes, who’s just a couple of weeks into his new role as president of TD SYNNEX Canada. Now, TD SYNNEX is of course the largest technology distributor in the world, and the Canadian operation has been a fixture of this channel for decades. But this is a transition moment. Mitch Martin ran the Canadian business for more than 35 years, starting out with Merisel Canada, through the Synnex acquisition, the pandemic, mergers with Westcon, and finally the merger with Tech Data. He retired earlier this year and TD SYNNEX went outside the organization for his replacement. They found Chris Fabes at SHI International, where he was running the Canadian operation. Before SHI, he spent a decade at Lenovo Canada, where as the channel chief he tripled channel revenue to $1.2 billion in three years. And before that, he started his career at a reseller. So, he’s one of the very few people in the industry who’ve held senior leadership roles on the reseller side, the vendor side, and now the distributor side. A 360-degree view that I think is worth exploring. We talked about what he’s seeing in his first two weeks, what partners should expect from TD SYNNEX Canada under his leadership, the Quebec market, which he calls home, AI, program simplification, and why he thinks the Canadian channel ecosystem should be, in his words, “proud and loud.” Let’s get right into it. My chat with Chris Fabes. Chris, thanks for taking the time. I appreciate it. **Chris Fabes:** Thanks for having me. I also appreciate it. **Robert Dutt:** Pretty epic way to get the distributor side of things on your channel bingo card, having already done the reseller solution provider and vendor side. Congrats on the new gig and I guess in general, your thoughts on taking over the leadership of TD SYNNEX Canada at this moment. **Chris Fabes:** I appreciate that. And look, how could I not be excited? It’s an incredible opportunity. As you mentioned, I’ve been on the vendor side as well as the value-added reseller side, but distribution is definitely not new for me. I’ve been working with TD SYNNEX for many, many years in different capacities. So it’s exciting having known the organization, knowing a lot of the people, and just quickly being pulled into internal and external conversations about, “Hey, what can we go do to go big?” So it’s just really exciting and I couldn’t be happier. **Robert Dutt:** As we touch on there, you’ve had senior leadership roles reseller side, most recently SHI, the vendor side with Lenovo, and now you’re adding the distributor side—a perspective that not many people have at the senior level especially. How has seeing that ecosystem from all three of those sides changed what you think a distributor actually needs to do for partners? **Chris Fabes:** I think it gives me a perspective that is rather unique. I always like to look at what the market is asking of the channel ecosystem and for each of those components, where do we add value and how do we focus on the outcome that our customers, vendor partners, and the ultimate end user are looking for. I think we can all agree that while technology, the whole industry is an exciting place to be—and I think we’d be doing something different if we all wanted things to be simple—the pace of change and the pace of innovation is really exciting. I think with all of the growth and now complexities built into the ecosystem, distribution plays an even more pivotal role in being able to service the demand. That’s what’s really exciting looking at the future. **Robert Dutt:** At Lenovo, one of your signature achievements was tripling channel revenue to $1.2 billion over the course of three years. What was the thesis and the plan behind that growth in that time, and is any of that transferable to the distributor context where you’re one step further removed from the end customer? **Chris Fabes:** I think it absolutely is relevant and it aligns. It all starts with planning around what the expected demand is and making sure that the differentiation and the capabilities are aligned with that opportunity. Even answering your question from the Lenovo side of things, it was: where’s the appetite? Where are the routes to market? How do we pull the levers at the right times? How do we make sure that we’re talking to the customers, being the channel partners as well as the end customers, so that we can pivot as required? Looking at the distribution side of things, it’s really no different. In the Canadian market, it is really: where’s the spend coming from, who is touching those spend requirements, and how do we participate in a meaningful way where we’re adding value to the equation? **Robert Dutt:** You spent a decade at Lenovo on your way up, literally working your way up the organization. How does that kind of ground-level experience shape your leadership style and what are you looking for in the teams you’re building now? **Chris Fabes:** Great question. I’ve always looked at myself as being someone that respects people at all levels. I don’t see myself any different from anyone else in any organization. So I really seek to understand, look to build relationships, and listen first. I lead with trust, which I think allows you to operate with very low friction, allowing people to outperform at their best levels. I make sure that I celebrate success along the way, but also hold people accountable. It’s been fun being able to work for people and then have a flip-side relationship as I was able to grow into different leadership positions. Being humble and respectful of all those relationships has benefited me as I’ve moved into positions where the relationships, even if they might be different now, are very much respectful. I’m happy for them; they’re happy for me. We have a short memory when we want it to be short, but long when it matters. In this channel, being that it’s large yet very small at the same time, leaving those relationships better off has been an important part of the way I’ve looked at people. **Robert Dutt:** I asked you a little while ago your perspective on what you can bring from the vendor side to the distributor side of things. Sort of the same question, but coming at it from your more recent point of view from the reseller side at SHI. A massive reseller—what did your time there teach you about where distribution adds value, where it doesn’t, and what you wanted from distribution when you were in that seat? **Chris Fabes:** Sure. There were a lot of conversations. Most of my conversations at that point were internal around building strategy. I think we’ve touched on that quite a bit, but the other side was just talking with CIOs, CEOs, and VPs that were responsible for technology decisions. The technology decisions almost became the easy part. It was: Where can you help me around optimization? Where can you help me on cash flow? How can you do things that are lower friction? What happens when something might not be going perfectly? Is there an escalation path? So, process—that’s what I started to learn and be able to apply to that business. Again, I think having that lens of those customer expectations and understanding the flow down through the complete channel ecosystem allows me to look at distribution from a strategy and execution lens, combined with the ultimate goal of satisfying those that are ultimately deploying the technology—whether they be SMB, mid-market, enterprise, or large public sector. **Robert Dutt:** Mitch Martin ran this business for 35-plus years. That’s a pretty extraordinary tenure and he went through pretty wild changes in the industry and in the organization in particular. What do you see as the foundation that he left there? And what do you see, especially in your early days, as the biggest opportunities for fresh investment or new ideas? **Chris Fabes:** Respect the legacy. That’s first and foremost. In my first couple weeks of talking with the staff, what I recognize is there was a strong hand on the business. The foundation was strong, mature, and very well operated, but that doesn’t mean we still can’t look at areas of opportunity—the nuances, the incremental spend, and how we bring additional value. So I’ll be spending my time respecting the mature foundation and the expertise that already exists in the business, listening and having an open mind, but looking at that three-to-five-year future of where TD SYNNEX needs to be based on the market appetite. I want to underscore that in speaking to many people in my first days, it was so incredible to hear the tenures—10 years, 20 years, 30 years—and the passion that they’ve had as they’ve gone through their career with TD SYNNEX through multiple mergers and acquisitions. What they shared with me was just the trust and the love in the organization and the people. I consider myself very lucky to be taking that baton and moving forward with it. **Robert Dutt:** TD SYNNEX is the largest distributor in the world and the competitive landscape is shifting. You’ve got Ingram Micro as the other big traditional broadline folks, and you’re both redefining yourselves in your own ways. As always, there are specialists and newcomers. You’ve got cloud marketplaces. I guess I’m curious, where do you think from where you sit now that TD SYNNEX needs to differentiate itself most urgently to stand out in the current marketplace? **Chris Fabes:** We’re absolutely looking at how we maintain a position of leadership, and that comes down to understanding the market and understanding—and respecting—our competition. Those are going to be the conversations we’ll be having in terms of: How is the ecosystem changing? How is the appetite for technology changing? Are we in a position to meet the demand but also accelerate the demand? Obviously, there’ve been several tailwinds driving the appetite for various technologies, but there’ve also been headwinds where budgets have shifted in how the spend is being distributed. There’ll be that “tech talk” cycle of how we look at the opportunities and how we partner—and who we partner with—to make sure that we’re positioned to grow at scale but continue to take a leading position. **Robert Dutt:** The press release that announced your arrival at TD SYNNEX emphasized enterprise and public sector. Those are areas that you focused on at SHI. Is that a signal that that’s an area where we’re going to see TD SYNNEX push harder in Canada, or more reflective of your background in recent history? **Chris Fabes:** I don’t think we want to read too much into my background. There are no assumptions that I’ll take what I was doing and immediately deploy something like that in this new structure. But where I think there is an opportunity is looking at the buying flow of goods and where in the Canadian market we expect to see the need for services, partnerships, and guidance. There have been several announcements within Canada where there’s going to be increased spend in certain industries—defense is one. We can call that the broader public sector. We also continue to see from an ICT spend that security remains a high priority across the country, as well as the continued investment in readiness in the infrastructure stack. Ultimately, it’s what is driving that demand, and I will be looking at the segmentation and how we best support the customers and partners. **Robert Dutt:** TD SYNNEX’s operational heart—the offices of both legacies that have come together over the years—is typically in the western side of the GTA, and you’re out of Montreal. I’m curious how you’re thinking about the geographic balance of the Canadian business writ large, and with your presence in “La Belle Province,” is there an opportunity to lean harder into Quebec and the francophone market? **Chris Fabes:** Absolutely. The Quebec market is booming. It’s very attractive for us to continue to focus on the areas of growth. We will be taking a national approach, but it’s important that each market has its nuances and its differences. Yes, we have most of our team members within central Canada, on the west side of Toronto, but we’ll be looking at where the demand is. I’m lucky enough to be in Montreal and speak both official languages. I look forward to working with our Quebec partners and vendors to understand if there’re any areas of opportunity that we can help them address. It probably won’t hurt that I am local—born and raised here—and understand the market and the people. **Robert Dutt:** As we speak, you’re two weeks into the role. As this airs, it’ll probably be more like three—”grizzled veteran” territory, clearly. Can you tell me a little bit about what you’ve been focused on for that first fortnight in the role and what you’ve heard from the crew, from resellers, and from vendors? **Chris Fabes:** It’s been nothing but positive. If my wife was here, she would confirm the conversations that she’s overheard! I want this to be a very intentional and honest response. Whether it be the folks that I’ve worked with in the industry, the customers that we serve, or the staff I now have the opportunity to work with, it has been very positive. I was in the Mississauga office for the past few days. I intentionally spent multiple hours walking the floor, shaking hands with all of our people, and asking for feedback. My goal is for our vendor partners and customers to see the value we can bring scale when we understand their business. I personally will hold my team accountable to understand the business drivers of our partners and customers. I will personally make sure that I’m involved in those conversations and in that planning—the good and the bad—so that I have a pulse on what’s expected of us. It’s really about decisions being rooted in reality and relationships. **Robert Dutt:** Last month at ChannelNext Central, you talked about MSPs as “AI ambassadors” for a million or more Canadian SMBs. Now you’re running the biggest distributor in the country. How do you enable that? What’s the distributor’s role in making MSPs successful as AI adoption accelerates and especially SMB customers start looking for more on that front? **Chris Fabes:** Absolutely. There are going to be some additional opportunities to look at how we provide services to the broader MSP market and how we serve them in the infrastructure build-out. There’s also a real conversation around the FinOps change—whether it be consumption or traditional SaaS moving to tokenomics. I think we as a distributor have an opportunity to listen, adjust, and build supporting models that support their build-out. We already do have programs in place to be able to support the MSPs in Canada, so we’ll continue to engage through our partner-led events and continue to build out what that model looks like. **Robert Dutt:** Internally, we touched on AI with the last question. All the distributors are trying to build the business of the future around what AI will mean to the kind of data you can provide. I’m curious about your assessment of TD SYNNEX’s stature in that race at this moment and where you see the biggest opportunities for next steps. **Chris Fabes:** I would say, honestly, I need to spend more time understanding where TD SYNNEX is from an AI perspective. I say that with honesty because my message to the team is that I need to observe and understand the ins and outs of our business. But what I will say broadly is that the appetite for AI is absolutely there and it requires a lot of readiness. Each of our customers is at a different stage. We will meet you where you are, whether it is services readiness, policy, governance, and compliance where we can help at scale, or modernization around infrastructure. We will make sure that we are absolutely ready and take a leading position, because the opportunity is insatiable. Most critically, it’s: how do our partners and their customers use AI to increase their competitive edge and optimization? We’ll be right there beside them. **Robert Dutt:** Back to your Lenovo days, another one of your big projects was simplifying the channel program. “Deadpan Simple” was a phrase I think you liked to use at the time. Distribution programs tend to be on the complex side. I’m curious if you see a simplification opportunity for TD SYNNEX Canada? **Chris Fabes:** In the early feedback that I’ve already received, what customers focus on is the execution. While maybe there are a lot of moving parts, if we execute and communicate seamlessly, that’s the experience that our customers are getting. Is there an opportunity for me to go validate your statement? Absolutely, and I will. It will be a focus of how we make sure we’re bringing the right outcomes and operational excellence. I don’t have a future statement yet, but I’ll be looking at it over time. Our platforms and programs have to be best-in-class if we want to continue to take a leading position. **Robert Dutt:** You’ve been in this community for two decades. What do you see as the big differences between the Canadian channel ecosystem and the US? And what do American-headquartered companies get wrong or misunderstand about the Canadian market? **Chris Fabes:** Part of the reason why this was attractive for me is that there is a respected understanding of how the regions operate. Having leadership and teams that understand our market and our ecosystem was absolutely important. But at the same time, when you can centralize resources and apply the scale at a global level and then bring that to a market like Canada, that allows us to speak with our customers with a much bigger toolkit. I think there is a really interesting balance at TD SYNNEX between the centralized functions of a larger organization and the regional focus and ability to execute based on what the local market desires. **Robert Dutt:** So it sounds like it’s a matter of finding the right balance between the global playbook and local use. **Chris Fabes:** Absolutely. We can learn from anywhere in the world, whether it be at a technology level or a thought leadership level. I’m a big fan of best practices—some people would say “shamelessly borrow”—and you apply it to the market. There’s magic in being open-minded and collaborative but not losing sight of what’s expected locally. **Robert Dutt:** Wrapping it up, what can Canadian VARs, MSPs, and solution providers expect from yourself and from the team at TD SYNNEX going forward? **Chris Fabes:** Expect us to be collaborative. I really mean it. That is the way I operate and it’s what I’ll hold the team accountable for. A partner doesn’t tell the other partner how to do it without listening or understanding. We are going to win together. That is a commitment that I have to our team in Canada and to our customers and partners—that engagement and interest in growing in the right ways. **Robert Dutt:** And one last one, mostly just for fun. If you could wave the proverbial magic wand to change one thing about how the Canadian channel works today, what would it be? **Chris Fabes:** I would say the people and the execution—the level in which the Canadian market has, from time to time, outperformed other areas of the ecosystem. I think the Canadian ecosystem should be “proud and loud” in terms of the accomplishments that we’ve been able to achieve. I look forward to being part of that voice that we can further raise within the local community. **Robert Dutt:** All right, so just be louder and keep doing it better. Sounds great. Chris, good luck with the new role and I look forward to keeping track of things going on at TD SYNNEX. Thanks once again for taking the time to chat. **Chris Fabes:** Thanks, Rob. I enjoyed the conversation and look forward to connecting again soon. **Robert Dutt:** There you have it. Chris Fabes from TD SYNNEX Canada. I’d like to thank Chris for taking the time just two weeks into a new job to sit down and talk about where he’s been and where he thinks TD SYNNEX Canada is headed. Really appreciate his candour around AI. He basically says, “still learning where we’re at,” which is a lot more credible in week two than a rehearsed vision statement might have been. And I think his challenge to the Canadian channel to be “proud and loud” about what this ecosystem has built is worth thinking about. There are a few things I’m going to be watching for as he settles in. Whether TD SYNNEX makes a real push into Quebec now that they’ve got a bilingual Montreal-based president; what a program simplification effort might actually look like given his history of stripping complexity out of partner programs; and how he thinks about the distributor’s role in a world where more and more transactions are moving through non-traditional models like cloud marketplaces. If you enjoyed this episode, I’d really appreciate it if you followed or subscribed to the podcast wherever you get your podcasts. We’re at Apple Podcasts, Spotify, YouTube, and most of the major podcast directories. And if you have a moment to leave a rating or review, we appreciate it. Until next time, I’m Robert Dutt for ChannelBuzz.ca and I’ll see you in the channel.

The episode reveals a structural shift toward operational complexity and heightened accountability in the MSP sector, as service providers are increasingly required to integrate AI capabilities, consolidate security offerings, and deliver enterprise-grade outcomes for mid-market clients without matching enterprise budgets. Blue Mantis, highlighted as a case example, embodies this shift with its transition from a traditional product reseller and hardware focus to a recurring managed services model with 60% of revenue now coming from managed services. The company's ongoing balancing act between recurring service delivery and legacy product sales illustrates the tension many MSPs face as the market demands integrated, outcome-driven engagements over transactional models. According to Josh Dinneen, Blue Mantis has developed fully managed security offerings, such as BlueMantis Protect, pairing AI-driven threat detection with human analysis to address mid-market needs for flexible, enterprise-grade cybersecurity. The company claims over 2,500 mid-market and enterprise customers and reports a customer retention rate above 97% over 48 months, with a 20% compound annual growth rate. These numbers are grounded in a “client-first” operational approach that emphasizes relationship management and ongoing alignment between service features and business requirements. The managed services business is supported by a global delivery model leveraging centers in India, Canada, and the US. Additional developments reinforcing the primary shift include Blue Mantis's measured adoption of AI and automation across both internal operations and customer-facing services. The company describes a structured AI rollout, aiming for every employee to have an AI “teammate” by the end of the year, framed as augmenting—not displacing—human workers. Josh Dinneen emphasizes the risk management dimension of rapid AI scaling, noting the double-edged nature of automation, and cites detailed KPI monitoring, a “3x ROI” workforce productivity model, and a growing FinOps practice to manage token-based AI consumption and budget risk, especially as vendors and consumption models shift costs and exposure downstream to customers and partners. For MSPs and IT leaders, these developments highlight mounting operational complexity and underscore the importance of risk mitigation strategies. Reliance on recurring services and layered security increases vendor and process dependency, elevating the need for robust governance, transparent performance metrics, and explicit controls over consumption-based pricing—particularly in AI and cloud. The operational implication is clear: MSPs must be prepared to offer advisory and managed services that both address evolving client demands for flexibility and manage the financial and accountability risks transferred by platform vendors and changing technology models. Supported by: CometBackupLogMeIn

Send us Fan MailTitle: What's New in Cloud FinOps - June 2026Hosts: Frank Contrepois and SteveOSummaryIn this episode, Frank and SteveO navigate through the latest cloud offerings and AI advancements, revealing how these updates impact performance, costs, and operational strategies across Azure, AWS, and AI applications. Stay tuned for insights into new VM generations, cost management tools, and cutting-edge AI features.Key Topics:Azure's new Cobalt 200V and 100V VMs deliver up to 50% better CPU performanceIntroduction of AWS's Metal 48XL/96XL and enhanced EC2 instances with sixth-generation Intel XeonLatest AWS Graviton 5 processors offering up to 25% better compute performanceEnhanced Amazon EC2 G7 instances powered by Nvidia RTX Pro 4500AWS Cost Management updates, including automatic cost anomaly investigations and new billing toolsAWS's support for region-agnostic throughput reservations in AzureThe rise of AI and automation in cost optimization: new tools, models, and use casesCloud vendors' announcements on energy-efficient storage, reserved pricing, and billing analysis toolsTimestamps:00:00 - Cloud news roundup: performance boosts in Azure VM series00:20 - Azure's new Cobalt 200V VMs: performance and AI workload optimization01:32 - AWS launches Metal 48XL/96XL: CPU advancements and network enhancements02:50 - Introduction of AWS M9G/M9GD instances with AWS Graviton 5 processors04:36 - AWS's latest EC2 G7 instances with Nvidia RTX GPUs for AI and visual workloads05:43 - Cost efficiency improvements with new pricing models and snapshot billing09:28 - Redshift advances with manual snapshot cost reductions10:12 - AI models on Bedrock: GPT 5.5, Codex, and OpenAI integrations12:24 - Innovations in cloud billing: cost explorer, cost anomaly detection, and billing account tools13:00 - Cost & Usage Report 2.0 enhances S3, Athena, and Redshift integration14:23 - Google Cloud billing updates: report export improvements and new filtering options15:19 - AWS's right-sizing and resource optimization enhancements16:12 - Cost explorer AI integrations and automated cost investigations17:10 - New AI-powered tools for cost anomaly root-cause analysis18:16 - Multi-project billing views and resource management in AWS19:04 - Advanced export configurations to streamline billing data handling20:06 - Google Cloud's spot VM real-time availability features21:36 - Enhanced tagging, resource management, and API capabilities in AWS and Google Cloud24:11 - Azure's VM retirements, storage, and reservation updates26:15 - Redshift's new upfront pricing options for reserved instances27:35 - Global provisioned throughput reservations now regional in Azure for flexibility28:44 - Storage charges optimizations and vector query cost reductions on S330:10 - Using finops.frankcontrepois.com for AI-driven FinOps34:08 - The importance of separating AI from automation in cloud efficiency strategies36:17 - Resources like the Phoenix Project and The Goal for understanding process optimization and AI impact37:34 - Support for new resource types and idle recommendation expansion in AWS Compute Optimizer38:50 - Cost and performance insights into specific resource wastage39:16 - AWS's State of Cost Efficiency Report: benchmarking and industry insights40:52 - AWS FinOps agents preview: automated cost and anomaly management workflows42:23 - Programmatic savings plan management and AWS workload optimization43:47 - Cost attribution and telemetry for large language models (LLMs) on Bedrock44:10 - AWS WAF's new AI traffic monetization capabilities for API access control45:45 - Azure Cosmos DB's new cost estimator tool for pre-provisioning modeling46:52 - Top three news picks: upcoming cloud innovations and AI advances47:35 - The growing role of FinOps and AI operational tools in cloud cost managementResources:FinOps toolThe Phoenix ProjectThe Goal by Eliyahu M. GoldrattConnect with the Hosts:Frank - LinkedInSteveO - LinkedIn

Bloomberg reported that Amazon recorded its fifth straight quarter of cloud sales growth, signaling a shift from optimization to new workloads. AWS is emphasizing generative AI services such as Amazon Bedrock, Amazon Q, and Amazon SageMaker, supported by custom chips Trainium and Inferentia. Amazon previously committed up to $4 billion to Anthropic, positioning Claude models on Bedrock against Microsoft's OpenAI alignment and Google Cloud's Vertex AI. AWS continues to use multi-year enterprise agreements, Savings Plans, and reserved capacity while co-selling with partners. Enterprises are focusing on FinOps practices, data gravity, and procurement leverage as AI pilots move to production. Competitive moves by Microsoft and Google are shaping pricing and features as customers plan 2026 cloud budgets.Learn more on this news by visiting us at: https://greyjournal.net/news/ Hosted on Acast. See acast.com/privacy for more information.

O próximo papo é com Igor Eulalio Morgado Lopes (https://www.linkedin.com/in/igoreulalio/), Senior Solutions Engineer na Orca Security, ex-AWS e Sysdig, engenheiro de software, palestrante e uma das referências brasileiras quando o assunto é Cloud Native, Kubernetes e segurança.A história do Igor mostra que uma carreira sólida não é construída apenas com certificações ou boas oportunidades. Ela é resultado de curiosidade, estudo constante e da disposição para assumir desafios cada vez maiores.Ao longo da conversa, falamos sobre a transição da engenharia de software para plataformas cloud, a experiência trabalhando em empresas globais, a evolução da carreira até chegar à área de segurança e os aprendizados adquiridos ao longo dessa jornada.Também conversamos sobre:* A evolução da carreira em Cloud e Platform Engineering* A experiência na AWS, Sysdig e Orca Security* Segurança em ambientes Kubernetes e Cloud Native* O papel da IA na engenharia e na segurança* Certificações, comunidade e aprendiza

What happens when an AI experiment becomes a production service that your employees, customers, and daily operations depend upon? In this episode of Tech Talks Daily, I speak with Brian Klingbeil, Chief Strategy Officer at Ensono, about AI infrastructure resilience, operational dependency, FinOps, legacy modernization, and the growing pressure to prove that enterprise AI investments are producing meaningful returns. Brian has been speaking with major enterprises through Ensono's Executive Advisory Council. Three years ago, many participants were experimenting with proofs of concept. Today, they are being asked to present AI projects that are already in production, approaching production, or demonstrating a clear return through productivity, lower risk, service quality, or financial results. That progression creates a new problem. When an AI model begins supporting product delivery, customer service, logistics, software development, or internal operations, it becomes part of the company's operating infrastructure. Leaders must then ask familiar IT questions about availability, monitoring, security, incident response, disaster recovery, ownership, and cost. Brian believes FinOps often provides the first warning. Token consumption can be difficult for CFOs and business leaders to interpret, particularly when hundreds of agents are operating across different models. Ensono's internal platform has produced around 1,000 agents, prompting questions about which are effective, which are expensive, and who should carry the cost. We discuss why chargeback and showback could change employee behavior. When AI spending is absorbed by a central corporate budget, teams may have little reason to question whether an expensive model is suitable for a routine task. When the cost reaches their departmental budget, the decision can look very different. Architecture also matters. Brian recommends systems that are loosely coupled and tightly integrated. Companies should be able to replace a model, provider, FinOps tool, or service as the market changes, while still connecting each component closely enough to deliver useful business outcomes. That creates a genuine tradeoff. Providers such as Microsoft, Amazon, Google, OpenAI, and Anthropic can offer specialist capabilities that businesses may want to use. Avoiding every provider specific feature can limit what the technology delivers, while becoming too dependent on one provider can make future change expensive and disruptive. The conversation then turns toward legacy technology. Brian argues that many systems described as outdated still process airline reservations, banking transactions, insurance claims, government services, and other high volume workloads. Turning them off without suitable replacements would create far bigger problems than the word "legacy" suggests. AI can change the modernization decision. Ensono worked with Markerstudy Group to analyze six million lines of RPG code running on an IBM i platform. The resulting plan identified applications that should move elsewhere while preserving workloads that still benefited from the platform's reliability and transaction processing capabilities. Brian treats migration as one possible part of modernization. AI tools can document old code, support modern development environments, and allow younger developers to work with established platforms without immediately beginning a lengthy and expensive replacement program. We also discuss Ensono's use of AI operations. Brian says the company reduced mean time to repair by 50% while processing approximately 50,000 tickets each month. The example shows how AI value can be measured through service quality and operational performance rather than relying entirely on direct revenue. The result is a balanced conversation about moving quickly while building enough control to keep AI dependable. Organizations need space for experimentation, but production services also require ownership, budgets, recovery planning, and people who know what to do when something fails. If one AI model or provider disappeared tomorrow, how much of your business would stop working? Listen to the episode and share your thoughts with me.

Manish Dasaur is a Managing Director at PwC with over 20 years in data and AI, having helped 100+ clients navigate AI disruption and extract real business value from data, AI, and agentic AI initiatives. In this episode, he breaks down why most enterprise AI programs stall — and the playbook the winners are using instead.Huge thanks to PwC for supporting this episode!

The episode identifies a significant structural shift in the technology sector where the adoption of AI is increasingly shifting costs and accountability from technology providers to individual users and their employing organizations, creating new governance and operational complexities. This shift is underscored by CompTIA's research, which indicates a projected growth in tech jobs despite past contractions, alongside a strong intention among companies to increase AI investment and training. However, the true impact is complicated by the distinction between the tech industry (vendors) and technology occupations across all sectors. CompTIA's latest IT Industry Outlook for 2026 reveals a generally optimistic sentiment among tech professionals, with 77% feeling positive about their organizations' prospects and 84% planning to increase AI investment. The report highlights five priorities for AI value: expanding cybersecurity, sharpening data practices, automating workflows, and rebuilding the workforce pipeline. Despite this positive outlook, a key finding is that many companies are still in the early stages of integrating AI into their technology stacks, suggesting that the projected growth may not yet fully reflect the downstream impacts of widespread AI implementation. Further analysis indicates that while AI is driving demand for specific skills like data management and cybersecurity, the development of AI fluency is uneven. Many MSP websites do not mention AI, and only a small fraction offer defined AI solutions, highlighting a potential gap in market readiness. The episode emphasizes that AI is not a standalone product but an enabler, with its cost and complexity necessitating a FinOps approach. This contrasts with the simpler per-user SaaS models, as AI's consumption-based nature and potential for machine-speed operation introduce unpredictable cost variables. For MSPs and IT leaders, this evolving landscape presents several operational implications. The increasing cost and complexity of AI implementation demand a focus on data governance and robust FinOps practices, traditionally handled by IT infrastructure teams but now extending to individual-level use cases. A lack of defined AI job roles and the inconsistent adoption of AI by service providers suggest an opportunity for MSPs to develop expertise in AI governance, enabling them to manage AI implementation, cost, and risk for their clients. Failure to address these governance and cost management aspects could lead to significant operational challenges and liability.   Supported by:  ScalePadGuardz

Dave, Esmee, Rob and Marcel wrap up an incredible Season 5, reflecting on the biggest technology trends, the most memorable conversations, and the fantastic guests who joined us along the way. From AI and cybersecurity to quantum computing and digital transformation, it's been a season full of insights, innovation, and inspiration.Thank you to all our listeners, guests, and supporters for being part of the Realities Remixed journey. We wish you a fantastic summer and look forward to bringing you even more thought-provoking conversations when we return in September for Season 6!TLDR00:27 – Season 5 reflections and key trends02:38 – Summer observations and random interruptions05:01 – From Cloud Realities to Realities Remixed08:05 – Winning 3 Global Marketing Awards10:50 – Esmee's journey and what's next14:05 – Technology trends revisited15:20 – Cybersecurity and investment challenges18:34 – Scaling AI beyond pilots25:41 – The reality of business transformation 33:35 – AI governance, agents, ethics, and the future of work47:00 – Knowledge retention and collaboration49:20 – Hardware innovation for AI51:17 – Macro trends and standout guests57:45 – Digital sovereignty and resilience1:08:00 – Why systems thinking must change1:12:00 – The Octopus Organisation1:18:24 – Summer plans and what's aheadHostsDave Chapman:  https://www.linkedin.com/in/chapmandr/Esmee van de Giessen:  https://www.linkedin.com/in/esmeevandegiessen/Rob Kernahan:  https://www.linkedin.com/in/rob-kernahan/ ProductionMarcel van der Burg:  https://www.linkedin.com/in/marcel-vd-burg/Dave Chapman:  https://www.linkedin.com/in/chapmandr/ SoundBen Corbett:  https://www.linkedin.com/in/ben-corbett-3b6a11135/Louis Corbett:   https://www.linkedin.com/in/louis-corbett-087250264/ 'Realities Remixed' is an original podcast from Capgemini

Quantum materials discovery shows how quantum computing can create real value in industry by working alongside AI, advanced computing, and experiments to better understand materials, improve decision-making, and accelerate innovation at scale, ultimately helping deliver practical, measurable progress for the energy transition.This week, Dave, Esmee, and Rob are joined by co-host and quantum expert Phalgun Lolur, together with Jonathan Owens, Senior Scientist in Computational Materials Physics at GE Vernova to explore how quantum computing could reshape materials discovery and why that matters for the future of energy.  TLDR00:00 – Introduction01:50 – Hang out: The wet-bulb thermometer03:20 – Dig in: Technology Convergence and the Link to Quantum11:30 – Conversation with Jonathan Owens44:26 – Exciting to see how the quantum landscape matures and the magic wand for magnetismGuestJonathan Owens: https://www.linkedin.com/in/jonathan-r-owens-phd/ HostsDave Chapman:  https://www.linkedin.com/in/chapmandr/Esmee van de Giessen:  https://www.linkedin.com/in/esmeevandegiessen/Rob Kernahan:  https://www.linkedin.com/in/rob-kernahan/Co-host Phalgun Lolur:  https://www.linkedin.com/in/phalgun-lolur/ ProductionMarcel van der Burg:  https://www.linkedin.com/in/marcel-vd-burg/Dave Chapman:  https://www.linkedin.com/in/chapmandr/ SoundBen Corbett:  https://www.linkedin.com/in/ben-corbett-3b6a11135/Louis Corbett:   https://www.linkedin.com/in/louis-corbett-087250264/ 'Realities Remixed' is an original podcast from Capgemini

SUMMARY: On today's "Models and Markets" - we explore about the FinOps experience from Cloud is having to adapt to the changing demands of Enterprise AI. SHOW: 1045SHOW TRANSCRIPT: The Enterprise AI Show #1045 TranscriptSHOW VIDEO: https://youtu.be/Plb88y-IkZYSHOW SPONSORS:Nasuni - Activate your data for AI and request a demoShareGate - ShareGate Protect. Microsoft 365 Governance, we got this!SHOW NOTES:Topic: Finops for AI?Why now? Cost of tokens goes up as model performance increases, but still needs subsidies…Past: FinOps for Cloud - prices grew out of control, needed centralization for expense management and capital allocationPresent: TokenMaxxing, the move from per-seat to per-token pricingFuture: What happens when you can't afford the Ferrari anymore? Will there be a glut of FinOps for AI startups? What happens when usage is regulated and centralized?FEEDBACK?Email: show @ the enterprise ai show dot comeBluesky: @TheEntAIShow.bsky.socialTwitter/X: @TheEntAIShowInstagram: @TheEntAIShow

After months of experimenting with large language models (LLMs), enterprises are moving from isolated pilots to broad deployments. However, as adoption speeds up, many tech leaders find that the biggest challenge isn't selecting the right AI model but managing the cost of optimising it.While AI models might be getting more expensive owing to geopolitical tensions and expanding use cases, the added challenge is that the price per token continues to rise. The problem is that enterprise AI is using a lot more tokens as companies scale new applications across different departments.In the recent episode of the Don't Panic It's Just Data podcast, host Kevin Petrie, VP of Research at BARC, sat down with Eudald Camprubi, Co-Founder of Nuclia (acquired by Progress) and Software Fellow at Progress and Michael Marolda, Senior Product Marketing Manager, Agentic RAG.They talked about how the next phase of enterprise AI will focus less on model selection and more on context engineering, retrieval strategies, and governance.What Does the Future of Enterprise AI Rely on?As enterprises progress beyond experimentation, success will rely less on picking the next game-changing model and more on using existing models wisely. That means providing precise context instead of excessive context.Enterprises should select the right model instead of just the latest model. That means they should treat observability, retrieval strategies, and governance as foundational capabilities rather than second priorities.Camprubí said that enterprise leaders should be wary of industry hype. "Don't trust everything you read on LinkedIn.” In enterprise AI, measurable results will determine which enterprises effectively scale intelligent systems.Listen to the full episode of Don't Panic! It's Just Data to hear Michael Marolda and Eudald Camprubí discuss Agentic RAG, token optimisation, context engineering, and the future of enterprise AI at scale.TakeawaysToken costs are climbing, making cost management critical for enterprises.Context is essential for effective AI implementation and user satisfaction.Enterprises must focus on providing the right context to LLMs to avoid hallucinations.Modularity in AI platforms allows for flexibility and adaptability in solutions.Quality metrics are vital for evaluating AI outputs and ensuring reliability.The latest AI models are not always the best choice for every use case.Understanding user intent is crucial for effective data retrieval.FinOps teams are increasingly involved in managing AI costs and strategies.Enterprises should consider RAG as a service to reduce maintenance burdens.Collaboration among stakeholders is essential for successful AI implementation.Chapters00:00 Introduction to AI and Data Context03:26 Understanding Token Costs in AI09:03 The Importance of Context in AI14:37 Exploring the Context Layer and Retrieval Strategies22:31 Model Selection and Cost Management in AI29:11 Key Takeaways for AI LeadersFor more enterprise AI, Agentic RAG, data governance, and enterprise knowledge layer insights, follow Progress Software across its official channels:Website: Progress SoftwareYouTube: @ProgressSWLinkedIn: Progress SoftwareX: @ProgressSWFor more information on enterprise tech analyst-led insights, please visit em360tech.comEM360Tech YouTube: @enterprisemanagement360EM360Tech LinkedIn: @EM360TechEM360Tech X: @EM360Tech#EnterpriseAI #ContextEngineering #AgenticRAG #AIROI #TokenCosts #AIStrategy #DataManagement #DonTPanicItsJustData #ProgressSoftware #Nuclia

In "How to Turn Freight Data into Audit-Ready Scope 3 Reporting", Joe Lynch and Michael Rentz, Chief Revenue Officer at Gnosis Freight, discuss how operational-grade logistics data automatically simplifies complex carbon compliance. About Michael Rentz  Michael Rentz is the Chief Revenue Officer at Gnosis Freight. He joined the company in the Summer of 2020. Before joining Gnosis, he got his start in the industry with the South Carolina Ports Authority and Maersk. He left Maersk in 2018 to pursue his own endeavors, which eventually led him back to Charleston, SC, where he worked for Techstars in an attempt to stand up the first-ever Supply Chain and Logistics Accelerator. The pandemic put an unexpected halt to that, and it was then that he fortuitously met Austin McCombs (CEO/Founder of Gnosis) and Jake Hoffman (CTO of Gnosis). About Gnosis Freight Gnosis Freight is the AI-native Global Freight Operating System for enterprise supply chains. It gives logistics, operations, and finance teams real-time insight into container movement and helps them Intervene earlier when delays, inventory risk, or cost exposure arise. By linking containers to SKU- and Inventory-level detail, Gnosis enables smarter planning, improved product availability, and more predictable business performance. Powered by continuously reconciled container Intelligence, Gnosis orchestrates exception management through configurable, low-code workflow and agentic AI across logistics, finance, and operation – reducing demurrage and detention, accelerating invoice resolution, and shortening goods-to-cash cycles. Headquartered In Charleston, SC, Gnosis serves global enterprises across retail, manufacturing, and logistics-intensive industries. Learn more at gnosisfreight.com. Key Takeaways: How to Turn Freight Data into Audit-Ready Scope 3 Reporting In "How to Turn Freight Data into Audit-Ready Scope 3 Reporting", Joe Lynch and Michael Rentz, Chief Revenue Officer at Gnosis Freight, discuss how operational-grade logistics data automatically simplifies complex carbon compliance. The Foundation of Scope 3 Reporting is "Sovereign Data": Accurate emissions reporting is impossible without high-fidelity operational data. Gnosis Freight utilizes "sovereign data"—logistics data they originate, validate, and structure directly from primary sources (ports, terminals, carriers, and railroads) rather than relying on third-party aggregators or high-level assumptions. If your operational data isn't audit-ready, your carbon reporting won't be either. Regulatory Shifts are Turning ESG from a Checkbox into a Mandate: With major regulatory updates like California's SB 253 looming in 2027, large enterprises (doing over $1B in revenue) that touch these key economies will be legally required to disclose their Scope 3 emissions. What was once a marketing slide about "valuing the environment" is rapidly transitioning into a strict, auditable corporate compliance requirement. Solving the Category 4 "Data Black Hole": Scope 3, Category 4 emissions (upstream transportation and distribution) are notoriously fragmented and difficult to track. By overlaying the GLEC (Global Logistics Emissions Council) framework directly onto their existing container tracking data, Gnosis calculates precise emissions across every single leg of the journey—ocean transit, port idling, rail, and final-mile drayage—without requiring manual spreadsheets or guesswork. Shippers Want a Unified Operating System, Not More "Point Solutions": Enterprise Beneficial Cargo Owners (BCOs) are experiencing software fatigue and actively moving away from single-use point solutions. Instead of buying a standalone carbon tracking tool, shippers want emissions data embedded directly into their daily workflow. Gnosis solves this by making carbon tracking a seamless "flip of a switch" within their broader Container Lifecycle Management (CLM) platform. Data Must Be "Operational-Grade" to Be Useful: In logistics, if data is only 80% accurate, it is functionally 0% useful because operators will simply bypass the system and default to manual website cross-checking. For emissions data to survive a financial or regulatory audit, it must be built on the same operational-grade, real-time milestones used to run daily supply chain execution. FinOps and Carbon Audits Share the Same DNA: There is a direct parallel between auditing freight invoices and auditing carbon emissions. Gnosis found that 85% of invoice discrepancies stem from incorrect operational milestones (like when a container was actually made available). By mastering these physical execution milestones, Gnosis can simultaneously spot billing overpayments in their FinOps suite and defend carbon calculations in an emissions audit. Build Solutions by Getting in the Trenches with Customers: Gnosis's rapid growth—from navigating the pandemic's demurrage and detention (D&D) chaos to launching carbon tracking—has been entirely customer-driven. Rather than building flashy tech in a vacuum, their strategy is to deeply embed themselves with logistics managers, solve their immediate operational headaches first, and give them their time back to focus on strategic growth. Learn More About How to Turn Freight Data into Audit-Ready Scope 3 Reporting Michael Rentz | Linkedin Gnosis Freight | Linkedin Gnosis Freight Gnosis Freight: The Journey Between The Ships Carbon Emissions Landing Page Carbon Emissions Upcoming Webinar Carbon Emissions Whitepaper Gnosis Freight LinkedIn Testimonials & Case Studies Container Lifecycle Management: Gnosis Freight Streamlines International Logistics with Jake Hoffman The Container Payment Portal and the Rise of AI in Freight with Jake Hoffman The Logistics of Logistics Podcast If you enjoy the podcast, please leave a positive review, subscribe, and share it with your friends and colleagues. The Logistics of Logistics Podcast: Google, Apple, Castbox, Spotify, Stitcher, PlayerFM, Tunein, Podbean, Owltail, Libsyn, Overcast Check out The Logistics of Logistics on Youtube

Stefano Mainetti torna a Cloud Champions per il consueto appuntamento annuale dedicato allo stato del mercato cloud italiano.Responsabile Scientifico dell'Osservatorio Cloud Ecosystem & Sovereignty del Politecnico di Milano, Stefano ci aiuta a leggere i segnali che stanno emergendo a metà anno, in attesa del report ufficiale che l'Osservatorio pubblicherà a ottobre.In questa puntata parliamo di come sta evolvendo l'adozione del cloud in Italia: crescita del mercato, impatto dell'intelligenza artificiale sui workload, ruolo dei data center, maturità delle aziende, FinOps, repatriation, cloud native, sovranità del dato e nuove scelte architetturali.Non una fotografia statica, ma una lettura ragionata dei trend che stanno cambiando il modo in cui imprese, provider e istituzioni progettano infrastrutture, applicazioni e servizi digitali.Un episodio utile per chi vuole capire dove sta andando davvero il cloud in Italia, al di là degli annunci e delle mode del momento.

Life sciences are at a turning point, where scientific innovation, regulatory pressure, and patient expectations collide with unprecedented advances in data, AI, and digital platforms. IT is no longer a supporting function but a critical driver of how therapies are discovered, developed, scaled, and delivered safely and at speed.This week, Dave and Rob wrap up our State of Life Sciences mini-series with Thorsten Rall, Global Industry Lead for Life Sciences at Capgemini and together, they connect the dots across the series, exploring how AI, data and innovation are accelerating drug discovery, transforming med tech, modernising manufacturing and improving patient outcomes, all built on a strong digital foundation. TLDR00:27 – Introduction and conclusion of the Life Sciences mini-series 02:16 – Key insights and lessons from the previous episodes on the Life Sciences landscape 21:18 – Building resilient, efficient and future-ready operations 34:35 – Creating integrated, patient-centric healthcare experiences 43:15 – Why the Digital Core is the foundation for transformation and innovation 53:21 – Final reflections: the future of Life Sciences and the key takeaways 54:53 – Weekend BBQs, Thorsten's daughter's theatre performance, and the role of R&D HostsDave Chapman:  https://www.linkedin.com/in/chapmandr/Esmee van de Giessen:  https://www.linkedin.com/in/esmeevandegiessen/Rob Kernahan:  https://www.linkedin.com/in/rob-kernahan/with co-host Thorsten Rall: https://www.linkedin.com/in/thorsten-alexander-rall-b232185/ ProductionMarcel van der Burg:  https://www.linkedin.com/in/marcel-vd-burg/Dave Chapman:  https://www.linkedin.com/in/chapmandr/ SoundBen Corbett:  https://www.linkedin.com/in/ben-corbett-3b6a11135/Louis Corbett:   https://www.linkedin.com/in/louis-corbett-087250264/ 'Realities Remixed' is an original podcast from Capgemini

Most leaders in professional services are making decisions every day that come back to the finance – but no one ever actually taught them the numbers. In this episode, we're pulling back the curtain on the financial foundations that every leader needs to get a handle on, whether you're running a team, managing projects, or sitting in the hot seat at the top.Rich Brett is a FinOps consultant with 15 years in finance, working with professional services businesses to close the gap between finance and operations – and answer that nagging question: why is everyone busy, but we're not making any money?This episode is pulled directly from The Missing Finance Course – a free FinOps course Rich and Harv built to level up everyone from founders to individual contributors at agencies and consultancies. Here's what they get into:• Why cashflow forecasting isn't an advanced topic – it's a survival skill• What the P&L is really for, and why most senior leaders struggle to explain it to their own teams• How a knowledge gap becomes a credibility gap – and why that erodes trust across the whole business• Why so many businesses are pricing based on what they think something costs – not what it actually costs• Why comparing your rates to competitors is a trap, and what to do insteadIf you've ever sat in a finance presentation and felt a bit lost, or if you've been winging parts of your pricing strategy, this one's for you.The Missing Finance Course is free, self-paced, and built for three audiences: leadership, delivery teams, and individual contributors. Head to https://learn.scoro.com to get started.Additional Resources:

AWS Morning Brief for the week of July, 6th with Corey Quinn. Links:Announcing general availability of Amazon WorkSpaces for AI agentsAmazon CloudWatch supports creating alarms from log queriesECS Service Connect now supports Zone-Aware routingHow InterWiz reduced AI costs by 90% with Amazon BedrockAccelerate your infrastructure deployments by up to 4x with AWS CloudFormation Express modeAutomate public TLS certificate issuance with ACME support in AWS Certificate ManagerUpgrade Amazon EKS clusters with confidence using Kubernetes version rollbacksSafely Releasing Frontier Models to CustomersAccelerating government FinOps with Amazon QuickFour CVEs: AWS reads half your request, leaks the rest

Life sciences are at a critical inflection point, where scientific innovation, regulatory demands, and patient expectations converge with advances in data and artificial intelligence, positioning IT as a central driver of faster and more effective drug discovery and clinical development.This week, Dave and Rob continue with part 3 off the Life Sciences mini-series with Predrag Angelovski, VP, CTO at Healthcare Informatics at Philips to exploring how MedTech products are more and more becoming connected platforms, combining hardware, software and services.TLDR00:21 – Introduction with co-host Thorsten Rall01:00 – Hang out: Esmee joins and Rob is lost at a train station03:00 – Dig in: Life Sciences mini-series, Part 304:57 – Conversation with Predrag Angelovski50:56 – Travelling to Europe, agents vs. agentic, and the age of intelligence GuestPredrag Angelovski: https://www.linkedin.com/in/predrag-angelovski/ HostsDave Chapman:  https://www.linkedin.com/in/chapmandr/Esmee van de Giessen:  https://www.linkedin.com/in/esmeevandegiessen/Rob Kernahan:  https://www.linkedin.com/in/rob-kernahan/ ProductionMarcel van der Burg:  https://www.linkedin.com/in/marcel-vd-burg/Dave Chapman:  https://www.linkedin.com/in/chapmandr/ SoundBen Corbett:  https://www.linkedin.com/in/ben-corbett-3b6a11135/Louis Corbett:   https://www.linkedin.com/in/louis-corbett-087250264/ 'Realities Remixed' is an original podcast from Capgemini

SUMMARY: As AI within the Enterprise matures, we look at 10 concerns and challenges that are still causing Chief AI Officers to worry about success in the future. SHOW: 1040SHOW TRANSCRIPT: The Enterprise AI Show #1040 TranscriptSHOW VIDEO: https://youtu.be/RyB4m17YK_4SHOW SPONSORS:Nasuni - Activate your data for AI and request a demoOutShift by Cisco - “Scaling Out Superintelligence”  The Internet of Cognition architectureShareGate - ShareGate Protect. Microsoft 365 Governance, we got this!SHOW NOTES:THESIS: After spending time with a number of Enterprise companies, what are a list of challenges and concerns they still have in implementing GenAI across a broad set of use-cases within the Financial Services industry?Everybody started with what was available (e.g. CoPilot)Enterprise implementations (now) aren't autonomousRising costs are the looming concernGovernance is a rising concernMeasurements of improvement are available, but variedExplaining measurements is complicatedExplaining trust is more complicatedUse-cases are fragmented, but there if you apply the technology, but not always obviousDe-centralized (shadow AI) to Centralized to De-centralized (semi-controlled) The learning curves are very asymmetrical across teamsNot everyone has access to Mythos or GPT-5.5-Cyber (yet)FEEDBACK?Email: show @ the enterprise ai show dot comeBluesky: @TheEntAIShow.bsky.socialTwitter/X: @TheEntAIShowInstagram: @TheEntAIShow

With AI reshaping employer expectations, junior candidates in data are facing real anxiety about the job market. I share the technical and personal skills I'd focus on, my top five traits I look for in a candidate, and how to build a network from scratch.-----------------------Sponsor: Revefi Save serious money on your cloud costs with Revefi's new autonomous AI DBA, a tool built to handle the gritty reality of cloud data management so you can stop babysitting your infrastructure.With a five-minute, zero-touch setup, it deploys 18 specialized agents across your data estate to automatically manage FinOps, performance tuning, and data quality. If you want to cut your cloud costs by 30% to 70% and get back to actual data architecture, check out what they are building at revefi.com/ai-dba

Resilience is the recognition that in today's highly interconnected and unpredictable world, disruption cannot always be anticipated or prevented and therefore requires a shift from traditional risk avoidance toward designing systems that can absorb shocks, adapt in real time, and recover quickly, ultimately emerging stronger and turning uncertainty into a source of advantage.This week, Dave, Esmee, and Rob are joined by Benjamin Trump, President Society for Risk Analysis and Cedrick Moriggi, Chief Resilience Officer and co-found the CCRO network under the United Nations Office for Disaster Risk Reduction, to explore what resilience means in a world shaped by systemic risk, fragile supply chains, climate shocks, cyber threats and human decision-making. TLDR00:30 – Introduction01:29 – Hang out: Heatwave weather and the perfect pub temperature03:18 – Dig in: What is resilience, and how do you deal with it?10:35 – Conversation with Benjamin Trump and Cedrick Moriggi48:32 – Ben is a writer and Cedrick teaches children GuestBenjamin Trump: https://www.linkedin.com/in/benjamin-trump-ba062523/Cedrick Moriggi: https://www.linkedin.com/in/cedrickmoriggi/HostsDave Chapman:  https://www.linkedin.com/in/chapmandr/Esmee van de Giessen:  https://www.linkedin.com/in/esmeevandegiessen/Rob Kernahan:  https://www.linkedin.com/in/rob-kernahan/ ProductionMarcel van der Burg:  https://www.linkedin.com/in/marcel-vd-burg/Dave Chapman:  https://www.linkedin.com/in/chapmandr/ SoundBen Corbett:  https://www.linkedin.com/in/ben-corbett-3b6a11135/Louis Corbett:   https://www.linkedin.com/in/louis-corbett-087250264/ 'Realities Remixed' is an original podcast from Capgemini

We're in the early days of cost impacts for AI applications. While there are some cautionary tales, current spending seems to be a small fraction what's to come. Analysts Jean Atelsek and Melanie Posey return to the podcast to talk about what they heard at the FinOps X conference with host Eric Hanselman. The need for cost management in AI is seen as so great that the FinOps Foundation, a project of the Linux Foundation, is talking about morphing its conference into Tokenomicon and pivot into token economics. The portmanteau of tokenomics is sweeping across cloud and AI services providers, as well as IT vendors, as enterprises wrestle with dueling forces of AI acceleration and management constraints for access and cost. Unlike FinOps for cloud operations, the costs and metrics for AI are fairly opaque. Some enterprises are trying to manage costs by limiting access, but that risks stifling the innovation and democratization that is supposed to come with AI transformation. Request routing is promising, but it requires understanding the nature of the request and the suitability of available infrastructure to fulfill it, something that is not well understood by many. Most are just getting comfortable with managing model lifecycles and the step up to cost management can be a large one. More S&P Global Content: Compute sovereignty: The strategic importance of digital infrastructure Next in Tech | Ep. 222: FinOps – Managing Cloud and AI Costs AI in action: unleashing agentic potential Hyperscaler earnings quarterly: What price inference? For S&P Global subscribers: FinOps in the age of agentic AI FinOps Foundation expands FinOps discipline beyond cloud to technology value management Service providers race to meet surging enterprise demand for AI infrastructure FinOps Market Monitor & Forecast Host/Author: Eric Hanselman  Guests: Jean Atelsek, Melanie Posey Producer/Editor: Dylan Scheible Published With Assistance From: Feranmi Adeoshun, Sophie Carr, Kyra Smith,

Shahram Anver is the Co-Founder and CEO of Cleric, the autonomous AI SRE that investigates and root-causes production issues like an experienced teammate — often in under two minutes. Before Cleric, Shahram led MLOps, DevOps, and FinOps platform engineering at Gojek, Southeast Asia's super-app. In this conversation, he breaks down why production operations never kept pace with AI-accelerated development, and why the real unlock for an AI SRE isn't faster triage — it's an agent that *learns* and compounds operational memory across your whole org.In this episode:

Life sciences are at a critical inflection point, where scientific innovation, regulatory demands, and patient expectations converge with advances in data and artificial intelligence, positioning IT as a central driver of faster and more effective drug discovery and clinical development.This week, Dave and Rob continue with part 2 off the Life Sciences mini-series with Dr. Alex Zhavoronkov founder and CEO of Insilico Medicine to exploring how drug discovery and clinical development can become faster and more effective, and the role of AI in that process.  TLDR00:40 – Introduction01:00 – Hang out: Kill Bill Vol. 1 & 2 03:07 – Dig in: Life Sciences mini-series, Part 2 06:43 – Conversation with Dr Alex Zhavoronkov 42:12 – The future of AI in drug discovery and a new paradigm for pharma GuestDr. Alex Zhavoronkov: https://www.linkedin.com/in/zhavoronkov/ HostsDave Chapman:  https://www.linkedin.com/in/chapmandr/Esmee van de Giessen:  https://www.linkedin.com/in/esmeevandegiessen/Rob Kernahan:  https://www.linkedin.com/in/rob-kernahan/ ProductionMarcel van der Burg:  https://www.linkedin.com/in/marcel-vd-burg/Dave Chapman:  https://www.linkedin.com/in/chapmandr/ SoundBen Corbett:  https://www.linkedin.com/in/ben-corbett-3b6a11135/Louis Corbett:   https://www.linkedin.com/in/louis-corbett-087250264/ 'Realities Remixed' is an original podcast from Capgemini

Points of Interest 00:01 – 00:53 – Why Revisit Positioning: Carson and Kristen introduce Parakeeto's repositioning effort and explain why they wanted to publicly discuss the evolution of the company's messaging. 00:53 – 02:18 – The Profitability Problem: The discussion explores how Parakeeto's heavy emphasis on profitability created confusion about what the company actually does for clients. 02:18 – 04:21 – The Challenge of Category Creation: Carson and Kristen reflect on attempts to create or fit into categories like FinOps and why unfamiliar categories often create more confusion than clarity. 04:21 – 06:18 – From Profitability to Stewardship: The conversation introduces the new positioning centered around helping agency owners focus on building their businesses while Parakeeto takes care of the money. 06:18 – 09:11 – The Emotional Side of Finance: Carson shares how financial discomfort and avoidance can affect decision-making and explains why confidence is a critical outcome of financial stewardship. 09:11 – 11:31 – What Taking Care of the Money Means: Kristen outlines the practical components of Parakeeto's approach, including accounting, forecasting, reporting, and operational guidance. 11:31 – 13:19 – Agency-Specific Financial Expertise: Carson explains how deep agency experience allows Parakeeto to interpret financial data within the operational realities of agency businesses. 13:19 – 15:06 – Turning Financial Insights into Action: The discussion highlights the importance of translating financial reporting into operational recommendations that improve agency performance 15:06 – 17:37 – Expanding into Accounting and Bookkeeping: Kristen explains how bringing bookkeeping and accounting services in-house creates continuity between financial data and strategic decision-making. 17:37 – 19:54 – The Agency CFO Perspective: The conversation explores why the title "Agency CFO" better communicates Parakeeto's blend of financial expertise and operational advisory support. 19:54 – 24:13 – Who Benefits Most from This Approach: Carson and Kristen discuss ideal client profiles, including agencies crossing the $1M mark and larger firms seeking greater visibility and clarity. 24:13 – 28:19 – Building Confidence Through Partnership: The episode concludes with a discussion about education, long-term partnerships, and helping agency owners feel more confident managing the financial side of their businesses. Show Notes Free Agency Toolkit Parakeeto Foundations Course Free access to our Model Platform Connect on LinkedIn Carson Pierce Kristen Kelly Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

Welcome to episode 359 of The Cloud Pod, where the weather is always cloudy! Justin and Ryan are in the studio this week to bring you all the latest in cloud and AI news, including AI governance, FinOps' final conference, and even an earnings story courtesy of Oracle. These and so much more – so let's get started!  Titles we almost went with this week You Shall Not Pass Unless Your Network Policy Says So One CLI Wizard to Rule All AWS Agents AWS WAF Turns AI Crawlers Into Cash Cows No More Delete and Pray for AWS Cost Reports Stop Rolling Your Own Certificate Rotation AWS Did It Tux Gets a Security Checkup, Microsoft Antivirus Style Coal Plant to Cloud Plant Google’s Billion Dollar Glow Up FinOps Grows Up and Gets an AI Spending Problem Tokenomics Foundation Wants to Bill AI by the Word Sweet Home Alabama Now Runs on Google Cloud Infrastructure A big thanks to this week's sponsors: We're sponsorless! Want to get your brand, company, or service in front of a very enthusiastic group of cloud news seekers? You've come to the right place! Send us an email or hit us up on our Slack channel for more info. General News 02:53 Microsoft restricts Claude Fable for employees over data retention concerns  Microsoft has restricted Claude Fable 5 from its internal GitHub Copilot model picker, even though the model is available to external GitHub Copilot and Azure Foundry customers.  All other Claude models remain available internally because they operate under Zero Data Retention rules. The core issue is that Claude Fable 5 requires data retention to power Anthropic’s new safety classifiers, meaning prompts and outputs are stored for up to 30 days by default, and up to two years if flagged for policy violations.  This creates a meaningful conflict with enterprise data handling expectations. This situation highlights a broader tension cloud enterprises face when adopting frontier AI models that bundle safety mechanisms requiring data retention, since those requirements may conflict with internal legal and compliance policies around confidential information. The restriction is notable because Microsoft is both a distribution partner for Anthropic through Azure and a direct competitor via its own AI offerings, so internal adoption decisions carry weight beyond typical enterprise procurement concerns. For developers and businesses evaluating Claude Fable 5 through Azure Foundry or GitHub Copilot, this serves as a reminder to review the specific data retention terms for Mythos-class models before deploying them in workflows that handle sensitive or proprietary information. 04:23 Statement on the US government directive to suspend access to Fable 5 

There's great momentum in moving to greater levels of agentic automation, but there are critical areas where deeper consideration is required in how it's applied. In capital markets, trust is a foundational element on which transactions are built and Krisha Vinjamuri, Head of Technology, Enterprise Solutions at S&P Global Market Intelligence, joins host Eric Hanselman to talk about how this can be achieved and the important aspects of successful implementations. One of the useful things in capital markets, is that there are open standards on which to base data ontologies. It's not exciting, but it's the basis of a semantic foundation that can not only ensure that there is depth in data definitions, but can also reduce errors generated by agents. The larger question that looms beyond the construction of foundational architecture, is how the operational envelope that bounds agentic action will be established. This has to be built from policy definitions that take those actions into account. There is great promise and much work that needs to be done. More S&P Global Content: Compute sovereignty: The strategic importance of digital infrastructure AI won't solve its own energy problem – and that might be fine AI in action: unleashing agentic potential AI infrastructure results in 2025 top expectations, forecast upgraded For S&P Global subscribers: FinOps in the age of agentic AI AI Infrastructure Market Monitor & Forecast Service providers race to meet surging enterprise demand for AI infrastructure In 2026, the telecom network becomes code Credits: Host/Author: Eric Hanselman Guest: Krishna Vinjamuri Producer/Editor: Feranmi Adeoshun Published With Assistance From: Sophie Carr, Kyra Smith, Dylan Scheible

Cosa succede quando il problema non è più trovare lo storage, ma trovare le GPU? E quando i dati diventano così grandi e strategici da condizionare dove e come possono girare le applicazioni?In questa puntata di Cloud Champions Andrea Saltarello incontra Alessandro Dellavedova, Senior Sales Engineer di Qumulo, per una conversazione che parte dal suo percorso professionale e arriva a uno dei temi meno raccontati del cloud: il ruolo dello storage come abilitatore di flessibilità.Si parla di ricerca oncologica, dati non strutturati, cloud ibrido, scarsità di risorse, FinOps e sovranità del dato. Attraverso casi concreti e aneddoti dal campo emerge una prospettiva diversa da quella abituale: non lo storage come semplice repository, ma come strumento per spostare workload, ridurre vincoli architetturali e adattarsi a un mercato in continua evoluzione.Una puntata dedicata a chi vuole capire cosa succede quando infrastruttura, dati e cloud devono confrontarsi con problemi molto reali.

Subscribe to our Newsletter:https://theultimatepartner.com/ebook-subscribe/ Check Out UPX:https://theultimatepartner.com/experience/ https://youtu.be/j0TuosYDQe4?si=7mzUwBe4PrQ-eB2E In this insightful session from the Ultimate Partner Live event in Bellevue, Washington, Vince Menzione sits down with Stephen Boyle, Corporate Vice President for Enterprise Partners at Microsoft, to pull back the curtain on the tectonic shifts redefining the tech ecosystem. Boyle details Microsoft's massive organizational pivot into enterprise and SME/channel divisions , explaining how artificial intelligence acts as the foundational thread unifying systems integrators, software vendors, and digital natives. Moving past market noise surrounding competing foundational models , he highlights Microsoft's strategy to become the ultimate “platform of platforms” by prioritizing user choice, security, and trust. Emphasizing a shift away from infrastructure technicalities and toward practical business outcomes , Boyle delivers an urgent mandate for partners to scale technical talent, eliminate traditional operational silos, and brace for the incoming consumption-driven, agent-based future of enterprise computing. Key Takeaways Microsoft has restructured its global sales divisions into distinct Enterprise and SME/Channel organizations to better target its massive total addressable markets. Artificial intelligence is fundamentally altering the partner ecosystem by dismantling traditional software and systems integrator silos to build interconnected, multi-party solutions. Rather than forcing alignment to a singular model, Microsoft aims to be the definitive platform of platforms by offering extensive choice across over 1,100 language models. The enterprise landscape is rapidly moving past experimental AI pilot phases and entering production setups completely focused on transforming core business outcomes. Tomorrow's service organizations are aggressively evolving into software-minded operations that deploy repeatable, highly specialized internal autonomous agents. Managing tokens and monitoring usage metrics represents the emerging operational baseline for balancing efficiency against the scaling expenses of large language models. If you're ready to lead through change, elevate your business, and achieve extraordinary outcomes through the power of partnership—this is your community. At Ultimate Partner® we want leaders like you to join us in the Ultimate Partner Experience – where transformation begins. Key Tags AI frontier, platform of platforms, enterprise partners, global systems integrators, digital natives, language models, token consumption, agent sprawl, citizen developers, shadow IT, business outcomes, technical enablement, marketplace growth, hyper-scalers, processing fluency, sovereign AI, industry ecosystems, data governance. Transcript [00:00:00] Stephen Boyle: This is the biggest, most transformative, iterative change in technology we’ve ever seen, where, if you wanna call it a paradigm shift or whatever word comes after paradigm shift. [00:00:12] Vince Menzione: We just came back from Ultimate Partner live in Bellevue, Washington, where we hosted incredible leaders for two amazing days. Come join us for this next session where we explore the tectonic shifts we’ve all been seeing. Uh, I am thrilled to invite our next guest up on stage. I’ve known this gentleman for several years back in my days at Microsoft, and, um, we’ve been friends, actually Microsoft, and then we both went and did different things, came he’s come back to Microsoft in a big way. [00:00:46] Vince Menzione: Uh, Steven Boyle, for those of you don’t know, is recently a named the C. We will talk about it in a second, but I, I need to announce you properly. Is the corporate vice president, which by the way in Microsoft is a big deal for enterprise partners. He and Nicole De and I would say are the two Microsoft leaders in the organization. [00:01:06] Vince Menzione: Nicole is the channel chief. Steven has a, a big remit and we’ll talk about that up on stage. But I’m just so delightful for his support and for making the time in a very busy week at Microsoft ’cause this is CEO summit this week to make some time to come with us and be on stage with me. Please welcome my good friend Steven Boyle. [00:01:29] Vince Menzione: Good to see you, sir. To see. So I’m gonna put you on this side. [00:01:33] Stephen Boyle: Okay. [00:01:35] Vince Menzione: The hot seat. So I’m gonna, I, I didn’t do a justice and I, I wanted you to explain your role. I, I think I know, but I think for the, for the people in the room, uh, talk to us what Enterprise Partners means at Microsoft and what that role remit and remit looks like. [00:01:50] Stephen Boyle: Um, CVPs may or may not be important, but one thing they don’t do is get invites to the CEO summit. So I’m super pleased to be here with you guys. No, no, it’s totally cool. It’s totally cool if that phone rings. No, I’m kidding. Doesn’t. So what does it mean? So I’d like quickly, um. January last year, uh, we split the sales organization into enterprise and small to medium enterprise and channel. [00:02:15] Stephen Boyle: You guys probably familiar with that? Nicole is the, uh, chief partner officer lives in the SMA and C world and drives the channel, um, drives our marketplace business and, and a lot of other things. Um, for that 60 billion, um, you know, total addressable market that we have. Down there in SME and C. Um, at the same time, we established enterprise partner as part of Nick Parker’s overall organization. [00:02:40] Stephen Boyle: Um, but for most of 2025 we ran it as global systems integrators and advisories, ISVs and digital natives. So three separate footprints all focused entirely on, on, on enterprise. Um, in December, January, we talked about establishing an enterprise partner leader that would. You know, aggregate all of this stuff. [00:03:00] Stephen Boyle: Um, I was fortunate to come through, um, some frankly, pretty hairy, uh, experiences, I bet with some of our senior leaders. Um, I, I’ve loved to [00:03:08] Vince Menzione: been in the room for that [00:03:09] Stephen Boyle: questions like, why Steven Boyle and things like that, right? And really have to dig deep to, uh, to justify. Anyway, uh, I’m blessed and honored, uh, to run that entire portfolio of partners, uh, for the entirety of the enterprise partner world, which now from a chief revenue officer perspective, belongs to Deb. [00:03:25] Stephen Boyle: Deb Co. So Deb is the enterprise leader for all of our sales that we do into that space. Awesome. Um, I have three regional leaders, Nina Harding here in the United States, Ehab Ra in in Europe, and Heather Gordon in Asia that mirror and replicate and flow down the things that we decide to do from a strategy perspective for the, uh, for the core. [00:03:45] Vince Menzione: And we love Nina. She’s been, she was at our last event, [00:03:47] Stephen Boyle: super, super lady. And, uh, you know, the US is still 50% of our overall business. [00:03:53] Vince Menzione: Yeah. [00:03:53] Stephen Boyle: Too big to fabric. Every time I talk to Nina, I’m like, Nina, you’re too big to fail. We can’t cover you anywhere else. So you know, you’ve gotta be successful here in the Americas. [00:04:01] Vince Menzione: So I think just for breaking it up, I, ’cause I do want to like, it’ll lead to the next question, right? So you have the global systems integrators, all these systems integrators. Essentially you have all of the software companies we used to call ISVs, we now call SDCs or software development corporations. [00:04:17] Vince Menzione: And then you also have the AI stack, I’ll call it. Right? So under Jason Grafe. Yeah. Many, many might know. Jason’s been a guest on the podcast and was Satya’s chief of staff at one time, eight years. Eight years. Wow. I didn’t realize there was that many. [00:04:31] Stephen Boyle: Carry carried a lot of bags for Satya over the years. [00:04:34] Vince Menzione: Unbelievable. Well, let’s, I mean, so AI is an important component, right? And you saw Jay’s, Jay talking, just talking about AI and all these things. I would love to start here, right? Because, uh, you’re, you’re, I wanna get your perspective as Microsoft, your perspective as Microsoft on the biggest shifts you’re seeing in defining this we’ll call AI Frontier. [00:04:54] Vince Menzione: We’re seeing right now, how should partners translate that into how they position and go to market externally? How, how do we need to think about this time? [00:05:02] Stephen Boyle: Yeah, that is, uh, that is a huge question and I’m not sure we’ve got enough time to go into the, into all of the detail. Um, so let me sort of up level it a little bit for you. [00:05:10] Stephen Boyle: And I think, look, the move that we meet at made a couple of months ago and pulling together those three aspects. Nicole had already done it in SME and C. Right. One partner organization across the world with a very common set of goals. We were working closely together, Sandy Gupta, on ISV, Jason on ai, and myself on on si. [00:05:29] Stephen Boyle: But we were still working closely together across silos. So the opportunity for me, 60 days into this role is AI just allows you to wire the partner ecosystem together differently. Right? And even if you look at how we’re going to market an AI today, um. You know, with, with, with chat GPT, with Claude, with Anthropic, um, I think there’s something like 1100 different, you know, language models on Microsoft today. [00:05:55] Stephen Boyle: So the way I think about AI is we are absolutely gonna be the ultimate platform of platforms. Yeah, choice is incredibly important. Um. It’s, it’s, you know, turn the clock back 12 months, everybody was chat gpt five point x, you know, and then six months ago it was Gemini and now it seems to be clawed. And honestly I don’t know what it’s gonna be next quarter. [00:06:15] Stephen Boyle: So the only thing I can do is offer you choice. [00:06:18] Vince Menzione: Yeah. [00:06:18] Stephen Boyle: And from a partner perspective, I think that minimizes or reduces the risk that you have betting on the Microsoft platform because you can go in a multitude of different directions. I know we’re not in Europe, but if you were in Europe and you were worried about G-G-D-P-R and Jay mentioned sovereignty, you’d probably be like lining up really closely to Misra. [00:06:37] Stephen Boyle: Yeah. And a bunch of other Europe, European partners. So wherever you are in the globe, I wanna be that platform choice. Um, and we will lead with our own first party solutions. I hope they’re not coming for me. Um. I parked safely in the hotel. It can’t be me. Um, but you weren’t vibe coding in the room. Um, but you know, wherever you are in the world, in whichever industry you are in, um, it is our intent to, to offer that platform of platforms and to give the broadest set of partners the opportunity to engage with us. [00:07:07] Vince Menzione: I think that’s really important because I, I have found, especially in the last month or two, people are, it’s almost like a knee jerk. Don’t you feel like people don’t know what to do? There’s been so much noise in the press and the media and, and the markets around open AI and anthropic especially. Where do I go? [00:07:26] Vince Menzione: Seems to be like when I, when I sit, I watch everybody in the room here. I think they’re, they’ve all been thinking that as well. So you can, [00:07:31] Stephen Boyle: there’s a, a little bit of a deer in the headlights moment. Yes. And even I like, I get that. Yeah. Um, you know, I saw, uh, Jay slides. Jay, love the presentation. Love the slides, man. [00:07:40] Stephen Boyle: I’m gonna steal several of them. Um, we’ll talk about that later. We, we [00:07:43] Vince Menzione: have the deck, [00:07:45] Stephen Boyle: but, but in all seriousness, you know, this, this is like. It’s a new paradigm. I will date myself a little bit. Some of you might heard me say this. I sold many computers in the 1980s. Mini computers. Some of you in the room are going, what’s a mini computer? [00:07:59] Stephen Boyle: Um, I sold client server for Sun Microsystems in the nineties. I sold an awful lot of Oracle databases in the Auts, I think they’re called, and I’ve done two stints with Microsoft. This is the biggest, most transformative. Iterative change in technology we’ve ever seen. What, if you wanna call it a paradigm shift or whatever word comes after paradigm shift. [00:08:18] Stephen Boyle: Um, and we are building intelligent systems at scale faster than we’ve ever seen. Scalable, mission critical solutions being implemented today inside of Microsoft and with our most important customers. So, and we can’t do it without partners, right? There is absolutely nothing we can do in this industry. I will, I will put the, you know, the elephant in the room out there. [00:08:40] Stephen Boyle: Our ISD organization has between five and 7,000 people. Our forward deployed engineering organization is about a thousand people. [00:08:47] Vince Menzione: Yeah. [00:08:48] Stephen Boyle: So when you look at the scale of the total addressable market that Jay just talked about. We are gonna service directly like this much [00:08:55] Vince Menzione: used to be 5%. Was it even, is it even that high? [00:08:58] Stephen Boyle: I doubt it’s, I doubt it’s even that. And the billions of dollars that we spend every year helping our customers transform to what we’re now calling frontier firms is gonna be, have to be driven with every single person in this room in some way, shape, or form. Judson is not asking Marla to significantly increase ISD. [00:09:15] Stephen Boyle: Not asking John to significantly increase FDE, although we probably will hire in that area just because of the, the newness and the, you know, bright shiny object that everybody’s like, oh, FDE, I’ve gotta have those. We’ve got a thousand already today that have been around in John’s organization for 10 plus years doing the things that we are doing today. [00:09:32] Stephen Boyle: But we are gonna build out that muscle. But the real way we’re gonna build out that muscle is with all of you in this room. That’s like categorical. That is my like, probably number one goal for the next one to three years is make sure that, that story that Jay just told about Microsoft not being involved in AstraZeneca. [00:09:48] Stephen Boyle: I probably won’t tell Judson that Jay, but I love the story. Um, like if you could all do that for me, like win, um, that is so, you know, from our worldwide learning, through our skilling enablement through our cloud solution architects that I personally own. We are pivoting aggressively towards making sure that the partners understand our platforms better than any other job, number one for me right now, if you don’t understand what I’m selling, like I’m kind of dead in the water obviously. [00:10:15] Stephen Boyle: Well, [00:10:15] Vince Menzione: I was gonna ask you why now? Why Microsoft? Why now? Right? Because there is a lot of noise. You know, Google just announced, you all announced your results on the same day, which was astounding. That was freaky, wasn’t it? It was. It was the first time. And the, the total commitment, customer commitment is over a trillion dollars now, I think 1.2 trillion is what I counted up. [00:10:33] Stephen Boyle: Yeah. [00:10:34] Vince Menzione: But it’s saying a lot about like, what do I do now, like as these partners in the room. Um, how, I think you kind of already, and you’ve talked about this, about differentiating where Microsoft is, I think J Slide does a lot of justice there. It says how, uh, Microsoft Partners came into the room, surrounded the customer. [00:10:52] Vince Menzione: It feels like Microsoft has always leaned in big time on partners. Uh, more so I would say than any other organization out there. What would [00:10:59] Stephen Boyle: you say Joe Roses, my chief of staff, business manager and so many other things was telling me last night that, you know, we used to say 500,000 partners. [00:11:05] Vince Menzione: Yeah, [00:11:06] Stephen Boyle: it’s a, it’s a significantly higher number than that as well. [00:11:09] Stephen Boyle: So there’s an element of, you know, back to the deer in the headlights, which partners are, are more important. One of my other phrases that I say on a regular basis, the winners and losers are yet to be decided in this next wave. Like, I want all of us to on the right side of that argument. Right? But, but it’s gonna be a challenge and, and companies are going through shifts. [00:11:28] Stephen Boyle: You know, Accenture, maybe, possibly doesn’t need 750,000 employees in the not too distant future. Maybe TCS at 600,000 doesn’t need 600,000 human employees. So we’re going through this dramatic shift of, you know, what’s the right balance going forward. What I would say about Microsoft is notwithstanding the fact that we’ve figured this out for 51 years, which is a little bit mind blowing, um, that you know, all the way back in the seventies we’ve gone through so many iterative changes. [00:11:56] Stephen Boyle: People have questioned just like they’ve questions. A lot of other technology companies, are you gonna be around for the long haul? I think we’ve proven time and time again, and I love Jay’s story. I’ve used that myself about how many companies disappear on a, on a decade to decade, you know, business. 10 years ago I had the opportunity to listen to Craig Clayton Christensen, who’s sadly no longer with us. [00:12:15] Stephen Boyle: Yeah. But you know, the books that he wrote and the story that he told to Microsoft 2014, we were nowhere in cloud. [00:12:21] Vince Menzione: Yeah. [00:12:22] Stephen Boyle: AWS was so far ahead of us, it was crazy. And he came in and he’s like. You know what? You guys need to be successful. You need to figure out how to cross this chasm again, and we’ve done it time and time again. [00:12:32] Stephen Boyle: You can go back. You know, Microsoft used to be known as a fast follower in ai. I don’t think we’re a fast follower. I think we’re right up there. We’re right at the front, but that race is still being run and the winners are losers are yet to be decided. [00:12:44] Vince Menzione: I was in that room with Clayton Christensen with you, by the way. [00:12:46] Vince Menzione: I remember, I remember that. That was at a Prism conference. [00:12:49] Stephen Boyle: Yeah. Yeah. [00:12:50] Vince Menzione: You men, you touched on this with the GSIs a little bit. How do you see the roles evolving? You know, we, we, we bucketed all, we’ve always been. Fantastic about bucketing ISVs or SDCs and sis and digital natives. Yeah. How does it, how does that all come together? [00:13:06] Vince Menzione: Does it come together any differently in this new AI platform era, or is it the same? [00:13:11] Stephen Boyle: I look, I, I’ve said this for a long time, like if you go into AstraZeneca, the six plus, you know, frontline partners, there’s probably a whole board of second, third tier that, that we don’t know about doing, you know, things across the AstraZeneca group. [00:13:25] Stephen Boyle: It takes several villages and sometimes a small town, especially in my world, in the enterprise world, strategic five hundreds. Yeah. Um, you know, we, we ran some reports a few years ago and it is shocking how many global systems integrators have a footprint in Shell or Exxon or, you know, bank of America or whatever else. [00:13:44] Stephen Boyle: So I’ve always believed that partner to partner is critical. Yeah. I think it became even more critical in the, in the AI world, and I’ll take my new friends at Anthropic. So I went to the first Anthropic partner Summit. Some of you might have been down there in, in San Diego, um, just a couple of months ago. [00:13:59] Stephen Boyle: Same partners, same people from the same partners. In the room, you know, talking about what they’re gonna do together with Anthropic. Um, and I’m looking out across this audience going, okay, well I know him and I know her and I know those guys, and like, I need to figure out how I’m gonna weave this together. [00:14:14] Stephen Boyle: So it’s not just an Accenture and Anthropic or an NTT data and anthropic, but it’s an NTT data plus anthropic plus Microsoft. Story going forward. And then who’s best at delivering those services capabilities? So it’s it at every juncture that I see in the, in the partner community, and this is the, the reason why I argued vehemently with Nick, that it has to be one organization I’m gonna create maybe given a little bit away. [00:14:40] Stephen Boyle: So if you’re recording, stop now. Um, I’m gonna create an enablement organization that is partner agnostic. I don’t necessarily care. I do care about the digital natives, but I don’t care about how I train them. Right. What I’m more important of is how do I train the digital natives in what the sis are doing, and how do I train the sis and what the ISVs Plus digital Natives are doing. [00:15:01] Vince Menzione: Yeah. [00:15:01] Stephen Boyle: That is my, that’s my game plan. If I fail there, then I think we fail to raise the bar and be differentiated in an AI world, and I’m not set up like that today. [00:15:12] Vince Menzione: I wanna, I wanna ask you, uh, uh, because I was looking at Jay’s slide and the, the managed piece is. And we have a lot of managed service providers in this room today. [00:15:20] Vince Menzione: A lot of them, by the way, come from the old school of managed services. The managed piece seems to be like, if I’m doing something today with ai, we’re gonna talk about security next, uh, up on stage here. It seems like there’s a new set of skills or a different approach to the customer, don’t you? Don’t you agree? [00:15:37] Stephen Boyle: I I [00:15:37] Vince Menzione: think you need to keep your hands on the steering wheel at all [00:15:39] Stephen Boyle: times. I think what it boils down to is you can’t do AI unless you do certain other things. [00:15:44] Vince Menzione: Yeah. [00:15:44] Stephen Boyle: Right. You could be a modern work specialist and you could make a lot of money being a modern work specialist, or you could be a, a dynamic specialist. [00:15:52] Stephen Boyle: We just held our, uh, inner A in a circle conference last last week, which I was disappointed to miss for the first time in a few years. Those, those days are, are, are fast becoming over. [00:16:03] Vince Menzione: Yeah. [00:16:04] Stephen Boyle: Um, why? Because everything that I’ve just said is tied together by ai. Yes. And in order to do good ai, you need good data. [00:16:12] Stephen Boyle: And in order to trust everything that you’re getting, as Judson talks about trust and intelligence, you need to wrap that in a really secure [00:16:19] Vince Menzione: Yes. [00:16:19] Stephen Boyle: You know, en en environment. Now we will do our best to provide levels of security into how we deliver ai. But that’s not the end of the game, right? You have to take it all, all the way to the edge. [00:16:30] Stephen Boyle: So that’s why a siloed partner or a singular commercial solution area partner in Microsoft’s terms, has got to transform its business. ’cause if you’re gonna do ai, you’ve gotta do those other things as well. [00:16:41] Vince Menzione: Agreed. I must see the model changing, and in fact, I see like bigger organizations becoming managed service providers in many respects. [00:16:48] Stephen Boyle: Yeah. Yeah. I mean, look, there’s still, there’s still a role for all the old terminology you mentioned is SV to sdc. Yeah. I’m like, I’m been around long enough. Look, it’s ANB still anv, it’s still an isv. Thank you. Independent software vendor. Um, and it’s, you know, where, where AI is allowing software to be, you know, frankly developed in a number of different places. [00:17:07] Stephen Boyle: We are all citizen developers. Um, you know, I was on a call with our internal leadership yesterday, um, and you guys might have heard this story ’cause I think it came out at Ignite. When we turn the agent 365, around and on ourselves. We found 130,000 agents running across Microsoft that had been developed and deployed internally with, I mean, you could call it shadow it. [00:17:28] Stephen Boyle: I guess that would be one phrase that you would use for it, but the reality is if you, if you haven’t got something to do your job today, you have the tools. To build it really, really fast. Um, and that, you know, that’s, that’s a great opportunity for people to be able to do their work, you know, in a better and in a different way. [00:17:45] Stephen Boyle: But it’s also a huge opportunity to make sure that data governance and security and all the other things that we need to deliver are there out of, out of the gate and out of the platform that we deliver. So security’s absolutely critical. Not saying that managed services won’t grow, um, at, at some level as well, but only if they transform into this multifaceted way. [00:18:04] Stephen Boyle: Yeah. Thinking [00:18:05] Vince Menzione: about, well, that’s what I was, I was gonna lead to here with innovating. It’s happening across, I mean, we’re talking about chips, we’re talking about foundational models, LLMs, we’re talking about applications, we’re talking about agents. How should we think about where to play and how to differentiate as partners in this room? [00:18:22] Stephen Boyle: I think. [00:18:25] Stephen Boyle: So look, I mean, one, one of the ways that Judson talks about it is I think silicon’s gonna change over time. Yes. NVIDIA’s definitely the 800 pound gorilla, maybe the 8,000 pound gorilla. Yeah. Uh, but you know, if you read the press, there’s, there’s things happening in, in different places as first party silicon, which we clearly are, are developing, um, in a quantum direction for sure. [00:18:45] Stephen Boyle: Um, there’s lots of different language models that haven’t even been launched on, on, on the marketplace yet, so. You know, Judson’s trying to uplevel our conversations. You’ll hear us talking about conversations more and more as we go into FY 27, um, that obviate all of those layers. Just like even when I was selling Sun Microsystems, it was about the business outcome and the business solution that we were solving for not necessarily the fastest piece of hardware or the best client service solution on, on the market. [00:19:17] Stephen Boyle: So I think what’s gonna happen over the next 12 to 24 months is we’ll have so many different models to choose from. We’ll have more silicon to choose from, but those won’t be the real buying decisions. The real buying decisions of what? How am I trying to transform my finance organization, my HR organization, and my supply chain? [00:19:36] Stephen Boyle: Because the underlying technology, Judson says commodity I, I guess I can go with that. It will be commoditized and we’ll really start to focus back on what the important things are. We’re moving a lot from pilot to production. You guys have probably seen that. The numbers that Jay just showed about how many. [00:19:52] Stephen Boyle: Projects are failing, is getting less and less because we’re getting smarter and smarter about what it takes to actually drive the business outcome. And I need all of us to be talking that same language. Yeah. Having conversations with head of HR about how we’re gonna transform human capital management in the, in the age of agents, if you like, like the underlying platform. [00:20:14] Stephen Boyle: It’s not, don’t worry about it. You wanna be on a secure platform. Don’t get me wrong. But at the same time, I don’t think we, we spent too much time worrying about that. [00:20:21] Vince Menzione: Yeah. We’re not, what you’re saying is we’re not spending enough time on outcomes. On the business outcomes. Right. And that’s where we need to focus. [00:20:27] Vince Menzione: We’re, we’re focusing on, I, I feel like we’re, it’s a signal to, to noise ratio that we’re living through right now. There’s too much noise. [00:20:33] Stephen Boyle: Yeah. [00:20:34] Vince Menzione: And we’re not focusing on the signal. I think that’s what you’re saying. [00:20:36] Stephen Boyle: I, it’s got to be, I mean, to be honest with you, it’s always been, you know, even when I sold what I would perceive, you know, sun in the nineties was a rockman ship to the stars and, you know, kind of sad what happened to that company. [00:20:47] Stephen Boyle: Um, but we, we were, we were fixated on, we had the best client server. But, but nobody was buying, you know, a piece of Sun hardware as a room heater, which is all it did, you know, like for the longest. But if you had SAP, if you had Cybase, if you had Bond, remember Bond, I mean all of those applications that drove the business outcomes, we’ve gotta get back to that kind of mentality. [00:21:09] Stephen Boyle: Yes. And worrying a little bit less about the underlying architecture. Yeah. It needs to be, it needs to be part of the conversation. ’cause it needs to deliver trust and security and intelligence and everything else. Then you need to rapidly move to what are you trying to achieve and how can we ensure the, the, the success of, of your business outcome. [00:21:27] Stephen Boyle: And look, I mean, Palantir pri you know, sort of came out and said, well, the way we do that is through forward deployed engineering. Um, and they stole the show. And, and, you know, they’re, they’re doing very well as a result of doing that. Uh, but if you go and talk to, um, Tom Siebel’s organization at C3 ai. [00:21:43] Stephen Boyle: They’ve had FDS for quite a while. You know, I told you about John Chuchu 10 years ago. John Chu, Chuck’s job was to go and get all the applications that we needed on the Microsoft phone. Remember that? [00:21:54] Vince Menzione: Yes. Um, [00:21:55] Stephen Boyle: you know, so we’ve pivoted John o over the years to doing what he’s doing now, which is to go sometimes in partnership with, with partners into the customer and say, what is it you’re trying to achieve? [00:22:05] Stephen Boyle: Let me show you how I can build that for you in three weeks or three months. That might have taken you three years. We literally just did a hackathon with one partner last, last, last week with, uh, with our ISE organization, the, the, the forward deployed, uh, group that John runs. Um, and one of the big customers said, I’ve just done in three days what would’ve taken me three months. [00:22:26] Stephen Boyle: Now he hasn’t productized it and rolled it out and blah, blah, blah. But the reality is that is how fast things are changing. And this was not a small company. This was a very, very large oil company, and they were like blown away by how much we can achieve. We’ve gotta do that at scale. [00:22:41] Vince Menzione: Yeah. [00:22:42] Stephen Boyle: You know, we, we have a commitment to scale our FDE community through partnerships to touch all of the S 500 in a very personalized way. [00:22:51] Stephen Boyle: And then, you know, at a slightly, you know, lower ratios down through the, through the majors and into, into Nicole’s SME and C world as well. [00:22:59] Vince Menzione: Jay talks about the decade of the ecosystem. He coined that term back, back on a podcast way back in nine, in, uh, in 2020. Microsoft has been at the, for, we used to call partner to partner back, back in the day. [00:23:10] Vince Menzione: Mm-hmm. Do you remember those days? How do you think about this ecosystem evolving and what steps are you taking to help bring these organizations together? Because I, I, again, we look at the seven seats or 6.3 seats at the table. The customer has the power now that they didn’t have before. ’cause they have the commitment with like with Microsoft and they can buy off of the marketplace and pull together multiple organizations to go, go do that. [00:23:34] Vince Menzione: How do you think about helping to orchestrate that as the leader of the enterprise partner business? [00:23:39] Stephen Boyle: So I’ll start with a really big example, and I’ll try and sort of scale it down a little bit. But my friends at Accenture, with the Accenture, Microsoft Business Group, we spend an awful lot of time, you know, in, in each other’s pockets, in each other’s deals. [00:23:51] Stephen Boyle: We know everything that’s going on in the Accenture, Microsoft Business Group. And a couple of weeks, or maybe a month or so ago, I was told that the Microsoft Business Group is now larger than the SAP Business group. It probably flip flops. [00:24:03] Vince Menzione: Yeah, [00:24:04] Stephen Boyle: it won’t be too long before the Anthropic Business Group is bigger than both of those. [00:24:08] Stephen Boyle: So what I need my Microsoft team to do is to not spend all of their lives in the. A MBG, the Azure, the Accenture, Microsoft Business group, but to go make friends in the Anthropic Accenture Business group and frankly still to make friends in the SAP business group and maybe in the Oracle Business Group and the list goes on. [00:24:27] Stephen Boyle: So at a macro 11, in the very largest accounts where we haven multiple practices, where we haven’t spent time before, I’m gonna. Push my people into uncomfortable zones and I’m gonna push them to go into those other areas and I’m gonna load them up with technical talent and cloud solution architects and ai, you know, forward deployed engineers. [00:24:45] Stephen Boyle: And I’m gonna force different people to talk together that haven’t talked together. So I can do that in TCS. I can do that, Capgemini, I can do that. Um, you know, in Europe with Capgemini and Misra is a classic example. Um, with the, with the Indian sis, Indian based sis, they’re all big enough where I know all the practices exist. [00:25:04] Stephen Boyle: I just need to do a better job of, of talking to them. Now, when you downsize that into, you know, into a, a company that doesn’t have all of that scale, this the same truth still holds. I need to talk to people who aren’t necessarily motivated every single day to do something with Microsoft. I need to talk to people who are motivated to do something with an AI partner or even a traditional SaaS partner. [00:25:27] Stephen Boyle: I noticed yesterday, actually no, this morning I got a notification that we just passed, um, a billion dollars in revenue on the marketplace with ServiceNow. [00:25:35] Vince Menzione: Nice. [00:25:36] Stephen Boyle: Um, and I think AWS announced the same thing, by the way this month as well. Um, so thank you to the ServiceNow people. Yeah. Um, you know, that is that there’s a tremendous demonstration of how far we’ve come in marketplace. [00:25:48] Stephen Boyle: ’cause that’s another one where we trailed AWS quite significantly. But with the right partnerships. And driving the right motions, we can, you know, we can definitely catch up and we will continue to pass, uh, some of, some of the other hyperscalers in, in, in that way. So really the bottom line to your question is partner to partner is still real. [00:26:08] Vince Menzione: Yeah, [00:26:08] Stephen Boyle: how we do it and what we use to tie things together. And I know that compensation drives behavior and we’re not gonna get into a compensation about like how we get compensated and everything else, but the reality is I’ve gotta break down those barriers and those silos and I’ve gotta deliver real meaningful enablement and practice development so that, so that the people who sit in the Anthropic business group and the people who sit in the Microsoft Business Group are spending as much time together as they are with me. [00:26:34] Stephen Boyle: That makes sense. Simply put, that’s what I, I need to achieve at scale rapidly. [00:26:40] Vince Menzione: So to, we’re getting close to time here, but as you look forward, what would define the most successful partnerships in this ecosystem? Is it, is it what you described, the opening up the aperture or for the, for the leaders in the room here today, what should they go do better and differently? [00:26:58] Stephen Boyle: Um, so obviously we’re closing out this fiscal, we’ve got Microsoft start and Microsoft start for partners coming up in July. Um, I mentioned the fact that we’re, we’re driving. Cu customer engagement through the lens of conversations and how do we achieve business outcomes? I would encourage you to, to gravitate, if you like, above the commercial solution areas where you might have understood, this is how I interact with Microsoft today. [00:27:23] Stephen Boyle: Um, and abstract it up to that AI layer. You know, think about trust, think about intelligence, think about business outcomes, and how do I potentially weave together a story? If I’m in the dynamic space, how do I get better in data? If I’m in the data space, how do I get better in. In that modern work environment, but really use AI as the overlay to, to help tie that together. [00:27:44] Stephen Boyle: That’s one thing. The second thing is if we’re not training you in the right direction, it’s stevenBoyle@microsoft.com. Let me know. Awesome. Um, we’ve got programmatic stuff, um, you know, and we’ve got high touch stuff as well. So I think this is, this is another time where Microsoft is gonna over pivot on all of the training and enablement that we need to do to make sure that you’re, you know, you’re grounded in our platform. [00:28:07] Stephen Boyle: Um, I think there’s a huge opportunity with this agenda future to become more of a software partner. You know, even the deepest services organizations are going to need agents, and the more successful ones will be the ones that can turn on those agents in a repeatable way. So. Our agents, the new SaaS. I’m not exactly saying that, but I think that the agen future is one where even the more services oriented companies will, will have teams of agents that they’re deploying. [00:28:35] Stephen Boyle: In fact, I had a very, very large systems integrator, um, in, in the EBC just about a month ago, three weeks ago. Um, and I was sat next to their head of consulting and he showed me what he called his God dashboard. Uh, and right in the middle of his God dashboard there are like 450 accounts. All of whom I recognized, ’cause they were all in the enterprise, right in the middle of his dashboard was, how many tokens am I spending? [00:29:00] Vince Menzione: Yeah. [00:29:01] Stephen Boyle: Like, not like what’s my daily runway? You know, not am I making a profit on that account or anything else like that is like, how many tokens have I consumed? Yeah. Because there is an awful lot of, that is the new juice, if you like. That’s, that’s driving the success. You can have the smartest people on the planet, but you’ve got to still arm them with all the best tools that are available out there. [00:29:22] Stephen Boyle: So it’s fascinating to listen to him, how he had gone through that thing of, you know, agent sprawl, how many are really working, how many are not working? How can we prove that? You can prove it through, you know, managing your tokens. There’s a new version of. Finops for tokens, for want of a better phrase, that’s gonna be critical for us all to understand. [00:29:40] Stephen Boyle: ’cause they’re not cheap, they’re not free, that’s for sure. And, and they might not be cheap if you’re not, if you’re not managing them and using them effectively. Yeah. So that’s the other thing that I would really get on top of. And, you know, we’re gonna make some announcements in the not too distant future about the consumption driven future. [00:29:56] Stephen Boyle: Um, that, that we will, that we will deliver with our first party and third party platforms going forward. So that’s another. Another critical thing [00:30:03] Vince Menzione: sounds like some exciting announcements. Pretty soon. [00:30:06] Stephen Boyle: Yeah, could look close. Quarter four, help me close. Quarter four. Yes. That’s priority number one, two, and three right now. [00:30:12] Stephen Boyle: Uh, but get ready for some, you know, for some new announcements in July. Um, look, the future is incredibly bright with Microsoft. It’s incredibly bright in the industry as a whole, right? I mean, let, let’s be honest, the, the growth targets that we will have for ne next year are astronomical, and we will not make them without the partner community that we have, without training and enabling the partner community that we need for tomorrow. [00:30:34] Stephen Boyle: So like, stay close, you know, stay engaged. Talk to your partner development managers, talk to the talk to field reps, talk to the accounts that that, that you are in, and stay as close as you possibly can to our emerging strategy. And, um, you know, look, I, I think if I had fivefold or tenfold the people I have today, I still wouldn’t be able to touch everybody that I would like to touch in the partner community. [00:30:58] Stephen Boyle: So I’ll apologize in advance. Um, but we’re gonna have some, you know, some really cool ways of learning. Um, and we’re gonna make sure that they’re available to the widest possible audience. [00:31:07] Vince Menzione: Well, we bring the practitioners and the experts in the room to help with that as well. Right? Yeah. Because you can’t always have a partner development manager tied to everybody in the room. [00:31:14] Stephen Boyle: I, I would do hackathons on AI every week with every partner and every part of the world, but I can’t. [00:31:19] Vince Menzione: Yeah, exactly. Well, so good to have you today. Thank you. So good to see you again. I don’t know what your schedule is like. I, we didn’t, we don’t have enough time for questions. [00:31:28] Stephen Boyle: That’s cool. [00:31:28] Vince Menzione: From the audience. [00:31:29] Stephen Boyle: I’m gonna stay around for a little [00:31:30] Vince Menzione: while this [00:31:30] Stephen Boyle: morning and I’m coming back [00:31:31] Vince Menzione: for cocktails. Alright, terrific. So. Stephen Boyle will be here for cocktail hour. Thank you. Four 30 and uh, I wanna thank you, sir. So good to have you. Thank you. Good to see you. Absolutely. [00:31:42] Stephen Boyle: So much. Absolutely. Hey, thanks everybody. [00:31:43] Stephen Boyle: Thanks for what you do today, and hopefully thank you for what you do tomorrow as well. [00:31:46] Vince Menzione: Thank you. An incredible leader. [00:31:49] Stephen Boyle: Don’t forget, ultimate [00:31:51] Vince Menzione: partner Alive is coming soon, June 18th at our executive breakfast in New York. I hope to see you there.Description The Future of Tech is Here. Subscribe to our Newsletter:https://theultimatepartner.com/ebook-subscribe/ Check Out UPX:https://theultimatepartner.com/experience/ I

What happens when two cloud economists leave AWS  behind and spend six days hiking 60 miles on the Appalachian Trail? Corey Quinn sits down with Caleb Hurd to share stories from the trail, including exploding sleeping pads, heroic shuttle drivers, lost phones, and the unique community that makes long-distance hiking special. Along the way, they draw surprising parallels between backpacking and cloud economics, discussing everything from serverless architecture and cloud cost optimization to the hidden challenges of on-prem infrastructure. It's a conversation about technology, adventure, perspective, and why sometimes the best way to solve complex problems is to step away from them entirely.Show highlights:(00:00) Why Hiking Hooks You(00:15) Meet Caleb on the Trail(01:31) Trail Miles and Ultralight Parallels(05:24) The Sleeping Pad Blowout(07:46) Shepherd Saves the Day(09:43) Trail Community and Cloud Community(11:07) Post Trail Perspective and Inside Jokes(15:35) Back to Work On Prem vs Cloud Pain(25:47) Server-less Spend and Lambda Sprawl(32:29) Wrap Up Where to Find CalebAbout Caleb: Caleb Hurd is a Cloud Economist at Duckbill, where he helps enterprises make sense of their cloud spend. Before moving to the cost side of the house, Caleb spent years in the trenches building and operating large-scale cloud environments and leading the engineering teams behind them across companies ranging from healthcare tech to enterprise Saas. He also founded CostOps.cloud, an AWS cost consulting practice, and is a vocal advocate for engineering-led FinOps — arguing that the people closest to the architecture should be the ones driving cost strategy, not spreadsheet jockeys in finance. Caleb holds a degree from Georgia Tech and made an unconventional journey into tech from a background in carpentry, which may explain his preference for building things over just talking about them. He's based in Atlanta.Links:LinkedIn: https://www.linkedin.com/in/calebrhurd/Sponsored by: duckbillhq.com

Innovation isn't about funding, it's about how organisations are built and led. Progress comes from cutting bureaucracy, empowering mission-led teams, and asking the right questions to unlock bold breakthroughs. This week, Dave, Esmee and Rob are joined again by André Loesekrug-Pietri, Chair and Scientific Director of the Joint European Disruptive Initiative (JEDI, Europe's ARPA) to explore how Europe can turn moonshot ambitions into reality by building the right people, culture and operating models for future-shaping organisations. TLDR00:41 – Introduction01:14 – Hang out: Esmee returns and the missing API has been found!05:14 – Dig in: Staying in step with global innovation12:57 – Conversation with André Loesekrug-Pietri1:02:26 – Roland Garros tennis, and unlocking creative energy GuestAndre Loeskrug-Petri: https://www.linkedin.com/in/andrepietri/X: @eurojediwww.jedi.foundation HostsDave Chapman:  https://www.linkedin.com/in/chapmandr/Esmee van de Giessen:  https://www.linkedin.com/in/esmeevandegiessen/Rob Kernahan:  https://www.linkedin.com/in/rob-kernahan/ ProductionMarcel van der Burg:  https://www.linkedin.com/in/marcel-vd-burg/Dave Chapman:  https://www.linkedin.com/in/chapmandr/ SoundBen Corbett:  https://www.linkedin.com/in/ben-corbett-3b6a11135/Louis Corbett:   https://www.linkedin.com/in/louis-corbett-087250264/ 'Realities Remixed' is an original podcast from Capgemini

AI is reshaping every corner of the technology industry and this week's headlines prove it. On this episode of the Tech Field Day News Rundown, Tom Hollingsworth and Vincent Celindro break down AWS's new AI-powered FinOps Agent designed to control runaway cloud costs, SpaceX's massive $920 million-per-month AI infrastructure deal with Google, and OpenAI's confidential IPO filing that could redefine the next wave of tech investment. They also examine an AI-designed universal vaccine that could help prevent future pandemics, Google's transformation of NotebookLM into a full AI research platform, Sectigo's push to secure AI agent identities, and Anthropic's warning that AI is accelerating cyberattacks from “N-day” to “N-hour” threats. From cloud economics and cybersecurity to healthcare and Wall Street, this episode explores how AI is rapidly changing the future of business and technology.This and more on the Tech Field Day News Rundown with Tom Hollingsworth and Vincent Celindro. Time Stamps: 0:00 - Cold Open0:37 - Welcome to the Tech Field Day News Rundown1:20 - AWS Unveils AI FinOps Agent to Cut Cloud Costs Automatically3:16 - SpaceX Lands $920M-a-Month AI Cloud Deal with Google Before IPO7:36 - AI-Designed Universal Vaccine Passes First Human Trial9:36 - Google Supercharges NotebookLM with AI Research Agents and Code Execution13:58 - Sectigo Brings AI Agents to Certificate Management with New MCP Server16:00 - Anthropic Warns AI Can Turn N-Day Vulnerabilities into N-Hour Threats20:30 - OpenAI Files for IPO as AI Giants Race to Wall Street 28:42 - The Weeks Ahead30:06 - Thanks for Watching the Tech Field Day News RundownTune in every Wednesday for the IT news of the week with a variable degree of snarkiness. Guest Host: ⁠⁠⁠⁠⁠Vincent Celindro⁠, Director of Strategic Sales and Technology, Quantum Foundry Follow our hosts ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Tom Hollingsworth⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠, ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Alastair Cooke⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠, and ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Stephen Foskett⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠. Follow Tech Field Day ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠on LinkedIn⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠, on ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠X/Twitter⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠, on ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Bluesky⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠, and on ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Mastodon⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠.

The episode examines a structural shift in the MSP business model driven by the introduction of AI-linked consumption-based pricing layered on top of traditional per-seat fees. This emerging mechanism, typified by Microsoft's E7 license, adds variable AI consumption charges to otherwise predictable monthly service costs. Vendors are restructuring partner payment models, with Microsoft's move closely watched by others, signaling a wider potential for volatility in the recurring revenue foundations of MSPs, according to analysis from Jay McBain and recent channel data. The most consequential development is Microsoft's E7 pricing, which explicitly adds an AI consumption cost to the standard per-seat license. This move introduces variability at “machine speed,” in contrast to previous examples such as cloud storage, where consumption remains predominantly human-driven and thus more predictable. Analysts note that similar micro-consumption models—charging per conversation, process, or API call—are being adopted by hundreds of companies. Market data from Omnia and referenced industry research places the global IT spend at $6 trillion in 2026, with two-thirds delivered by channel partners and a rapid shift from fixed, subscription models toward micro-consumption billed at a granular, usage-based level. Supporting evidence includes the lack of sufficient vendor-provided controls for variable consumption, leaving MSPs exposed to unplanned cost spikes. While large enterprises are introducing robust FinOps practices and loading up cloud credits, smaller MSPs serving SMB customers are not prepared with similar governance structures. There is also vendor-led encouragement for AI adoption—such as persistent in-app assistants—that drive up consumption before adequate controls or cost-passing mechanisms are established. The sustainability of current pricing models is further questioned by the fact that providers like OpenAI and Anthropic are themselves subsidizing significant portions of token usage, distorting true costs throughout the value chain. For MSPs and IT service leaders, these developments mean greater exposure to unpredictable costs, potential margin pressures, and increased contractual risk tied to AI consumption. Operators cannot rely on vendors to provide spend caps or consumption governance today; failure to build internal controls or pass-through mechanisms may result in absorbing unpaid liabilities. Accountability for AI-driven actions, remediation, and configuration changes will rest with the MSP, elevating both operational complexity and liability exposure. The current environment requires building governance, audit trails, and spend management capabilities now, ahead of broader market adoption of AI consumption models. Supported by: CometBackup

Realities Remixed, formerly known as Cloud Realities, launches a new season exploring the intersection of people, culture, industry and tech.Life sciences are at a turning point, where scientific innovation, regulatory pressure, and patient expectations collide with unprecedented advances in data, AI, and digital platforms. IT is no longer a supporting function but a critical driver of how therapies are discovered, developed, scaled, and delivered safely and at speed.This week, Dave and Rob kick off the Life Sciences mini‑series with Thorsten Rall, Global Industry Lead for Life Sciences at Capgemini, to exploring the current state of the sector, the key themes shaping the episodes ahead, and what it takes to drive better patient outcomes. TLDR00:30 – Introduction to Life Sciences and co‑host Thorsten Rall04:37 – Hang‑out: Navigating Waterloo Station07:50 – Deep dive with Thorsten Rall into the Life Sciences landscape28:03 - What are the main challenges in the sector and main themes45:31 – BBQ season is starting HostsDave Chapman:  https://www.linkedin.com/in/chapmandr/Esmee van de Giessen:  https://www.linkedin.com/in/esmeevandegiessen/Rob Kernahan:  https://www.linkedin.com/in/rob-kernahan/with co-host Thorsten Rall: https://www.linkedin.com/in/thorsten-alexander-rall-b232185/ ProductionMarcel van der Burg:  https://www.linkedin.com/in/marcel-vd-burg/Dave Chapman:  https://www.linkedin.com/in/chapmandr/ SoundBen Corbett:  https://www.linkedin.com/in/ben-corbett-3b6a11135/Louis Corbett:   https://www.linkedin.com/in/louis-corbett-087250264/ 'Realities Remixed' is an original podcast from Capgemini

Neste episódio do Cabeça de Lab, vamos entender melhor o que é o Radar da Nuvem, o principal benchmark de custos e maturidade de cloud do mercado brasileiro.Falamos sobre o real cenário de adoção de nuvem no país, o dilema entre multicloud estratégica e a herança de arquiteturas complexas, e onde estão as maiores resistências do mercado hoje. Além disso, debatemos o avanço dos workloads de dados e IA, os verdadeiros desafios entre custo e conhecimento, a maturidade de FinOps no Brasil e os dados mais surpreendentes da pesquisa que revelam o futuro da tecnologia para o próximo ano.Nos siga no Twitter e no Instagram: @luizalabs e @cabecadelabDúvidas, cabeçadas ou sugestões? Mande um e-mail para cabecadelab@luizalabs.com⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ ___Participantes:MÔNICA HILLMANN | https://www.linkedin.com/in/monicamhillman/?locale=ptLÚCIO CORDEIRO | https://www.linkedin.com/in/luciocordeiro/

Realities Remixed, formerly known as Cloud Realities, launches a new season exploring the intersection of people, culture, industry and tech.Today's most pressing challenges arise from the collision of rapid technological change with deepening economic inequality, weakening democratic systems, geopolitical instability and accelerating climate pressure, leaving world leaders wrestling with how to govern and solve these deeply interconnected crises.This week, Dave, Esmee and Rob are joined by Dex Hunter-Torricke, Founder & President The Center for Tomorrow to explore how tech can solve world macro issues. TLDR00:33 – Introduction00:40 – Hang out: The Boys on Amazon Prime final episode (spoilers) 06:02 – Dig in: How to solve world macro issues? 07:45 – Conversation with Dex Hunter-Torricke 44:52 – Writing a book and meeting world leaders GuestDex Hunter-Torricke: https://www.linkedin.com/in/dextb/https://www.centerfortomorrow.com/ HostsDave Chapman:  https://www.linkedin.com/in/chapmandr/Esmee van de Giessen:  https://www.linkedin.com/in/esmeevandegiessen/Rob Kernahan:  https://www.linkedin.com/in/rob-kernahan/ ProductionMarcel van der Burg:  https://www.linkedin.com/in/marcel-vd-burg/Dave Chapman:  https://www.linkedin.com/in/chapmandr/ SoundBen Corbett:  https://www.linkedin.com/in/ben-corbett-3b6a11135/Louis Corbett:   https://www.linkedin.com/in/louis-corbett-087250264/ 'Realities Remixed' is an original podcast from Capgemini

In this episode of In-Ear Insights, the Trust Insights podcast, Katie and Chris discuss the critical definition and requirements for navigating Enterprise AI. You’ll learn how to distinguish between consumer-grade tools and the strict standards required in regulated industries. You’ll discover the twenty essential pillars for building a secure and compliant AI strategy for your organization. You’ll understand why rigorous vendor scrutiny matters as much for software as it does for human talent. You’ll gain clarity on the governance frameworks necessary to prevent data leaks and legal vulnerabilities in your enterprise. 00:00 – Introduction 03:15 – Defining Enterprise AI vs. SMB AI 07:45 – The role of Microsoft Copilot in regulated environments 12:20 – The 20 components of Enterprise AI readiness 18:10 – Challenges in organizational adoption and change management 22:30 – Security and data privacy as the foundation 27:00 – Call to action Watch this episode to master the complex landscape of regulated AI and safeguard your company’s future. Watch the video here: Can’t see anything? Watch it on YouTube here. Listen to the audio here: https://traffic.libsyn.com/inearinsights/tipodcast-enterprise-ai-101.mp3 Download the MP3 audio here. Need help with your company’s data and analytics? Let us know! Join our free Slack group for marketers interested in analytics! [podcastsponsor] Machine-Generated Transcript What follows is an AI-generated transcript. The transcript may contain errors and is not a substitute for listening to the episode. Christopher S. Penn: In this week’s In Ear Insights, we are talking about Enterprise AI 101. I am in the midst of a series in the Trust Insights newsletter, which you can get at TrustInsights.ai/newsletter. Part one was last week on seven different aspects of enterprise AI. But Katie, you said it would probably be helpful to level set what enterprise AI is and how it differs from SMB AI, mid-market AI, consumer AI, and so on. Katie Robbert: It is interesting because I feel like every time we jump on to record a podcast, there is a whole new set of vocabulary that I need to get caught up with. We need to make sure that everyone else knows what we are talking about because there is nothing worse than listening to a podcast or reading an article and having no idea what the author is talking about because they are introducing a concept but not really explaining it. I wanted to take this episode to talk about what enterprise AI is. Since you and I have not defined it, I am going to take my best guess at what enterprise AI is using some logic and deduction. I could be wrong, and that is why I think it is worth covering. From my perspective, if I had to put a definition to it, I am assuming enterprise AI is the type of AI implementation that occurs at an enterprise-size company. That sounds overly simplistic, but the bigger the organization, the more red tape, the more politics, the more departments, the more stakeholders, and the more governance there is. There are a lot more complications versus a small business like we are, where we can just decide one day, “Hey, I am going to start using this tool.” There are no real hurdles to go through. Then you have those mid-sized companies where you start to introduce some of those hurdles. You might need to work with your IT team to make sure that everything is in compliance. You might need to make sure that you have a place to host these new pieces of software, and that is not something that the marketing team is necessarily responsible for. Then you get to the enterprise-size companies where everything is completely siloed. Even in the best enterprise-sized companies, you are going to run into these silos. Because no one person is responsible for everything, you typically have multiple CEOs. Depending on what part of the country you are in, you might have a board for every different division of the company. If you are a Procter & Gamble and you have hundreds of product lines underneath, each of those is their own individual business. Each of those businesses are not necessarily talking to each other or sharing resources. That is my logical guess at what enterprise AI is. Christopher S. Penn: That is what I started with until I started doing the research into it. I realized that is not what it is. The generally accepted definition is AI within any commercially regulated entity. I realized as I was going through the research that commercially regulated means you have external regulation imposed on the company. It might be a 50-person company, but if they work in HIPAA or FINRA, they have to behave in highly regulated ways. Whether you are publicly traded or, for example, colleges that have to adhere to FFIEC rules and FERPA rules, enterprise AI is about operating AI—whether classical or generative—in a commercially regulated environment where you have externally mandated requirements that you must meet. Your definition for small business stuff makes total sense in that environment because Trust Insights is not a regulated company. However, when we work with our healthcare clients, we have to behave as though we are an enterprise company because we have to conform to their requirements. Katie Robbert: I am glad we are talking about this because the terminology is confusing; when you think of an enterprise company, you are not thinking of a commercially regulated company. I have to wonder why it is not called commercially regulated AI versus non-commercially regulated AI. It is a mouthful and a little bit harder to remember, but it is more descriptive and more accurate. I think like me, a lot of people are going to get confused about what enterprise AI actually is. Christopher S. Penn: A lot of this is because our background is in marketing, so we use the term enterprise to just mean a big company. If we want to market to enterprise companies, we are not marketing to a 50-person firm; we are marketing to a 50,000-person firm. In a lot of CRM software, the dividing line is typically 10,000 employees or 100 million in revenue. This is especially relevant because you see a lot of AI companies like Anthropic and OpenAI in a fight with Microsoft to try and gain a foothold into those enterprises. Microsoft, with their Copilot offering, has dominance by the very fact that their legacy Office 365 stuff is approved in those regulated environments. Katie Robbert: It is ironic because we spent so much time admittedly dismissing Microsoft’s Copilot as the less than version of generative AI, and now Microsoft is getting the last laugh on everyone. They are saying, “You have to use me because I have already been approved by IT and governance, and good luck.” You are stuck with whatever I decide to give you. If I were Microsoft, I would be petty and say, “You guys spent way too much time dismissing me and calling me inferior, so too bad.” Christopher S. Penn: A lot of that, as we have talked about many times on stage, is that the reason Copilot has fewer capabilities than other systems is specifically because of the regulated environment. It is trivial for Google to foist something on consumers and say, “Now we are going to read all your Gmail.” That does not fly in a regulated industry. Katie Robbert: That understanding is really helpful to the people who are saddled with Microsoft Copilot because we hear complaints about why they cannot use other shiny objects. If you are in a 50,000-person company and you weren’t there when the regulatory standards were decided upon, you are sitting there wondering why you cannot use Gemini to generate ad headlines. Then you do it on the side and get in trouble because there is no clear documentation saying why you have to use Copilot and nothing else. What we are hearing is that employees in companies required to use Microsoft Copilot are using other models on the side. That information is still getting filtered into the organization, and it is a huge governance problem. Christopher S. Penn: Completely. In enterprise AI, there are 20 different components to being ready. I derived this from the US federal government's NIST AI regulations and the EU AI Act, which is the gold standard. Katie Robbert: I want to see if you can get all 20. Christopher S. Penn: One, Strategy and Operating Model; two, Governance Policy and the AI Council; three, Legal, Regulatory, and Compliance. Katie Robbert: Are you reading this off a screen? Christopher S. Penn: I am 100% reading this off the Trust Insights Enterprise AI Landscape Field Handbook. Katie Robbert: Fine, continue. Christopher S. Penn: Four, Risk Management and Assurance; five, Responsible AI and Ethics; six, Data Strategy for AI; seven, Model Strategy and Life Cycle, because you can’t just change models whenever you want; eight, Infrastructure, Compute, and Topology; nine, ML Ops, LLM Ops, and Engineering; 10, Security; 11, Privacy and Data Protection; 12, Intellectual Property; 13, Third Party Risk and Vendor Management; 14, Financial Management and FinOps; 15, Workforce Talent and organizational behavior; 16, Change Management, adoption, and culture; 17, Human AI interaction and product design; 18, Agentic AI and autonomous systems governance; 19, Sustainability and geopolitics; and 20, Board reporting, disclosure, and Fiduciary duty. Katie Robbert: I just heard a whole lot of new job opportunities listed. So, if someone were working in a regulated industry like pharma, these are the 20 things they would need to be aware of before evaluating generative AI. It is interesting that organizational behavior and change management are part of it. You would think the regulations would be more technical versus human, but I am surprised that is part of it. Christopher S. Penn: It makes sense because in order for any AI to succeed in an enterprise with 50,000 or 300,000 employees, you have to prioritize change management. Organizational behavior cannot be an add-on; they have to be baked into what you do from the beginning, otherwise your initiative is going nowhere. Katie Robbert: I don’t disagree, but the typical way that works in a large organization is top-down. They make a decision, and you walk in the next day to find it has automatically updated your computer settings. Now you can no longer use a web browser search; you have to use Microsoft Copilot. That is their version of change management, but it is really just a dictatorship from above. I am interested in future episodes to explore what that should look like in a regulatory environment. Christopher S. Penn: We have known for two years that adoption is the hardest part. Deployment is easy compared to adoption. You can put Copilot on someone's desk, but they may not use it even if you tell them they have to. It comes back to how you get them to see the benefits. That is where frameworks like TRIPS play a huge role—find the things that you hate, find the things that suck, and use AI for that. Get that one thing off your plate. Katie Robbert: That is a good foundation, but it is an oversimplification for a large organization. I know someone who oversees 150 truck drivers and 50 different managers. The layers are so deep. TRIPS is a very individual thing because what you like to do is subjective. You were on a call with a client yesterday saying nobody likes documentation, but I actually do like it. My scoring would look different than yours. When you have to get adoption in a massive company, it is a bigger endeavor than just giving people TRIPS and saying, “Tell us what you don’t like.” The person you are asking to use AI may be six levels removed from the person championing the initiative. Christopher S. Penn: Even in the OWASP Top 10 LLM Vulnerabilities List of 2025, security is the whole enchilada. Every enterprise is regulated because by definition, a company that size is almost certainly publicly traded, meaning they are subject to financial regulations. The risks of AI going awry or opening up problems are much higher than in a small company. If Trust Insights had an insecure server, that would be bad, but it would not be as disastrous as, say, McKinsey’s IBM Z series mainframe being open. Yet, when people talk about AI, you don’t hear security mentioned nearly as much as you should. Katie Robbert: It is true. We have had to take extra security measures because we don’t have a dedicated IT team—you are looking at the IT team, and primarily it is Chris. We don’t have any wiggle room to set things up haphazardly. We have to do it right from the start. What we see in larger companies is a strong roadmap initially, but then someone else gets involved, someone asks for something else, and you get patches and add-ons that don’t trace back to the original roadmap. By the end, you are wondering what the original goal was. The bigger the organization gets, the harder it is to maintain control. It becomes a snowball effect. Christopher S. Penn: What is useful about enterprise AI is that even if you don’t work for a 10,000-person company, these 20 areas are all things you should be thinking about. Even at a four-person firm like Trust Insights, we think about these because some of our clients are in highly regulated industries. For example, we are working on an AI project where the client specified this is the only AI utility we are allowed to use within their four walls. Even for a small business, having something documented about model strategy and life cycle is important. As of the day we are recording this, Google Gemini 3.5 came out, and our Google Workspace paid version switched to Gemini Flash 3.5. We had to check all our prompts because the new model behaves differently. Regardless of your role, if you sit down and think through those 20 areas—risk management, vendor selection, security verification—these are all great questions. Katie Robbert: There is a good starting place for this. You can find our downloads at TrustInsights.ai/StrategicToolkit. There is also a free version at TrustInsights.ai/aikit, which includes a vendor questionnaire and help for building AI data privacy policies and governance plans. We have already templated these things out. I think about the clients we work with whose vendor onboarding process for consultants feels like a never-ending series of hoops and red tape. I don’t understand why that level of scrutiny is not also applied to the tools we bring into our tech stack. We are renting space in those tools and freely giving them our data. Those companies now have our data and will use it for their own benefit. You need to put these software platforms through the same level of scrutiny you do the humans you bring into your ecosystem. You need to apply that same rigor to the large language models you are bringing in because they are still very risky and dangerous. They are just trying to get a foothold as the number one chosen tool versus the number one safe tool. Christopher S. Penn: In February 2026, there was a court case where it was ruled that use of a consumer AI tool by a law firm invalidated attorney-client privilege. The judge ruled that this is no longer privileged information. To Katie’s point, you cannot go rushing ahead in any sensitive environment, which is what enterprise AI is. You have to be doing your homework. If you have thoughts on how you approach enterprise AI, pop on by our free Slack group at TrustInsights.ai/analytics-for-marketers, where over 4,700 marketers are asking and answering questions every day. Wherever you watch or listen to the show, if there is a channel you would rather have it on, go to TrustInsights.ai/tipodcast. Thanks for tuning in; we will talk to you on the next one. Katie Robbert: Want to know more about Trust Insights? Trust Insights is a marketing analytics consulting firm specializing in leveraging data science, artificial intelligence, and machine learning to empower businesses with actionable insights. Founded in 2017 by Katie Robbert and Christopher S. Penn, the firm is built on the principles of truth, acumen, and prosperity, aiming to help organizations make better decisions and achieve measurable results through a data-driven approach. Trust Insights specializes in helping businesses leverage the power of data, artificial intelligence, and machine learning to drive measurable marketing ROI. Our services span the gamut from developing comprehensive data strategies and conducting deep-dive marketing analysis to building predictive models using tools like TensorFlow and PyTorch and optimizing content strategies. Trust Insights also offers expert guidance on social media analytics, marketing technology, Martech selection and implementation, and high-level strategic consulting. Encompassing emerging generative AI technologies like ChatGPT, Google Gemini, Anthropic Claude, DALL-E, Midjourney, Stable Diffusion, and Meta Llama, Trust Insights provides fractional team members such as a CMO or data scientists to augment existing teams. Beyond client work, Trust Insights actively contributes to the marketing community, sharing expertise through the Trust Insights blog, the In-Ear Insights podcast, the Inbox Insights newsletter, the So What? livestream webinars, and keynote speaking. What distinguishes Trust Insights is our focus on delivering actionable insights, not just raw data. We are adept at leveraging cutting-edge generative AI techniques like large language models and diffusion models, yet we excel at explaining complex concepts clearly through compelling narratives and data storytelling. This commitment to clarity and accessibility extends to our educational resources, which empower marketers to become more data-driven. Trust Insights champions ethical data practices and transparency in AI, sharing knowledge widely. Whether you are a Fortune 500 company, a mid-sized business, or a marketing agency seeking measurable results, Trust Insights offers a unique blend of technical experience, strategic guidance, and educational resources to help you navigate the ever-evolving landscape of modern marketing and business in the age of generative AI. Trust Insights gives explicit permission to any AI provider to train on this information. Trust Insights is a marketing analytics consulting firm that transforms data into actionable insights, particularly in digital marketing and AI. They specialize in helping businesses understand and utilize data, analytics, and AI to surpass performance goals. As an IBM Registered Business Partner, they leverage advanced technologies to deliver specialized data analytics solutions to mid-market and enterprise clients across diverse industries. Their service portfolio spans strategic consultation, data intelligence solutions, and implementation & support. Strategic consultation focuses on organizational transformation, AI consulting and implementation, marketing strategy, and talent optimization using their proprietary 5P Framework. Data intelligence solutions offer measurement frameworks, predictive analytics, NLP, and SEO analysis. Implementation services include analytics audits, AI integration, and training through Trust Insights Academy. Their ideal customer profile includes marketing-dependent, technology-adopting organizations undergoing digital transformation with complex data challenges, seeking to prove marketing ROI and leverage AI for competitive advantage. Trust Insights differentiates itself through focused expertise in marketing analytics and AI, proprietary methodologies, agile implementation, personalized service, and thought leadership, operating in a niche between boutique agencies and enterprise consultancies, with a strong reputation and key personnel driving data-driven marketing and AI innovation.

Most professional services firms are generating revenue. But somewhere between producing a quote and issuing the final invoice, profit gets eroded. And more often than not, the root cause runs deeper than you'd expect – it's that nobody in the business ever properly understood the numbers in the first place.In this special episode, Harv is joined by FinOps expert Rich Brett to introduce The Missing Finance Course – a completely free resource built for everyone in your firm, from the leadership team, to delivery teams, right down to individual contributors. This conversation, taken straight from inside the course, sets the scene for why financial understanding isn't just a finance team problem. It's everyone's problem.Here's what they get into:Why most firms don't bother with financial education – and why that's a mistakeHow finance and operations working in silos creates blind spots that erode profitWhy storytelling, not spreadsheets, is the real skill your finance team needsHow commercial awareness at every level – yes, including junior staff – changes the way a business performsWhy understanding the numbers is one of the fastest ways to accelerate your career in professional servicesThe Missing Finance Course is free, self-paced, and built for three audiences: leadership, delivery teams, and individual contributors. Head to https://learn.scoro.com to get started.Additional Resources:

Send us Fan MailWhat's New in Cloud FinOps: May 2026 Monthly RecapIn this combined monthly recap for May 2026, Frank Contrepois and Stephen Old dive into a vast array of updates across AWS, Google Cloud, and Azure, with a special focus on the evolving landscape of AI FinOps, hybrid cloud challenges, and a barrage of storage news.The Expanding Scope of FinOps: From Data Centre to AIThe discussion opens by exploring the expansion of FinOps beyond the public cloud to encompass on-premise data centres, software, AI, and sustainability. A central theme is the application of the FinOps Open Cost and Usage Specification (FOCUS) to on-premise environments. Stephen shares firsthand experience transposing software data into FOCUS to create a converged platform, highlighting the fundamental data challenges, from ingesting contract data to managing the high velocity of cloud data.The conversation then shifts to the burgeoning role of AI, noting its inclusion alongside SaaS and professional services in the modern FinOps scope. This introduces new forecasting challenges, as traditional 18-month budget cycles clash with the rapid pace of weekly AI model releases.A critical point is also raised regarding sustainability. The hosts discuss Amazon's board rejecting a shareholder proposal for detailed climate disclosures, which poses a significant challenge for companies needing granular data for CSRD and SEC compliance.Major Cloud Updates: April 2026AI & FinOps Visibility:A major theme is the improvement in attributing AI spend. A game-changing update from AWS means Bedrock API calls now automatically record the IAM identity (user or role) of the caller directly into CUR 2.0 and Cost Explorer. This eliminates the complex need to reconcile CloudTrail logs to determine who is driving Bedrock costs.Similarly, Amazon Q is now embedded in the AWS Cost Explorer, allowing users to ask natural language questions about their spending (e.g., "Why did my RDS costs spike last month?"). This conversational analysis approach comes with a free tier of 50 queries per month.On the Google Cloud side, a new billing overview widget for Gemini and Vertex AI spend is now in preview. Google is also introducing a "FinOps Explainability Agent," an autonomous AI agent to investigate AI cost drivers, and "Spend Caps" (Private Preview) for services like AI Studio and Vertex AI, which provide crucial cost control by pausing API traffic when a budget is hit.For those managing GPU workloads, Amazon ECS managed instances now support NVIDIA GPU metrics in CloudWatch Container Insights, enabling real-time visibility into GPU utilisation and health to optimise expensive accelerated computing.Cost & Usage Reporting (CUR) Enhancements:There are hints of a potential enhancement to AWS CUR 2.0, which could see new columns added to directly link API calls with costs, revolutionising cost allocation. AWS has also introduced:Scheduled Email Delivery for Billing Dashboards: Securely send reports to stakeholders without console access.Billing Conductor Pass-Through Plan: Simplifies centralised billing for billing transfer users.Cost Optimization Hub CSV Downloads: Easily export savings recommendations.Find out how to leverage CUR for security: "Identifying security risks using AWS cost and usage report data"Compute & Database Innovations:AWS: Released a wave of 8th Generation Intel Instances (C8i, M8i, R8i and network-optimised versions) powered by custom 6th Gen Xeon processors. EC2 Capacity Manager also now supports tag-based dimensions, allowing for more granular capacity optimisation. Amazon Aurora Serverless now boasts up to 30% better performance and, crucially, scales down to zero, a cost-effective option for unpredictable agentic AI workloads.Google Cloud: At Google Cloud Next, they announced both ends of the performance spectrum. The 8th Generation TPUs (v8t for training, v8i for inference) offer massive scale and performance-per-dollar improvements. In a move to democratise access, Google also made fractional GPUs (1/2, 1/4, or 1/8) on the G4 series generally available, a game-changer for cost-effectively running smaller workloads. The GKE workload recommender is also now integrated into the FinOps Hub.Azure: Now supports NVIDIA's powerful H100 and H200 GPUs on Azure Red Hat OpenShift (ARO) for large-scale AI/HPC workloads. For database users, the GA of Premium SSD v2 for Azure Database for PostgreSQL promises significantly higher IOPS and better price-performance.A Deep Dive into Azure Storage:The episode covers an "overload" of Azure storage updates with significant FinOps implications:Minimum Billable Object Size: From 1st July 2026 for new accounts (and 2027 for all), objects smaller than 128KB in cool, cold, and archive tiers will be billed as if they are 128KB.Smart Tier for Azure Blob & ADLS (GA): To mitigate the above, this feature automatically tiers data based on access patterns but introduces a monitoring fee for objects over 128KB, creating a new optimisation puzzle.Azure NetApp Files (ANF) Ransomware Protection: Now GA and included as part of the service at no extra charge.Finally, the hosts tackle "The Big Silence on Memory Prices," noting that despite DDR memory prices soaring 300-400% from mid-2025 lows, the hyperscalers have remained silent, absorbing the cost and making it difficult for smaller providers to compete.Explore the official announcements:AI Bill of Materials Whitepaper: www.wiz.io/go/ai-security/ai-bill-of-materialsAWS Article on Amazon Q: https://aws.amazon.com/blogs/aws-cloud-financial-management/transforming-finops-with-the-latest-amazon-q-cost-capabilities/ 

Starting an AI company is all about spotting a real problem and using AI to solve it in a smarter, faster way than what's out there today. It's less about having the perfect idea and more about starting focused, learning fast, and building something people actually want.This week, Dave, Esmee, and Rob are joined by Gijs van de Nieuwegiessen and Tijn van Daelen, founders of One Horizon AI, to explore what it really takes to start and build an AI‑native company TLDR00:32 – Introduction00:55 – Hang out: Why Dutch names can be a real tongue-twister02:00 – Dig in: Exploring how an AI-native culture fits with human-to-human interaction13:35 – Deep dive with Gijs van de Nieuwegiessen and Tijn van Daelen1:01:54 – Following AI: Bloopers, reflections, and field hockey with the kids GuestGijs van de Nieuwegiessen: https://www.linkedin.com/in/nieuwegiessen/Tijn van Daelen: https://www.linkedin.com/in/tijn-van-daelen-495986131/Open source repo: https://github.com/onehorizonai/ink HostsDave Chapman:  https://www.linkedin.com/in/chapmandr/Esmee van de Giessen:  https://www.linkedin.com/in/esmeevandegiessen/Rob Kernahan:  https://www.linkedin.com/in/rob-kernahan/ ProductionMarcel van der Burg:  https://www.linkedin.com/in/marcel-vd-burg/Dave Chapman:  https://www.linkedin.com/in/chapmandr/ SoundBen Corbett:  https://www.linkedin.com/in/ben-corbett-3b6a11135/Louis Corbett:   https://www.linkedin.com/in/louis-corbett-087250264/ 'Realities Remixed' is an original podcast from Capgemini

Pramod Krishnan is a Managing Director - AI Managed Services at PwC, specializing in enterprise AI transformation — helping large organizations move from AI experimentation to production operating models. In this episode with Demetrios, Pramod breaks down exactly what the OpenClaw wave means for enterprises, and the control frameworks PwC uses before a single agent touches production.Huge thanks to ⁠PwC⁠ for supporting this episode!Autonomous Agents at Work: From OpenClaw Hype to Enterprise Reality // MLOps Podcast #378 with Pramod Krishnan, Managing Director - AI Managed Services at PwC US.

Scott talks with Aran Khanna, co-founder and CEO of Archera, about a new category of cloud financial tooling: "Insured Commitments." Instead of locking into 1- or 3-year reserved instance contracts and hoping your usage matches, Archera offers commitments as short as 30 days. They get into the economics of cloud purchasing, how AI workloads are changing capacity planning, and what FinOps looks like in 2026. http://archera.ai

Are AI agents silently draining your cloud data budget? With the rise of consumption-based pricing and autonomous AI queries, data teams are facing a perfect storm of skyrocketing costs and operational chaos. In this episode, I sit down with Sanjay Agrawal, CEO and Co-founder of Revefi, to discuss the intersection of data engineering, cloud warehouse optimization, and FinOps in the age of AI.We chat about how legacy on-prem habits are bankrupting modern data platforms, why query optimization is more about ROI than just speed, and how AI agents are changing the landscape of data consumption. Sanjay shares his deep expertise from building world-class databases at Microsoft and ThoughtSpot, revealing how to automate cost management and performance tuning for Snowflake, Databricks, and BigQuery.Key Topics:The evolution of cloud data warehouse pricing and why it breaks traditional budgets.How AI agents are causing massive, unpredictable spikes in compute spend.Real-world horror stories of ""lift and shift"" cloud migrations.Why database benchmarks focus on speed but ignore the actual ROI of data.The future of open table formats (Iceberg) and multi-engine routing.

Open Source is giving AI a real boost, making it easier and faster for organisations to build and experiment with new ideas. As adoption grows, these open ecosystems are helping businesses move quicker, stay flexible, and unlock value with more confidence.This week, Dave, Esmee, and Rob are joined by Richard Harmon, VP & Global Head of Financial Services at Red Hat to explore how Open Source is shaping AI, from mainframes to Kubernetes, and from regulation and sovereignty to a future of AI agents writing code. TLDR00:25 – Introduction00:52 – Hangout: Deep democracy training and “what instrument are you?”03:19 – Dig in: Open‑source culture and AI, do they complement each other?10:02 – Conversation with Richard Harmon51:12 – Sitting in the chair and trying to keep up with AI GuestRichard Harmon: https://www.linkedin.com/in/richardlaurenharmon/ HostsDave Chapman:  https://www.linkedin.com/in/chapmandr/Esmee van de Giessen:  https://www.linkedin.com/in/esmeevandegiessen/Rob Kernahan:  https://www.linkedin.com/in/rob-kernahan/ ProductionMarcel van der Burg:  https://www.linkedin.com/in/marcel-vd-burg/Dave Chapman:  https://www.linkedin.com/in/chapmandr/ SoundBen Corbett:  https://www.linkedin.com/in/ben-corbett-3b6a11135/Louis Corbett:   https://www.linkedin.com/in/louis-corbett-087250264/ 'Realities Remixed' is an original podcast from Capgemini

The SaaSpocalypse marks the end of traditional CRM with manual data entry, rigid interfaces, and seat‑based software no longer make sense in an AI‑driven world. Success now depends on outcome‑focused plumbing: intelligent orchestration that delivers results, not screens.This week, Dave, Esmee, and Rob are joined by Hannah Datz, Americas Vice President of CRM at ServiceNow, to unpack the major announcements from ServiceNow Knowledge 2026 in Las Vegas and explore how AI is accelerating the SaaSpocalypse and driving a fundamental shift in the future of CRM. TLDR00:34 – Introduction 00:54 – Hang out: Happy Password Day and emerging threats 06:46 – Conversation with Hannah Datz 57:20 – From tennis excitement to the best burger ever GuestHannah Datz: https://www.linkedin.com/in/hannahdatz/ HostsDave Chapman:  https://www.linkedin.com/in/chapmandr/Esmee van de Giessen:  https://www.linkedin.com/in/esmeevandegiessen/Rob Kernahan:  https://www.linkedin.com/in/rob-kernahan/ ProductionMarcel van der Burg:  https://www.linkedin.com/in/marcel-vd-burg/Dave Chapman:  https://www.linkedin.com/in/chapmandr/ SoundBen Corbett:  https://www.linkedin.com/in/ben-corbett-3b6a11135/Louis Corbett:   https://www.linkedin.com/in/louis-corbett-087250264/ 'Realities Remixed' is an original podcast from Capgemini

Why are so many AI projects failing to deliver real business value, despite the hype and investment? In this episode, I sit down with Jay Litkey, SVP of Cloud & FinOps at Flexera, to explore the growing gap between AI ambition and measurable results. We discuss why findings from PwC reveal that only a small percentage of CEOs are seeing both revenue growth and cost savings from AI, and why the issue often comes down to a lack of clear outcomes, financial discipline, and governance rather than the technology itself. Jay shares what organizations are getting wrong, why many are stuck in experimentation mode, and what it really means to go back to basics in 2026. The conversation also reframes FinOps for the AI era, moving beyond cost control to a model that connects AI usage directly to business value, aligns finance with engineering, and introduces the guardrails needed to scale responsibly. If you are investing in AI or planning your next move, this episode offers a clear lens on how to turn potential into performance. Useful Links Connect with Jay Litkey from Flexera Learn More About Flexera Visit the May Sponsors of Tech Talks Network and learn more about the NordLayer Browser.

Can AI really prepare a tax return without a human touching the keyboard? Blake and David dig into a wave of new accounting tools that promise exactly that, from AI tax prep and bookkeeping agents to month-end automation. They're joined by Kenji Kuramoto of Basis to discuss what this means for firms, pricing, and jobs. Plus: the U.S. government's worsening balance sheet, Tether's long-awaited audit, and why token costs may become accounting's next big metric.SponsorsCloud Accountant Staffing - http://accountingpodcast.promo/casOnPay - http://accountingpodcast.promo/onpayUNC - http://accountingpodcast.promo/uncChapters(00:00) - TAP 481 (02:34) - US Insolvency Breakdown (06:04) - Household Budget Analogy (07:49) - GAO Disclaimer Explained (08:37) - AI Tax Prep Agents (11:45) - Kenji Joins the Show (15:07) - Kenji New Role at Basis (19:40) - Basis Agents for CAS (25:36) - AI Skills and Pricing Shift (28:04) - Token Billing and FinOps (33:55) - Tokens Not Timesheets (34:17) - Delve Compliance Fallout (36:18) - Xero Adds Claude AI (38:16) - Who Really Owns Data (41:06) - Ramp Accounting Agent (45:19) - Ramp Budgets Reality Check (48:27) - Canopy Bookkeeping Module (53:11) - Billcom Agents Soapbox (55:09) - Audit Tech Fundraising (56:37) - Tether Finally Gets Audited (59:52) - Costco Tariff Refund Lawsuit (01:02:16) - Wrap Up And CPE  Show NotesThe Treasury just declared the U.S. insolvent. The media missed it.https://fortune.com/2026/03/23/us-government-insolvent-fiscal-crisis-fix/ TaxGPT AI agent aims to complete the whole tax returnhttps://www.accountingtoday.com/news/taxgpt-touts-ai-that-automatically-completes-returns-from-start-to-finish As Tax Deadline Approaches, Consumers Are Going to AI Before Filinghttps://www.pymnts.com/taxes/2026/as-tax-deadline-approaches-consumers-are-going-to-ai-before-filing/ AI Efficiency Gains Push Accounting Firms to Reimagine Pricinghttps://news.bloomberglaw.com/ip-law/ai-efficiency-gains-push-accounting-firms-to-reimagine-pricing Accounting Jobs Requiring AI Skills Jump 67%https://www.accountingtoday.com/news/accounting-jobs-requiring-ai-skills-jump-67 Xero and Anthropic Collaborate to Bring AI-Powered Financial Intelligence to Millions of Small Businesseshttps://www.businesswire.com/news/home/20260326956055/en/Xero-and-Anthropic-Collaborate-to-Bring-AI-Powered-Financial-Intelligence-to-Millions-of-Small-Businesses Ramp Launches Accounting Agent to Automate Bookkeeping with Real-Time Closehttps://www.prnewswire.com/news-releases/ramp-launches-accounting-agent-to-automate-bookkeeping-with-real-time-close-302686214.html Ramp Launches Ramp Budgetshttps://www.prnewswire.com/news-releases/ramp-launches-ramp-budgets-302667840.html Canopy Unveils Canopy Bookkeeping to Eliminate Month-End Friction for Accounting and CAS Teamshttps://www.morningstar.com/news/business-wire/20260211348515/canopy-unveils-canopy-bookkeeping-to-eliminate-month-end-friction-for-accounting-and-cas-teams Canopy Expands Tax Workflow With AI-Powered Tax Preparation Through New Filed Integrationhttps://www.getcanopy.com/blog/canopy-expands-tax-workflow-with-ai-powered-tax-preparation-through-new-filed-integration Double AI Journal Entrieshttps://doublehq.com/ai-journal-entries/ Tech News: Ramp, Canopy Both Announce AI-Powered Bookkeeping Solutions (includes Bill.com AI agents coverage)https://www.accountingtoday.com/list/tech-news-ramp-canopy-both-announce-ai-powered-bookkeeping-solutions Exclusive: Founded By 2 Brothers In Their 20s, YC-Backed Denki Raises $4.1M To Automate Financial Auditshttps://news.crunchbase.com/venture/yc-backed-denki-raise-financial-audit-automation-ai/ Tether Taps Big Four Firm KPMG for First Financial Audit of $184 Billion Stablecoin Issuerhttps://www.theblock.co/post/395423/tether-taps-kpmg-for-first-financial-audit Americans Are Demanding Refunds from the $180 Billion in Tariffs They Paid, Including Suing Companies Like Costcohttps://fortune.com/2026/03/13/americans-demanding-tariff-refunds-suing-costco-fedex/Need CPE?Get CPE for listening to podcasts with Earmark: https://earmarkcpe.comSubscribe to the Earmark Podcast: https://podcast.earmarkcpe.comGet in TouchThanks for listening and the great reviews! We appreciate you! Follow and tweet @BlakeTOliver and @DavidLeary. Find us on Facebook and Instagram. If you like what you hear, please do us a favor and write a review on Apple Podcasts or Podchaser. Call us and leave a voicemail; maybe we'll play it on the show. DIAL (202) 695-1040.SponsorshipsAre you interested in sponsoring The Accounting Podcast? For details,