Podcasts about enterprises

What does it take to turn a high school side hustle into a thriving retail brand, wholesale business, and nationally recognized name? Ashley Alderson sits down with John Mark Sharpe (John Mark Enterprises) as he shares the incredible journey from selling wreaths out of a guest bedroom to building a multi-location business, launching a successful wholesale ribbon line, and leading a team of nearly 40 employees. Along the way, he learned one of the most important lessons in business: sustainable growth happens when you're willing to start small, stay consistent, and keep reinvesting in what works. You'll learn: How a simple wreath business sparked an entrepreneurial journey Why he believes most business owners overthink growth How a mission trip to India led to a successful ribbon line The mindset change that helped him rethink debt and growth Join The Boutique Hub Get Swym John Mark & John Mark Enterprises: Instagram:@JohnMarkEnterprises Website: JohnMark.com  The Round Top Collection: shop.thertc.com                       ____________________________ Ashley Alderson: Instagram     The Boutique Hub: Website | Facebook | Instagram | Pinterest | TikTok | YouTube

"The real challenge is converting enterprise data into real-time, accurate, meaningful context" In this episode of Mint Techcetra, Nelson John speaks with Sriram Raghavan, General Manager, IBM Software, India, and Software Innovation Lab, about how agentic AI is driving the next major evolution in enterprise data management. From data silos and real-time context to hybrid architectures and governance, the discussion examines what organisations need to do to build AI-ready data foundations. The conversation also explores the expanding definition of digital sovereignty and why openness, flexibility, and control are becoming key considerations as enterprises modernise their data and AI environments. Learn more about your ad choices. Visit megaphone.fm/adchoices

In part two of my two-part field trip to Livermore, California, I sit down with Inertia Enterprises' third co-founder — Annie Kritcher, the chief scientist at Inertia and a longtime physicist at Lawrence Livermore National Laboratory.Annie was the lead designer behind the December 2022 National Ignition Facility (NIF) shot that achieved ignition — a self-heating fusion “burning plasma” that produced more fusion energy out than was delivered to the target. In this episode, Annie walks us through what it took to get there (spoiler: not one magical breakthrough), what “the ignition cliff” actually means, and why Inertia is betting that manufacturing and economics — not brand-new physics — is the fastest path to commercial fusion.We talk about:Annie's path from nuclear engineering + plasma physics to becoming NIF's lead designer on ignition platformsWhy the historic ignition shot was the result of years of iteration (and a few duds along the way)The “pancake” shot (and the lab's surprisingly extensive breakfast-food vocabulary for failed plasmas)What it felt like to get the 3:00am text — “I think we got ignition” — and why relief came before celebrationWhy many in the field had nearly given up on laser fusion ignition — and how close the NIF campaign came to being cutWhy other fusion companies pursued different approaches: history, uncertainty, and the (very real) cost problem for lasers + targetsThe core commercialization challenge: scaling to high-repetition-rate shots (think “engine cycles”) and producing targets cheaply enough to fire millions per dayLinks:Inertia Enterprises: https://inertia.com/Everybody in the Pool: https://www.everybodyinthepool.com/Subscribe to the Everybody in the Pool newsletter: https://www.mollywood.co/Become a member for the ad-free version of the show: https://everybodyinthepool.supercast.com/Join our Discord: https://discord.gg/2EsDhwQC2z Hosted on Acast. See acast.com/privacy for more information.

The conversation around artificial intelligence often creates the impression that software development has already been transformed beyond recognition. Social media feeds are filled with stories about AI agents replacing teams, generating applications automatically, and eliminating the need for traditional development processes. The Enterprise AI Reality is much more nuanced. While AI has become a valuable tool inside software organizations, large enterprises are approaching adoption far differently than many public conversations suggest. The gap between experimentation and production remains significant, especially when millions of dollars, regulatory requirements, and customer trust are involved. About Samuel Otero Samuel Otero is a Software Solutions Specialist with Deloitte US and a technology consultant with nearly 14 years of experience spanning enterprise software development, government projects, commercial consulting, and large-scale digital transformation initiatives. His career began with an early Microsoft internship that shaped his approach to continuous learning and technical humility. Since then, he has worked across media, public-sector, and enterprise environments, helping organizations deliver complex software solutions while mentoring the next generation of developers. Based in Puerto Rico, Samuel is also an advocate for developer growth, career development, and practical AI adoption in modern software engineering. Links LinkedIn Enterprise AI Reality Is Different from Social Media One of the strongest observations Samuel shared was the contrast between what people see online and what happens inside large organizations. Social media often highlights extreme success stories. Teams appear to build entire products using AI agents. Individual developers showcase impressive workflows that dramatically accelerate delivery. Those examples are real. However, enterprise software operates under different constraints. Systems support financial transactions, critical business processes, compliance requirements, and large customer bases. Mistakes carry significant consequences. As a result, organizations are adopting AI incrementally rather than replacing existing development practices overnight. Enterprise AI Reality Requires Trust Before Automation Every technology faces a trust curve. Before organizations automate critical workflows, they need evidence that systems perform reliably under real-world conditions. Samuel described how enterprises often use AI first in lower-risk scenarios before allowing it to influence more critical components of a platform. Features with limited business risk become testing grounds for new approaches. This pattern mirrors previous technological shifts. Cloud adoption happened gradually. DevOps adoption happened gradually. AI adoption is following a similar trajectory. The technology may be powerful, but trust must be earned through consistent results. Enterprises don't adopt technology because it's impressive. They adopt it because it's reliable. Enterprise AI Reality Still Depends on Human Expertise One misconception surrounding AI is that generated code eliminates the need for technical understanding. In practice, the opposite may be true. The more organizations rely on AI-generated outputs, the more important validation becomes. Developers must understand architecture, business requirements, security concerns, and implementation details well enough to verify what AI produces. Samuel emphasized a simple but powerful habit: asking AI to explain exactly what it did and why it made certain decisions.   That approach transforms AI from an answer machine into a learning tool. Developers who understand generated solutions become more effective. Developers who blindly accept generated solutions create risk. Never merge AI-generated code until you can explain its behavior to another developer. Enterprise AI Reality Is Creating New Skill Gaps The rise of AI is changing how developers gain experience. Historically, growth came from solving difficult problems manually. Developers researched documentation, struggled through debugging sessions, and built mental models through repetition. AI reduces much of that friction. While this increases productivity, it also creates new challenges. Developers may complete tasks successfully without fully understanding how those tasks were accomplished. Over time, this can create a dangerous gap between perceived capability and actual expertise. Organizations must address this by emphasizing understanding rather than output alone. The future belongs to developers who combine AI acceleration with deep technical comprehension. Enterprise AI Reality May Increase Software Complexity An interesting prediction from the discussion involved software quality. As AI accelerates development, more software will be produced. More features will be released. More experiments will reach production environments. That acceleration creates opportunity. It also creates risk. Samuel suggested that many organizations are still learning where AI performs exceptionally well and where it struggles under enterprise-scale conditions. During that learning period, users may experience more bugs, patches, and corrective updates as teams discover limitations. This isn't evidence that AI has failed. It's evidence that every transformative technology goes through a maturation phase before reaching stability. Faster development cycles can produce bugs faster if organizations don't maintain engineering discipline. Enterprise AI Reality Still Comes Back to Problem Solving Perhaps the most important lesson from the entire conversation is that technology itself is rarely the source of professional value. Languages change. Frameworks change. Platforms change. AI models will change. The underlying business need remains consistent: solving problems. Samuel's closing advice focused on developing problem-solving skills rather than attaching identity to a specific technology stack. That mindset provides resilience regardless of how quickly tools evolve. Developers who can understand problems, communicate solutions, and create business value will remain relevant long after today's AI tools are replaced by tomorrow's innovations. The most durable technical skill isn't coding. It's problem-solving. Conclusion The Enterprise AI Reality is neither the dystopian future predicted by skeptics nor the fully automated paradise promised by enthusiasts. Instead, it's a period of careful experimentation, measured adoption, and ongoing learning. Organizations are discovering where AI delivers value, where human expertise remains essential, and how both can work together to build better software. The developers who succeed during this transition won't be the ones who resist AI or blindly trust it. They'll be the ones who learn how to use it responsibly while continuing to strengthen the problem-solving skills that define great engineers. Stay Connected: Join the Developreneur Community

The Wall Street Journal reported that a $13 billion AI startup is betting on cheaper alternatives to OpenAI and Anthropic. Enterprises are shifting from pilots to production and seeking to control inference costs across support, copilots, and content workflows. Open source options such as Meta's Llama and models from Mistral enable targeted deployments with retrieval and fine-tuning to improve cost predictability. Procurement teams weigh SLAs, latency, security certifications, data retention, indemnity, and regional hosting against premium providers. Vendors distribute through AWS, Microsoft Azure, and Google Cloud marketplaces, while access to Nvidia accelerators influences performance and cost. Pricing includes per token and per seat plans, with some platforms routing simple tasks to lower cost models and reserving premium models for complex work. Founders are advised to build evaluation harnesses, track cost per outcome, and negotiate for predictable terms.Learn more on this news by visiting us at: https://greyjournal.net/news/ Hosted on Acast. See acast.com/privacy for more information.

Expereo: Enterprises Are Racing Into AI, But the Network Still Has to Carry the Load, Podcast, “AI is no longer a debate. Enterprises are already using it. The question now is whether the network is ready to support what comes next,” says Marek Wasilewski of Expereo @Doug Green “AI is no longer a debate. Enterprises are already using it. The question now is whether the network is ready to support what comes next,” says Marek Wasilewski of Expereo. In this Cisco Live 2026 podcast, Doug Green speaks with Marek Wasilewski of Expereo about the company's 2026 Enterprise Horizons report and what it reveals about enterprise AI adoption, network readiness and the growing pressure on global connectivity. This is one of several Cisco Live podcasts worth revisiting after the initial wave of show coverage. The conversation provides interesting insights into how AI is changing the network conversation for enterprises, service providers and channel partners. According to Expereo's research, 92% of enterprises are using AI in some form, while 30% are already using it extensively. At the same time, 70% are investing in AI without carefully measuring ROI. That combination creates both opportunity and risk: enterprises are moving quickly, but many are still building on networks that were not designed for the scale, performance and resilience demands of AI-driven operations. Expereo, a global Network-as-a-Service provider, helps enterprises simplify and manage connectivity across complex international environments. In the podcast, Wasilewski explains why AI success depends not only on models, applications and cloud platforms, but also on the underlying network that connects users, data, workloads and business locations. For channel partners, MSPs and enterprise technology leaders, the message is clear: AI is making the network strategic again. Connectivity is no longer just plumbing. It is becoming a core part of digital transformation, customer experience, automation and business continuity. The conversation also explores how enterprises can think more clearly about AI investment, how global connectivity strategies are changing, and why network visibility, flexibility and reliability will matter even more as AI moves from pilot projects into production environments. Learn more: expereo.com

Network Is Hot Again: Stackpane's Sarbjeet Johal on Cisco Live, AI Infrastructure and Systems Economics, Podcast, Johal brings a unique mix of technical, business, and economics experience to the discussion @Doug Green, Publisher, Technology Reseller News “The network is hot again because a lot more data is traversing on it, and a lot more data will traverse on it,” says Sarbjeet Johal of Stackpane. In this Technology Reseller News podcast, Doug Green speaks with Sarbjeet Johal, Founder and CEO of Stackpane, technology analyst, cloud strategist and go-to-market specialist, about why the network has moved back to the center of the enterprise technology conversation. Johal brings an unique mix of technical, business and economics experience to the discussion. A veteran of VMware, Oracle and Dell EMC, Johal has spent decades building and deploying enterprise systems, advising technology providers, and helping buyers understand cloud strategy, infrastructure modernization and digital transformation. At Cisco Live, Johal says the biggest theme was simplification. Cisco, he argues, is working to reduce infrastructure complexity for customers operating across public cloud, on-premises systems, AI workloads and increasingly distributed environments. That includes a renewed focus on infrastructure as code, platform control, and AI-assisted tools such as Cisco IQ, which Johal says can help customers and partners troubleshoot, configure and operate Cisco environments more effectively. The conversation then turns to Johal's recent observation that “the network is hot again.” His point is that AI, real-time systems, digital services, autonomous agents, and API-driven interactions are all placing new demands on network performance. As more data moves across enterprise systems, latency, memory, compute, and connectivity become more strategically important. Johal notes that during AI inference, latency is especially critical, making the network, chips, CPUs, and memory all part of the same infrastructure story. Johal also frames the issue through systems economics. Enterprises are not simply buying more technology for the sake of modernization. They are being forced to ask whether cloud, AI, on-prem infrastructure, and automation actually pencil out in terms of total cost of ownership, return on investment, and operational value. For MSPs, channel partners, and technology providers, that creates an opportunity to help customers make better architecture decisions, not just consume more tools. The podcast closes with a look ahead to a future conversation on token economics, AI infrastructure costs, and where MSPs and channel partners can find real business opportunity as enterprise technology becomes more automated, more data-intensive, and more dependent on resilient network infrastructure. Editor's note: This podcast was recorded at Cisco Live in Las Vegas and is being posted later. With time, the conversation has become even more notable. Johal's central point — that the network is “hot again” — has only gained relevance as AI, automation, cloud infrastructure and real-time digital services continue to place new pressure on enterprise networks. Learn more: Stackpane at stackpane.com

The RNIB trustees recently met in Edinburgh to talk about the next steps for the charity.Andy Barry, Chair of RNIB enterprise, told Amelia about some of the new ways RNIB is funding its vital work and some emerging opportunities for the organisation.Image shows the RNIB Connect Radio logo. On a white and black background ‘RNIB' written in bold black capital letters and underline with a bold pink line. Underneath the line: ‘Connect Radio' is written in black in a smaller font. 

Enterprises rushing agentic AI into production are running it through approval gates, batch windows, and audit systems built for human speed — and the gap is where most operational risk lives. In this episode, Chris Caldwell, President and CEO at Concentrix Corporation, examines how machine-scale transactions break processes designed for human pace and why bounded digital delegates outperform unrestricted digital twins in the enterprise. The discussion covers compliance bots that check other bots, the cost reality of poorly tuned agentic agents, and what leaders need to stop doing if they want a defensible AI roadmap. Learn how to evaluate AI vendors by assessing leadership expertise, and why funding benchmarks can signal product maturity and stability, download our free PDF report, "5 Ways to Select the Right AI Vendor," at emerj.com/aiv2.

Most enterprises believe they have a data problem. In reality, it is an architecture problem in disguise, and the rise of agentic AI is making that distinction impossible to ignore. That is the central argument Karthik Ranganathan, CEO of Yugabyte, makes in this episode of Don't Panic! It's Just Data, hosted by Scott Taylor of MetaMeta Consulting.The conversation traces 30 years of infrastructure evolution in 30 minutes. From Oracle's dominance as the monolithic backbone of enterprise applications, to the NoSQL revolution of the mid-2000s, and the cloud-native era of the 2010s, it builds toward the rise of agentic AI. In this new phase, systems do not just store and retrieve data; they act on it autonomously.“The challenges of current architectures under pressure are no longer theoretical. Agentic systems expose every seam, every silo, every bottleneck you've been quietly managing around,” says Raghanathan.Why Current Architectures Crack Under Agentic PressureTaylor opens the episode by asking the question many enterprise data leaders are quietly asking: Are today's architectures actually fit for AI workloads? Raghanathan's answer is measured. Most are not, and the reasons are structural rather than superficial.The core issue is fragmentation. Decades of 'good enough' tooling decisions have produced estates where relational databases sit in silos next to document stores, vector indexes live apart from transactional systems, and data pipelines patch the gaps. For traditional applications, this messiness is manageable. For agentic AI, systems that must reason across context, execute multi-step decisions, and maintain coherent state across interactions, it's a fundamental blocker.Raghanathan identifies three compounding failure modes: siloed knowledge stores that prevent AI systems from drawing on the full breadth of enterprise information; disconnected memory systems that can't persist context reliably across agent runs; and non-deterministic outputs from large language models (LLMs) that make it difficult to design stable data models around AI-generated results. Together, these problems don't just slow down AI projects; they erode the trust enterprises need to deploy agentic systems at any meaningful scale.Knowledge vs. MemoryOne of the episode's sharpest conceptual moves comes when Raghanathan draws a clean line between knowledge and memory in AI systems, two concepts that get conflated constantly, and at high cost.Knowledge, in this framing, is the structured, long-term body of facts and context an AI system can draw on: product catalogues, customer histories, domain documentation, and enterprise policies. Memory, by contrast, is the short-term, session-aware state that lets an AI system track what just happened, what's been decided, and what step comes next in a workflow.Most current architectures treat these as interchangeable or ignore memory entirely, forcing every agent interaction to start cold. The result is factually capable AI but contextually amnesiac; it knows the company's product catalogue but forgets it already recommended three options to this customer ten minutes ago.This is the gap Meko, YugaByte's knowledge-memory engine, is designed to close. By building a unified layer that handles both the persistent knowledge graph and the operational memory of active agent sessions, Meko allows enterprises to run agentic workflows without patching together vector databases, caches, and relational stores by hand. It's an architectural bet that the knowledge-memory distinction is not a nuance but a first-class design requirement and that enterprises ignoring it will pay the integration tax repeatedly.Bridging AI Capability To Business ValueTaylor pushes Raghanathan on the perennial tension between AI capability and business value, a conversation that lands differently now that agentic systems are making decisions, not just recommendations. Raghanathan's view is that the critical role of context in AI workflows is still being underestimated by most enterprises.He cites YugaByte customers who have moved from proof-of-concept AI deployments to production-grade agentic systems by making one architectural shift, treating context as infrastructure, not as application logic. When context management is embedded in the data layer, versioned, auditable, and available across agent boundaries, the reliability bar for AI systems rises dramatically.For enterprises ready to act, Raghanathan's guidance is clear: start by auditing existing architectures for knowledge and memory silos before evaluating AI tooling, invest in unified data models that support both relational and non-relational workloads, and treat the context layer as a core engineering concern rather than an afterthought added to LLM integrations. If you would like to find out more, visit yugabyte.com or connect with Karthik Ranganathan on LinkedIn.TakeawaysEvolution of data infrastructure for agentic AI.Limitations of current architectures and silos.The role of knowledge and memory in AI systems.Strategies for enterprise data architecture in the AI era.Chapters00:00 Introduction to Data and AI Infrastructure03:02 The Evolution of Data Infrastructure05:53 Understanding Agentic Applications08:55 The Architecture War in Data Management11:58 Knowledge vs. Memory in AI15:00 Operational Challenges in Multi-Agent Environments17:58 The Importance of Context in AI Workflows20:49 Bridging the Gap Between AI and Business Value24:10 Customer Success Stories with YugaByte26:47 Rethinking Data Architecture for Enterprises

Celebrating 5 years of my personal/professional brand with myselfRecorded 2/8/2026

Joe Beda and Craig McLuckie co-created Kubernetes, the infrastructure standard that became the default for cloud native computing. Now running Stacklok, they're watching enterprises hit the same identity, permissions, and security problems with AI agents that took the container ecosystem years to resolve, and they're building tools to compress that timeline. In this episode of Founded & Funded, Madrona's Tim Porter sits down with Joe and Craig to talk through what AI adoption actually requires: why MCP is the Docker moment for AI-native applications, how the LLM gateway is becoming a strategic chokepoint for cost, safety, and model flexibility, and why enterprises that don't get the architecture right early will face a familiar trap: vertical integration that looks like productivity and acts like lock-in. They cover: Why the developer workflow is the template for knowledge worker AI adoption, and where the analogy breaks down The mainframe vs. open platform question that will define the AI infrastructure era Why the knowledge worker transition is harder than it looks — and what has to be built differently before developer-grade AI tooling can scale to the rest of your organization The governance gap between human accountability and AI behavior, and what enterprises actually need to build to close it Where to start: MCP controls first, LLM gateway second, and why deploying a platform without staying to close the loop consistently fails Transcript: https://www.madrona.com/the-best-infrastructure-moment-since-cloud Chapters: (0:00) – Introduction (1:04) – Why the Kubernetes Creators Are the Right People to Read This AI Moment (2:18) – Joe's Lesson from Cloud Native: Ignore Conventional Wisdom, Except When You Shouldn't (4:16) – Craig on Enterprises and the Chaos of a New Infrastructure Era (5:32) – Why Joe Rejoined Craig at Stacklok: The Engineer's Case for Getting Your Hands Dirty (7:05) – Developers as Agent Orchestrators: How the Knowledge Worker Transition Will Follow (10:10) – MCP Explained: Craig Sees Docker in 2013 When He Looks at the MCP Spec 1 (7:53) – The Mainframe vs. Open Platform Question That Will Define the AI Era (20:24) – LLM Lock-In Is the Wrong Worry: The Real Risk Is Left of the Model (25:19) – Where Enterprises Actually Start: Developer Posture First, Knowledge Workers Second (29:10) – MCP First, LLM Gateway Second: The Concrete Technical Starting Point (31:19) – How Stacklok Builds Software Now: Agents, Smaller Teams, the Unrecognizable Developer Profile (38:07) – The Recruiter Who Started Building Agents: What AI Tools Do to Role Boundaries

Most enterprises are renters, not owners, of their technology and AI. Raffi Krikorian, Chief Technology Officer of Mozilla, explains why dependence on a handful of closed model providers means losing control over model behavior, pricing, and your own data.In CXOTalk episode 920, Krikorian lays out where open-source AI actually wins in the enterprise, how lock-in happens quietly, and what CIOs and CTOs should do about it now. Krikorian draws on his experience building infrastructure at Twitter and running the self-driving division at Uber to ground the discussion in real engineering and economic tradeoffs, not hype.YOU'LL DISCOVER✅ Why 85% of enterprises believed they could switch AI vendors, but only about 30% actually could when they tried✅ The "renters vs. owners" framing and what it means to control your AI destiny✅ Why Krikorian wants data "protected by architecture, not legal handshakes"✅ How Pinterest reportedly saved on the order of $10 million in a single quarter by switching from closed to open models✅ Why IT is becoming "the HR team for agents," and the read/write "dangerous triangle" of agentic permissions✅ The case for recording your prompts and running your own evaluations instead of trusting public benchmarks✅ Why roughly 70% of enterprise GPUs sit idle, and the missing "LAMP stack for AI" that could put them to work✅ How closed "validation machines" can quietly steer answers toward sponsored outcomes⏱️ TIMESTAMPS (estimated, verify before publishing)0:00 Renters vs. owners: who controls enterprise AI2:26 The risks of depending on closed model makers6:23 How lock-in happens and where open source fits9:53 Regression testing and building your own evals13:24 Pricing instability and the post-IPO cost question23:31 Governance: IT as HR for AI agents32:38 Can a small organization own its AI stack end-to-end?38:47 Validation machines, trust, and sponsored answers43:39 Keeping humans at the center, not in the loop47:23 Can open source beat big tech in AI?51:39 Inside Mozilla.ai: Otari, CQ, Octanus, Thunderbolt55:21 The "rebel alliance" strategy

PagerDuty SVP Rukmini Reddy explains why AI is making software operations exponentially more complex — and why the companies that learn and recover fastest will be the ones that win.Topics Include:PagerDuty powers critical digital operations for enterprises and AI-native companies.Founded by early AWS employees who experienced always-on system failures firsthand.The platform evolved from simple alerting into a full operational intelligence platform.Complexity exploded with microservices, cloud-native infrastructure, and multi-cloud environments.Reliability must be a core value — not an operational afterthought.PagerDuty's culture champions the customer above everything else.Employee recognition extends beyond sales to celebrate the whole business.AI is accelerating software creation but making operations far more complex.AI fails differently — silently, unpredictably, with a much larger blast radius.Enterprises should leverage their operational history as a competitive AI asset.AI-native companies must build operational resilience early, not bolt it on later.The winners won't build fastest — they'll learn and recover fastest.Participants:Rukmini Reddy – Senior Vice President of Engineering, PagerDutySee how Amazon Web Services gives you the freedom to migrate, innovate, and scale your software company at https://aws.amazon.com/isv/

Welcome to RIMScast. Your host is Justin Smulison, Business Content Manager at RIMS, the Risk and Insurance Management Society.   In this episode, Justin interviews François Beaume about the AMRAE 2026 RMIS Panorama available now and about the RISKWORLD 2026 session that François presented. Justin and François discuss ESG functional coverage. They discuss how François uses AI daily. They discuss the continuing increase in RMIS users, moving RIMS out of the niche tool category into an enterprise governance platform. They discuss the 2026 RMIS Panorama findings, the Panorama database, and how you can access it. Listen for insight into the 2026 RMIS Panorama and how your organization compares.   Key Takeaways: [:01] About RIMS and RIMScast. [:16] About this episode of RIMScast. We are delighted to welcome back to RIMScast AMRAE President François Beaume. He's here to discuss the findings of the 2026 AMRAE RMIS Panorama. We'll talk all about emerging trends. But first… [:48] RIMS Virtual Workshops. The next RIMS-CRMP-FED Exam Prep with AFERM will be held on June 16th and 17th. The next RIMS-CRMP Exam Prep with PARIMA will be held virtually on July 21st and 22nd. Links to registration are in this episode's notes. [1:06] You can enroll now in the RIMS CRO Certificate Program in Advanced Enterprise Risk Management hosted by the famous James Lam. Beginning July 15th, workshops will be held bi-weekly from 11:00 a.m. to 3:00 p.m. Eastern Time. The registration link is in the show notes. [1:27] The RIMS ERM Conference 2026 will be held on November 19th and 20th in Columbus, Ohio. We want to hear from you. Submit a session proposal by June 19th to reach engaged practitioners, innovators, and leaders looking for guidance they can utilize right away. [1:45] Help define what's next for Enterprise Risk Management. Submit a session proposal by Friday, June 19th. A link is in this episode's show notes. [1:53] Folks, through the generosity of industry partners, RIMS has launched The Foundation for Risk Management™, which provides scholarships for early-career professionals to attend RIMS events like the RIMS Texas Regional Conference, RIMS Canada Conference, and RISKWORLD. [2:11] The Foundation also helps beneficiaries earn their RIMS-CRMP and fund research projects. To learn more or contribute to the Foundation, visit RIMS.org/FRM and visit the link in this episode's show notes. [2:27] RIMS is back on YouTube. Our handle is @RIMSOfficialChannel. We've got plenty of videos there, including RIMScast, RIMScast Canada video podcasts, and other informative and entertaining content from RIMS. Subscribe to the channel today! [2:46] On with the Show! Our guest today is making his third appearance here on RIMScast. He is the Senior Vice President for Risks and Insurance at Sonepar, and he is the President of AMRAE, the Association for the Management of Risks and Insurance in Enterprises. [3:04] François Beaume is here to discuss the 2026 RMIS Panorama, published by AMRAE, in partnership with EY. Panorama is free and publicly available. [3:14] Panorama provides an in-depth look at the organizations and professionals who are using risk management information systems, how well they've adapted, and guidance for those seeking their first or newest framework. It's always great to speak with him. Let's get to it! [3:28] Interview! François Beaume, Welcome Back to RIMScast! [3:36] François has been Chairman at AMRAE for a year and will be for two more years. Because of his role at AMRAE, Justin wanted to have him on the show to speak about this year's RMIS Panorama. [4:04] Justin mentions a difference between last year's RMIS Panorama and this year's RMIS Panorama. Last year, AI felt like an emerging capability. This year's report shows a 20-point jump in planned or actual AI integration and an 8-point increase in functional coverage. [4:19] At the same time, people aren't always happy with AI. The satisfaction part is still a little bit behind. Justin asks, Are we entering a phase where expectations are outpacing execution? [4:32] François says, Yes, probably. AI has moved faster in CEOs' and leaders' minds than in the organization. Everyone wants the data, governance, and skills. Educating the workforce users takes time. The ambition was there, but the "plumbing" is catching up. [5:11] François says that is what is being reflected in the 2026 RMIS Panorama's deep dive on AI. [5:29] François says he uses AI all day long for various things. As a risk manager, he uses it to increase his efficiency and daily productivity. He thinks that is quite common. He says it's also what we need for faster and better analysis. [6:00] Daily analysis from an AI engine using trusted sources is much faster than manual analysis. Now he has the time to tighten it, understand it, and complement it. [6:44] SONEPAR is using it for their benefit and to better spread risk management principles throughout the organization through Helpdesk or Chatbot, allowing people who are less skilled in risk management or insurance to ask questions through the tools to get support. [7:05] Those tools answer almost 90% of the questions. The remaining questions go to the Risk Management team because they are in a gray area. SONEPAR is using AI more and more and is entering a phase where they are looking at automating some risk management processes. [7:33] François says he is looking at automating business partner assessments, a cumbersome and complex process that the Risk Management team is doing with multiple tools. [7:49] Now, they are trying to streamline it, still with humans making the decisions, based on an AI data set that will be faster and easier to produce and much more reliable. [8:24] Justin says one of the more surprising findings in the RMIS Panorama is that ESG Functional Coverage dropped by 15 points this year. François explains why he thinks this is the case. It's not ESG fatigue, but it's in the way companies are approaching ESG. [9:22] François says a lot of ESG features are moved out of risk management information systems into dedicated tools and sometimes into dedicated teams. In the beginning, some ESG features were encapsulated in Risk Management systems. [9:39] François says it's less and less the case, at least in the tools that are sold in Europe. In the U.S., it could be more mixed. Separating ESG from Risk Management is more linked to maturity and topical evolution, rather than fatigue or a decrease in the importance of ESG. [10:06] Justin says the report also suggests that functional coverage overall has stabilized, which Justin asks if that indicates a mature market. François speaks of maturity and breaks down the RMIS Panorama, made from three surveys: Vendors, Risk Managers, and Insurers. [10:43] Maturity is reflected by a mix of these studies. Almost 250 Risk Managers from 36 countries took the survey. They want smarter features, better insight, better connections, and better decisions. They want the tools RMIS is using to be part of the group's way of functioning. [11:27] François says this is not yet the case. The tools are a bit apart and not fully connected with the CRM and other tools. François says they are starting to change. The risk managers using these tools are expecting change to come in the next few years. [11:52] Justin asks if it's easier today for a startup to build from the ground up with their Risk Management Information System embedded in their processes, or for an established organization. François says today it's easier for both, but big groups are more complex. [12:39] A Quick Break! There are so many other wonderful RIMS events coming up in 2026. The 2026 Florida RIMS Educational Conference will be held from July 28th through August 1st at the lovely Ritz-Carlton in Naples, Florida. A link to the event is in this episode's show notes. [12:57] Register now for the Second Annual RIMS Texas Regional Conference, which will be held from August 10th through 12th at the Grand Hyatt on the San Antonio River Walk. [13:08] The 11th Annual Chicagoland Risk Forum will return to the Old Post Office on Thursday, September 24th, 2026, in Chicago. Visit ChicagolandRiskForum.org for more information. [13:18] The RIMS Western Regional Conference will be held from October 4th through the 7th in Seattle, Washington. Registration is open, and you can also submit a session. Visit RIMSWesternRegional.com and the link in this episode's show notes for more information. [13:35] Save the dates October 18th through the 21st. We will be in Quebec City to celebrate the 50th Live RIMS Canada Conference. Booth sales are already open. Advance registration will open on June 10th. [13:50] Visit RIMSCanadaConference.ca for more information. Also, remember to check out RIMS.org/Canada for our spinoff show, RIMScast Canada, hosted by National Conference Committee Chair, Aaron Lukoni. [14:04] The RIMS ERM Conference 2026 will be held on November 18th and 19th in Columbus, Ohio. The deadline for educational content submissions is Friday, June 19th. Get submissions in now. The link is in this episode's show notes. Registration opens in July. [14:27] Let's Return to Our Interview with François Beaume! [14:36] François Beaume presented at RISKWORLD 2026. You can check out the materials from his presentation on RIMS.org/ASC. You will have had to have registered for or attended RISKWORLD 2026 to check it out. We're here to continue the dialog. [15:12] François feels his session went well. There were 50 to 55 people gathered there to listen and take notes. For François, it was pleasant to do. [16:00] François says you have a feeling when you are connecting with an audience. You can see that they are following you, and the message is passing from you to them. [16:51] François says, If you are losing your audience, you can try to use humor. Sometimes you succeed. He tells of a session in a noisy room, where everybody, including himself, was provided with a helmet, to listen to like a podcast. He could not feel if they were getting the message or not. [17:47] When presenting, you try to hold the attention of the room. Justin says that sometimes he locks eyes with somebody who's listening and then talks to that person and hopes that others will pick up on that energy. [18:18] Justin says risk management is not the easiest topic to make exciting. You have to figure out ways to jazz it up a little bit. [18:31] François says if you are convinced that the topic is interesting, that conviction, at a certain point, will pass through the mic and go to the room. If you are not convinced, the public will feel it. Justin says, If you are not excited to present, the audience will not be captivated. [18:58] François notes that he is French and speaks English like a Frenchman, so he has to manage that. His message may not be phrased as the audience expects. The way an American would phrase it is not the way I am using it. Justin stresses listening better to different accents. [19:58] Justin says François is a very good presenter, and the RISKWORLD audience seemed engaged in his message. Justin says if one person walks away with something actionable, it was worthwhile. François says, "Mission accomplished!" [20:23] Another Quick Break! The Spencer Educational Foundation's Risk Manager on Campus application period is now open, and it will close on June 30th. Grant awardees, colleges, and universities are typically notified in September. [20:43] The Course Development Grant application deadline for Interval Number 2 will be on June 15th, 2026. Award notifications will be sent out in late July. [20:58] General Grant applications are open, and the application deadline is July 30th. Internship Grant applications open on August 15th and close on October 15th. [21:09] Links to each of these grants are in this episode's show notes. Visit SpencerEd.org for more information. [21:17] The Spencer 2026 Funding Their Future Gala will be held on Thursday, September 17th, from 6:30 to 10:00 p.m. at a different venue this year. It will be at the fabulous Waldorf Astoria in New York City. [21:32] Sponsorship opportunities and benefits are available now. A link to the Funding Their Future Gala is in this episode's show notes. [21:40] Next week's guest is the Funding Their Future Gala Honoree, Marya Propis! More Spencer celebrities and board members will be making appearances on RIMScast this summer, as well. [21:53] Let's Conclude Our Interview with François Beaume! [22:09] Justin says the Panorama notes an increase in organizations with more than 200 RMIS users. Does that signal that RMIS is becoming an enterprise-wide infrastructure, or is it still a niche tool for risk teams? [22:26] François says that this is really positive. A Risk Management Information System is not a niche risk tool anymore. It's becoming part of the company infrastructure. [22:44] Once you have hundreds of users, expectations explode, the momentum is there, and user patience drops. As the tool starts to become more massive and interconnected with other tools, you have to manage expectations. The scope of usage of these tools is widening. [23:16] You have not only niche risk usage, but you also have risk management, internal control, insurance, compliance, etc., that are managed inside the tool. The tool reaches all areas of development. The momentum is self-generating. [24:15] François says executive involvement in RMIS usage is positive. Executives want clarity from dashboards. They want to know what matters, why it matters, and what we can do next. They want the deep insight of the tool. They may not go into the tool, but will use the dashboard. [25:10] François speaks of the progress of the techniques of Risk Management Information Systems. Data mining, SaaS contracts, and AI usage have contributed to making RMIS easier to deploy, connect, and access in order to load data, analyze data, and extract data. [26:08] Now is a time of wider usage of Risk Management Information Systems; once they have been adopted, they are there for life, and then you have to make them evolve. [26:21] This means that we have more discussions inside the corporations on RMIS evolutions and replacement. Are we able to make it evolve on its own, or is it time to change? If yes, what kind of process can I depend on to contemplate and manage that change? [26:56] This is executive level. You have created expectations. You have provided dashboards and KPIs, and you have to manage the production. Once it's done, you need a different momentum to run the production and make it better and more accurate over time. It's not easy. [27:40] With their partner EY, AMRAE is finalizing the deployment of the 2026 Panorama Sessions. The French translation will be released by mid-June, and explanation sessions will be run with vendors, risk managers, insurers, and brokers. [28:05] François says AMRAE is already working on the 2027 Panorama, which will be ready for the next RISKWORLD session in New Orleans. [28:27] If someone wants to participate in the Panorama, they need to contact AMRAE. Risk managers will be contacted by the risk management association of the country where they operate. If you are a vendor, you can contact AMRAE. AMRAE contacts insurers and brokers. [29:35] Justin says if you wish to participate, reach out. Go through your risk association where you have membership, like RIMS, FIRMA, or IFRIMA. The confidential information collected helps educate the global risk community. This Panorama is very important for us. [30:08] François says that inside the Panorama, all the contact details are available. As part of the panel, you have access to an online data form. The Panorama has a PDF version, a snapshot of what's in the database. The full database is accessible to anyone. [30:27] François says that as a risk manager or a vendor, you can run your own analysis by filtering and sorting the Panorama database. [30:45] Justin says that's the nice thing about it: AMRAE has made it complimentary and is broadening the horizons of the global risk community by doing so. [30:57] Justin says, I do miss recording with you in person. So, next year, hopefully we get a chance to see each other and have some Cajun food, put the mic up, and eat some jambalaya and talk. It will be great. I want to thank you again, and you're welcome back any time. [31:17] Special thanks again to François Beaume for joining us here on RIMScast! We look forward to seeing him at a future RIMS event. You can visit AMRAE.fr to access the free and publicly available RMIS Panorama 2026. [31:34] Plug Time! You can sponsor a RIMScast episode for this, our weekly show, or a dedicated episode. Links to sponsored episodes are in the show notes. [32:03] RIMScast has a global audience of risk and insurance professionals, legal professionals, students, business leaders, C-Suite executives, and more. Let's collaborate and help you reach them! Contact pd@rims.org for more information. [32:21] Become a RIMS member and get access to the tools, thought leadership, and network you need to succeed. Visit RIMS.org/membership or email membershipdept@RIMS.org for more information. [32:39] Risk Knowledge is the RIMS searchable content library that provides relevant information for today's risk professionals. Materials include RIMS executive reports, survey findings, contributed articles, industry research, benchmarking data, and more. [32:55] For the best reporting on the profession of risk management, read Risk Management Magazine at RMMagazine.com. It is written and published by the best minds in risk management. [33:09] Justin Smulison is the Business Content Manager at RIMS. Please remember to subscribe to RIMScast on your favorite podcasting app. You can email us at Content@RIMS.org. [33:21] Practice good risk management, stay safe, and thank you again for your continued support!   Links: RIMS ERM Conference 2026 | November 19‒20 in Columbus, Ohio | Session Submission Deadline: Friday, June 19 RIMS Canada Conference — Oct. 18‒21, 2026 | Quebec City | www.rimscanadaconference.ca | Registration Opens June 10 RIMScast on YouTube! Spencer Educational Foundation — Scholarships and Grants | Open Calls and Timelines. RIMS-CRO Certificate Program In Advanced Enterprise Risk Management | July‒Sept. 2026 Cohort | Led by James Lam | Register Now! 2026 Florida RIMS Educational Conference | July 28‒Aug. 1 | Register Now RIMS Texas Regional Conference 2026 | Aug. 10‒12 in San Antonio | Register Now! ChicagoLand Risk Forum | Sept. 24, 2026 RIMS Western Regional Conference — Oct. 4‒7, 2026 | Seattle, WA | Register Today and Submit an Educational Session! RIMS Risk Management Magazine | Contribute | Look for the Awards Edition in "Digital Issues"! RIMS Now RIMS-Certified Risk Management Professional (RIMS-CRMP) | Insights Video Series Featuring Joe Milan! RIMS, the Foundation for Risk Management The Strategic and Enterprise Risk Center RIMS Diversity Equity Inclusion Council RIMS-CRMP Stories RIMScast Canada — Episodes Now Live RISK PAC | RIMS Advocacy RISKWORLD 2026 Presentations Available via Attendee Service Center — www.RIMS.org/Asc - and via the RIMS Events App RMIS Panorama: https://www.amrae.fr/bibliotheque-de-amrae/2026-rmis-panorama Upcoming RIMS-CRMP Prep Virtual Workshops: RIMS-CRMP Exam Prep with PARIMA | July 21‒22, 2026 RIMS-CRMP-FED Exam Prep with AFERM | June 16‒17, 2026 Full RIMS-CRMP Prep Course Schedule See the full calendar of RIMS Virtual Workshops   Upcoming RIMS Webinars: RIMS.org/Webinars   Related RIMScast Episodes: "Strategy and Change with Ward Ching and Aaron Olson" "Live from RISKWORLD 2026!" "The Evolving Role of the Risk Analyst" "AI and the Future of Risk with Dan Chuparkoff" "Live from RISKWORLD 2025" "AI Risks and Compliance with Chris Maguire"   Sponsored RIMScast Episodes: "AI-Scale, Risk Ready: Engineering Controls for the New Data Center Boom" (New!) | Sponsored by Global Risk Consultants, a TÜV SÜD Company "Facing Into Risk: Navigating the New Risk Landscape" (New!) | Sponsored by AXA XL "Secondary Perils, Major Risks: The New Face of Weather-Related Challenges" | Sponsored by AXA XL "The ART of Risk: Rethinking Risk Through Insight, Design, and Innovation" | Sponsored by Alliant "Mastering ERM: Leveraging Internal and External Risk Factors" | Sponsored by Diligent "Cyberrisk: Preparing Beyond 2025" | Sponsored by Alliant "The New Reality of Risk Engineering: From Code Compliance to Resilience" | Sponsored by AXA XL 'Change Management: AI's Role in Loss Control and Property Insurance" | Sponsored by Global Risk Consultants, a TÜV SÜD Company "Demystifying Multinational Fronting Insurance Programs" | Sponsored by Zurich "Understanding Third-Party Litigation Funding" | Sponsored by Zurich "What Risk Managers Can Learn From School Shootings" | Sponsored by Merrill Herzog "Simplifying the Challenges of OSHA Recordkeeping" | Sponsored by Medcor "How Insurance Builds Resilience Against an Active Assailant Attack" | Sponsored by Merrill Herzog "Third-Party and Cyber Risk Management Tips" | Sponsored by Alliant   RIMS Publications, Content, and Links: RIMS Membership — Whether you are a new member or need to transition, be a part of the global risk management community! RIMS Virtual Workshops On-Demand Webinars RIMS-Certified Risk Management Professional (RIMS-CRMP) RISK PAC | RIMS Advocacy RIMS Strategic & Enterprise Risk Center RIMS-CRMP Stories — Featuring RIMS President Manny Padilla!   RIMS Events, Education, and Services: RIMS Risk Maturity Model®   Sponsor RIMScast: Contact sales@rims.org or pd@rims.org for more information.   Want to Learn More? Keep up with the podcast on RIMS.org, and listen on Spotify and Apple Podcasts.   Have a question or suggestion? Email: Content@rims.org.   Join the Conversation! Follow @RIMSorg on Facebook, Twitter, and LinkedIn.   About our guest: François Beaume, SVP Risks and Insurance, Sonepar President of AMRAE   Production and engineering provided by Podfly.

Host Jason Pereira interviews Thomas Clawson, co-founder of Slant, an AI-native CRM built from the ground up for financial advisors. Launched in late 2025, Slant shifts the traditional CRM focus by using the "household" as its core data object. This structure allows its AI engine to instantly generate accurate context for client summaries, meeting prep, and firm-wide queries like tracking geographic exposure or review cadences.The conversation highlights how Slant uses natural language and selectable AI models to automate record updates immediately after client meetings. Clawson also discusses the hurdles of wealthtech integration and maps out Slant's future, including public API access, deeper custodian connections, and proactive, relationship-focused alerts.This episode is a must-listen for forward-thinking advisors and operations leaders looking to replace rigid databases with a flexible, AI-driven client management system.Episode Highlights:00:00 Welcome and Guest Intro00:43 Slant Origin Story01:59 Rethinking CRM Around Households05:15 Defining a Household07:57 AI Features and Chat Everywhere10:47 Workflow Flexibility and Change15:18 Solos vs Enterprises in AI19:11 Open Models and Public API20:24 Data Model and Structured Inputs24:05 Roadmap Integrations and Deliverables27:34 Lightning Round and ClosingResources:Facebook – Jason Pereira's FacebookLinkedIn – Jason Pereira's LinkedInWoodgate.com – SponsorSlantLinkedIn - Thomas Clawson's LinkedIn Hosted on Acast. See acast.com/privacy for more information.

Get the free Core Drives in the Wild guide, behavioral design applied to real corporate cases: professorgame.com/WildCD Episode Summary Rob breaks down why enterprise AI adoption stalls even with paid licenses and training, while a group of students beat a locked, proctored exam with ChatGPT and no support at all. Reading both cases through the Octalysis Framework, he shows how the exam accidentally stacked Core Drive 8 (Loss & Avoidance), Core Drive 6 (Scarcity & Impatience), and Core Drive 2 (Development & Accomplishment) into a ferocious, if mispointed, motivation engine. The enterprise bought the most capable tool and surrounded it with zero motivation, so nobody opened the app. Listeners learn why AI adoption is a motivation problem wearing a tooling costume, and leave with a two-part diagnostic question to ask of any AI initiative. About the Host Rob Alvarez is Head of Engagement Strategy, Europe at The Octalysis Group (TOG), a leading gamification and behavioral design consultancy. A globally recognized gamification strategist and TEDx speaker, he founded and hosts Professor Game, the #1 gamification podcast, and has interviewed hundreds of global experts. He designs evidence-based engagement systems that drive motivation, loyalty, and results, and teaches LEGO® SERIOUS PLAY® and gamification at top institutions including IE Business School, EFMD, and EBS University across Europe, the Americas, and Asia. Key Takeaways Students beat a lockdown, proctored, face-to-face online exam by getting ChatGPT to answer questions live through a Chrome extension, with no license, no training, and no change management. Adoption was instant, total, and creative enough to defeat the security. The exam accidentally stacked three Black Hat Core Drives: Core Drive 8 (Loss & Avoidance, failing is high-stakes), Core Drive 6 (Scarcity & Impatience, one timed shot), and Core Drive 2 (Development & Accomplishment, clearing the hurdle to the grade). Enterprises buy the paid license, training, IT support, and a leadership mandate, then adoption stalls because none of those things are motivation. There is no personal loss for ignoring the tool and no personal win for using it. Motivation pointed at the wrong goal produces flawless adoption of exactly the behavior you did not want. The students aimed AI at passing, not learning, and got it. As AI removes capability constraints, the human motivation layer becomes the only constraint left, which is why behavioral design matters more in the AI era, not less. The diagnostic: ask what your team personally gains by using the tool and what they personally lose by ignoring it. If the honest answer is "nothing much either way," no rollout plan will save it. Topics Covered 0:00 - Students hacked a locked exam 0:52 - Same tech, opposite outcome 1:44 - Adoption was never the problem 2:39 - The exam's accidental motivation engine 4:31 - Almost entirely Black Hat motivation 5:18 - Why the funded enterprise stalls 6:30 - Adoption and direction both matter 7:41 - Why behavioral design matters with AI 7:55 - Your diagnostic question for today Mentioned in This Episode The Octalysis Framework, developed by Yu-kai Chou ChatGPT (OpenAI) Core Drives in the Wild, the Professor Game free guide Free Resources and Get in Touch Core Drives in the Wild: Professor Game Free Guide Get Daily Value on Your Email Let's chat about your gamification project YouTube LinkedIn Instagram Facebook Start Your Community on Skool for Free Ask a question

Vieth v. MOM Enterprises, LLC

Microsoft Build 2026 announced an end-to-end agentic AI stack. COMPUTEX Taipei confirmed heterogeneous AI infrastructure across ARM, Marvell, Intel, Qualcomm, and NVIDIA. Alphabet raised $80 billion. Cisco Live repositioned the network as the AI platform. Patrick Moorhead and Daniel Newman break it all down alongside earnings from Broadcom, HPE, Palo Alto Networks, and CrowdStrike, plus the token cost conversation, the edge AI push, and what Palantir and Oracle are saying about proprietary data as the real AI moat. The handpicked topics for this week are: Microsoft Build 2026 Announced an End-to-End Agentic AI Stack: Microsoft shipped MAI-Thinking-1, its first homegrown thinking model, alongside Scout, Microsoft IQ, Project Solara, and a Majorana 2 quantum update targeting a 2029 commercial timeline with claims of a 1,000x reliability gain. Pat describes MAI-Thinking-1 as likely better than Sonnet 4.6 in blind testing and delivering close to GPT 5.5 quality at a far lower cost. Scout is Microsoft's first autopilot agent, anchoring the M365 Agent Suite with Office Pilot Agent Mode and Agent 365. Microsoft IQ serves as the context layer, integrating M365, business data, boundary IQ, and web IQ with GitHub Copilot, Foundry, and Copilot Studio. Project Solara is a new Android-based platform built for agent-first devices across transportation, retail, and hospital settings. Microsoft also added 83 Unix commands to the Windows stack. Dan frames Microsoft's real play as distribution, not frontier model development, noting that the open model ecosystem being pulled into the platform will matter more to CFOs managing token costs at scale. (The Decode) The AI Stack Goes Multi-Silicon — COMPUTEX Taipei 2026 Confirms Heterogeneous AI Infrastructure: ARM's AGI CPU is in production with Google moving its TPU head node to ARM, and adding Oracle and ByteDance as new customers. ARM also introduced a new switch, the TT100, and put the 51T CPO switch on stage. Marvell received a trillion-dollar company endorsement from Jensen Huang, adding $90 billion in market cap on the comment alone. Intel announced disaggregated inference details and Xeon 6+ Clearwater Forest, its first 18A data center processor. Vista Equity and Cambium Capital announced a NeoCloud called Vector Core Compute, with Xeon 6 handling orchestration, Salmonova RUs handling decode, and Blackwell GPUs handling pre-fill. Qualcomm's Cristiano Amon announced the Dragonfly data center brand with Snapdragon C details coming at their June investor day. The WSTS raised the 2026 semiconductor TAM forecast by 90% to $1.51 trillion, with Pat noting the market could hit a trillion dollars if memory is excluded entirely. (The Decode) NVIDIA RTX Spark and the Edge AI Push: NVIDIA coordinated with ARM and Microsoft around the RTX Spark at COMPUTEX, with the shared message being that the future of Windows is here. Signal65's Ryan Shrout asked Jensen directly why NVIDIA wants to be in the PC business, given low margins and diminishing returns. Dan frames the answer in the context of devices increasingly becoming mobile data centers, capable of running models at much greater efficiency than cloud delivery. The edge AI conversation is also directly tied to token cost economics: as intelligence delivery moves closer to the device, the cost per token drops significantly. The jury is still out on whether NVIDIA will meaningfully disrupt the PC market, but its influence over OEMs like Lenovo and Dell that depend on it for data center gives it real leverage over SKUs. (The Decode) Token Economics and Frontier Model Cost Pressure: Dan and Pat discuss a substantive shift in how enterprises are thinking about AI consumption costs. Dan argues that "token maxing," the practice of defaulting to the most powerful frontier model for every task, has now effectively peaked, as bills have come due at scale. Companies paying for tokens in volume are starting to question whether they can afford the prices that frontier models actually cost to deliver. Pat pushes back, saying the dynamic is still present, but both analysts agree that the market is moving toward a model where token selection is matched to the job, with Microsoft's MOE approach and thinking models positioned to help CFOs manage that economics story. (The Decode) Continuum Goes Public at Highest Valuation for an AI Platform: Dan notes that Continuum, the Honeywell-spawned quantum company, went public this week at what he calls the highest valuation for an AI platform to date. He flags that IonQ will likely contest that characterization. The broader context is Microsoft entering the quantum conversation with Majorana 2 at Build, a name that has largely been absent from the quantum race, while IBM has received most of the attention. (The Decode) AI CapEx Has Outgrown Cash Flow — Alphabet's $80 Billion Equity Raise: On June 1, Alphabet announced an $80 billion equity capital raise, upsized to $85 billion, structured as $40 billion ATM, $30 billion underwritten, and a $10 billion private placement with Berkshire Hathaway anchoring. Pat frames the questions over CapEx returns as entirely dependent on whether you are an AI boomer or a doomer: if the payback comes, the raise is the right move. If it does not, the math doesn't close. Dan argues the investment is existential, drawing parallels to how infrastructure-first companies have always spent ahead of monetization, and notes that Google's equity is being used as a capital engine that may be more efficient than the debt markets right now. Both analysts flag the downstream implications for Broadcom, MediaTek, and Marvell given the TPU connection. (The Decode) The Network Becomes the AI Platform: Cisco Live 2026: Cisco launched Silicon One P200, the Secure AI Factory with NVIDIA and Spectrum X, AgenticOps, MCP-native automation, Cisco IQ, LiveProtect, and folded Astrix Security and Galileo into Splunk under one control plane. Pat identifies Cisco Cloud Control as the biggest announcement of the entire show, pulling together Catalyst, Meraki, Nexus, Firewall, and WebEx under agentic ops that run natively through MCP, with code running directly on smart switches that have x86 processors. Pat also credits Cisco for establishing Silicon One as a credible chip alternative for hyperscalers capable of taking on Tomahawk and Jericho. Dan frames the long-term opportunity as campus and branch enablement when industrial AI and robotics deployments accelerate, arguing that the numerator of AI's economic impact has barely started, as edge deployment spending has not yet begun. (The Decode) The Flip: Did Microsoft Build 2026 Effectively End the OpenAI Partnership? Pat argues the divorce decree has been filed. MAI-Thinking-1 was built with zero distillation from third-party models offering clean enterprise data lineage, with Maia 200 in production plus Anthropic chip supply, which signals vendor hedging. OpenAI is going all-in on AWS, which means you cannot be married to two people, and the full Build stack covering model, OS containment via MXC, agents via Scout and Agent 365, and context via Microsoft IQ removes every architectural dependency on OpenAI. Dan counters that Microsoft is hedging rather than leaving and predicts the partnership will run through the decade. Enterprise Copilot customers are explicitly showing in data that they demand GPT 5.5, internal benchmarks have not been independently validated, and Microsoft stands to make meaningful money from the OpenAI IPO. (The Flip) Broadcom Q2 FY26 Earnings: Broadcom posted revenue of $22.19 billion, a narrow miss depending on which consensus data set is used, with EPS of $2.44 beating estimates and AI semis at $10.8 billion. Hock Tan declined to raise the $100 billion full-year AI chip target, and the stock dropped 13% in premarket trading. Q3 guide came in at $29.4 billion. Pat calls the miss a timing issue driven by Google's multi-sourcing across Marvell, MediaTek, and Broadcom rather than a fundamental problem. Dan flags that Hock Tan opened the earnings call by accidentally reading from the 2025 print, calling it "not the best moment." Sell-side re-ratings held in the 500s across Jefferies, Mizuho, and Deutsche Bank despite the drop, with Futurum Equities having it at 600. (Bulls and Bears) Hewlett Packard Enterprise Q2 FY26 Earnings: HPE delivered revenue of $10.68 billion, up 40% year over year, and EPS of $0.79, up 100%. Juniper integration and AI servers both outperformed, and all FY26 guides were raised. The stock jumped 19% after hours before settling into a roughly 15% gain, with HPE up 68% over the last month. Pat frames HPE as a value play rather than a volume play, methodically targeting enterprise and sovereign cloud deals where it can maintain profitability, rather than competing for massive NeoCloud volume. Antonio Neri was clear on the call that the profitability pull-forward is a one-shot deal. Pat and Dan will both be at HPE Discover the week after next to interview Neri and the C-suite. (Bulls and Bears) Palo Alto Networks Q3 FY26 Earnings: Palo Alto posted revenue of $3.0 billion, up 31% year over year, beating the $2.94 billion estimate, with non-GAAP EPS of $0.85, beating the $0.79 to $0.81 range. NGS ARR reached $8.1 billion, up 60% year over year, including $1.6 billion from CyberArk and Chronosphere. RPO hit $18.4 billion, up 36%. Both FY26 revenue and EPS guides were raised. Adjusted FCF margin came in at 38.5% TTM, up 430 basis points. The stock jumped 11% immediately after hours, then drifted lower. Pat points to 2,200 platformized customers and 120% net retention as the most important metrics. Dan notes the SaaSpocalypse thesis continues to be wrong. (Bulls and Bears) CrowdStrike Q1 FY27 Earnings and the Proprietary Data Moat Argument: CrowdStrike posted revenue of $1.39 billion with EPS of $1.10 and ARR of $5.51 billion. Net new ARR of $255.8 million set a Q1 record, up 32% year over year. FY27 net new ARR guide was raised by $52 million to a $1.29 billion midpoint, and FY27 revenue was raised to $5.915 to $5.959 billion. A 4-for-1 stock split was announced effective July 2nd. The stock dropped 11% despite the beat after a 64% year-to-date run into earnings. Dan uses the results to make a broader argument against the software disruption thesis, referencing Palantir CEO Alex Karp daring customers to build without him using Anthropic or OpenAI, and Larry Ellison's argument that the real AI value unlock sits in proprietary enterprise data that is not accessible to frontier models. Enterprises with governed, secure, proprietary data will continue to need platforms like CrowdStrike regardless of what frontier models can do. (Bulls and Bears) Six Five Summit is coming. Salesforce CEO Mark Benioff will kick off the event. Register and stay current at sixfivemedia.com/summit. Watch the full video at sixfivemedia.com, and be sure to subscribe to our YouTube channel so you never miss an episode.   The Decode Microsoft Declares Independence — Build 2026 Ships an End-to-End Agentic AI Stack (MAI-Thinking-1 + Scout + Microsoft IQ + Project Solara + Majorana 2) https://www.theverge.com/tech/941738/microsoft-build-2026-biggest-announcements The AI Stack Goes Multi-Silicon — Computex 2026 Confirms a Heterogeneous AI Infrastructure (ARM + Marvell + Intel ASIC + Qualcomm + RTX Spark); WSTS Raises 2026 Semi TAM Forecast 90% to $1.51T https://www.tomshardware.com/tag/computex AI Capex Has Outgrown Cash Flow — Alphabet's $80B Equity Raise Is the Largest in U.S. Corporate History; Berkshire Anchors $10B https://abc.xyz/investor/news/news-details/2026/Alphabet-Announces-Proposed-80-Billion-Equity-Capital-Raise-to-Expand-AI-Infrastructure-and-Compute-2026-b0myAMewCa/default.aspx The Network Becomes the AI Platform — Cisco Live 2026 Launches Silicon One P200, Secure AI Factory (with NVIDIA), AgenticOps, Astrix Security + Galileo https://www.cisco.com/site/us/en/about/whats-new/index.html The Flip Did Microsoft Build 2026 Effectively End the OpenAI Partnership? MAI-Thinking-1 Beats Sonnet 4.6 in Blind Testing, Microsoft Claims GPT-5.5 Parity at 10x Cost Efficiency — Will MS Quietly Wind Down OpenAI Exclusivity by FY28, or Is OpenAI Still the Frontier Anchor Microsoft Needs?   FOR:  MAI-Thinking-1 beating Sonnet 4.6 in blind preference + GPT-5.5 parity at 10x cost efficiency is a frontier-model independence proof point https://www.latent.space/p/ainews-microsoft-build-mai-thinking Build 2026: Accumulating Evidence of Microsoft's AI Independence — EDN (June 4) — https://www.edn.com/build-2026-accumulating-evidence-of-microsofts-ai-independence/ Maia 200 in production + Anthropic-Maia chip talks signal Microsoft is hedging its inference vendor stack https://blogs.microsoft.com/blog/2026/01/26/maia-200-the-ai-accelerator-built-for-inference/ Microsoft canceled Anthropic's internal software licenses + pivoted to chip-supply pursuit — customer-not-competitor positioning https://www.cnbc.com/2026/05/21/anthropic-microsoft-maia-200-ai-chip.html   AGAINST:  Enterprise Copilot customers explicitly demand GPT-5.5 — internal benchmarks don't replace the brand https://learn.microsoft.com/en-us/microsoft-365/copilot/release-notes?tabs=all MAI-Thinking-1 benchmarks haven't been third-party verified — Microsoft is the only source https://www.latent.space/p/ainews-microsoft-build-mai-thinking The MS-OpenAI partnership is contractual through 2030+ — unwinding it is impractical and expensive https://blogs.microsoft.com/blog/2026/04/27/the-next-phase-of-the-microsoft-openai-partnership/ Microsoft's actual strategic risk is OpenAI leaving, not MS leaving — Anthropic + OpenAI IPOs make OpenAI exit risk the real concern https://www.anthropic.com/news/confidential-draft-s1-sec Bulls & Bears Broadcom (AVGO) Q2 FY26 ACTUALS — Rev $22.19B (Narrow Miss) + EPS $2.44 (Beat); AI Semis $10.8B; Hock Tan Refuses to Raise the $100B Full-Year AI Chip Target — Stock −13% Premarket; Q3 Guide $29.4B https://www.cnbc.com/2026/06/03/broadcom-avgo-earnings-report-q2-2026.html Hewlett Packard Enterprise (HPE) Q2 FY26 ACTUALS — Blowout: Rev $10.68B (+40%), EPS $0.79 (+100%); Juniper Integration + AI Servers Both Outperform; FY26 Guides All Raised; Stock +19% AH https://www.businesswire.com/news/home/20260601866494/en/HPE-Reports-Fiscal-2026-Second-Quarter-Results Palo Alto Networks (PANW) Q3 FY26 ACTUALS — Beat-and-Raise: Rev $3.0B (+31% YoY, Beat $2.94B), Non-GAAP EPS $0.85 (Beat $0.79-0.81); NGS ARR $8.1B (+60% YoY, $1.6B from CyberArk + Chronosphere); RPO $18.4B (+36%); FY26 Revenue + EPS Guides BOTH RAISED; Adj FCF Margin 38.5% TTM (+430 bps); Stock +11% Immediate AH, Then Drifted Lower https://www.paloaltonetworks.com/company/press/2026/palo-alto-networks-reports-fiscal-third-quarter-2026-financial-results CrowdStrike narrowly beats estimates on AI tailwinds, but stock falls 9% — CNBC (June 3) — https://www.cnbc.com/2026/06/03/crowdstrike-crwd-q1-2027-earnings.html  

Individual AI productivity gains are already here, but they are uneven, and they are not the main event. In this episode, Tim Sears, Chief AI Officer at HTEC, argues that the real transformation in software development will arrive when AI becomes a catalyst for teamwork rather than an enhancer of individual performance. The conversation examines why software development is the clearest available model for how AI will eventually reshape every business function, how the developer role is being elevated from syntax and grunt work toward architecture, security, and client judgment, why the traditional build-versus-buy decision is being replaced by a build-versus-build reality, and what it will mean when perfection in enterprise software becomes the expected standard rather than the exception. For senior leaders trying to move from supporting AI in principle to actually delivering change, Sears offers a direct and practitioner-grounded view of what needs to change in teams, in expectations, and in the way business processes are understood and redesigned. AI is moving fast — new tools, new research, new use cases every week. Emerj synthesizes what matters most, so senior leaders and practitioners can stay ahead without getting buried. Join 85,000+ subscribers and get the most useful AI business insights delivered to your inbox. Visit: http://emerj.com/ad1

What if AI Actually Costs More Than Humans?   The headcount reduction mandate has landed on your desk: replace talent with AI and cut costs. But beneath the vendor demos and boardroom promises lies a dangerous assumption - that artificial intelligence is automatically cheaper than human expertise.   What if the token economics tell a different story?   Join us for a provocative livestream that flips the AI narrative and protects your workforce strategy.   • The hidden maths of token consumption -and why projected savings evaporate at scale   • Why cost-per-inference is rarely modelled against fully-loaded employee costs in vendor ROI   • Talent attrition: when top performers leave because they see AI replacement unfolding   • Quality degradation and the invisible cost of human-in-the-loop error correction   • Vendor lock-in: how API pricing volatility turns fixed labor into unpredictable OpEx   • The productivity paradox: why AI-augmented teams outperform pure replacement strategies   • Compliance blind spots: liability, bias audits, and regulatory costs headcount never triggered   • Retraining debt: the unbudgeted expense of prompt engineering and system maintenance   • The competitive cost of hollow teams when institutional knowledge walks out the door   • Frameworks to model true total cost of AI ownership before approving any reduction-in-force   This is not an anti-AI argument - it is a financial reality check for leaders pressured to cut first and calculate later. Before you trade headcount for tokens, understand the true cost of replacing humans with models.   We're on Friday 5th June, 2pm BST. Register now and bring your C-suite the data they need!       Ep386 is supported by our friends Ashby   The all-in-one recruiting platform that evolves at the speed of AI. ✨Empowering ambitious teams from Startups to Enterprises.   Ashby can handle the whole pipe - ATS, CRM & Sourcing, Scheduling, and Analytics - while incorporating the latest AI advancements every step of the way.   Learn how Ashby helps companies at every size up level their hiring - contact one of team here today

Wipro Brings Enterprise Perspective to Cisco Cloud Control, Podcast Wipro's Uday Kiran discusses what Cisco's new platform means for enterprise customers, global partners and the shift to unified, AI-ready operations By Doug Green “Cisco Cloud Control unifies all of these domains.” In this Technology Reseller News podcast, recorded virtually during Cisco Live, Doug Green speaks with Uday Kiran of Wipro about Cisco Cloud Control and what the announcement means when viewed from the front lines of enterprise transformation. For Wipro, the announcement represents a logical evolution in Cisco's portfolio. Kiran says enterprise customers are often managing separate domains across networking, security and observability. Those domains have historically operated as “multiple islands,” creating complexity for IT teams that need visibility, speed and control across distributed environments. Wipro brings a global systems integrator's view to the conversation. The company serves enterprise customers in more than 64 countries, has more than 250,000 employees, works with more than 1,000 enterprise customers, and has partnered with Cisco for more than 30 years, according to Kiran. That scale gives Wipro a practical view of what customers are asking for now. Enterprises are not simply looking for another dashboard or another tool. They are looking for ways to simplify operations, improve resilience, bring security and networking closer together, and make AI useful inside complex production environments. Cisco Cloud Control is important because it points toward a more unified operational model. Instead of treating network, security and observability as separate disciplines, the platform is designed to bring those areas together. For partners such as Wipro, that creates a larger opportunity than product deployment. It creates a consulting, integration and managed services opportunity around helping enterprises modernize operations, rationalize toolsets, and prepare for AI-enabled infrastructure. The discussion also reflects a broader Cisco Live theme: AI is moving from concept to operations. As enterprises adopt agentic AI, infrastructure must become more observable, more secure and more automated. Wipro's role is to help customers make that transition in real environments, where legacy systems, global operations and business continuity all matter. In this podcast, Kiran offers a partner's view of Cisco Cloud Control: not just what was announced, but why it matters to enterprise customers trying to turn fragmented IT operations into a more unified, intelligent and resilient operating model.

Accounting Voices is a senior leadership platform hosted by Rob Brown that interprets the forces reshaping accounting firms across North America and beyond.This "AI Reality Inside Firms" series brings together influential accounting leaders to answer the same five structured questions about how AI is actually landing inside firms.No hype. No vendor narratives. Just honest leadership perspective from someone navigating AI from the inside.Today's special guest is Randy Johnston, Founder at K2 Enterprises.The five questions:Where is AI genuinely reshaping strategic direction for firms?What are firms still getting wrong about AI?Which AI-related leadership decisions will matter most over the next two years?Where is AI creating the greatest internal tension in firms?By 2027, what will separate leading firms from the rest?Five questions. One honest conversation. Part of a season that is building a definitive picture of AI reality inside accounting firms in 2026.Watch this episode on YouTube: https://youtu.be/TV-p6NI6GyoThank you to our Season Partners for making this series possible.Fieldguide is the AI-native platform for audit and advisory enabling human and AI collaboration to scale capacity, improve quality and transform how firms operate. fieldguide.ioInstead is the first AI agent that owns end-to-end tax from research, planning, filing, and defense all in one system. It replaces CCH, GoSystems, UltraTax, Lacerte, ProConnect, Drake and many more. instead.comKarbon is the global leader in AI-powered practice management software for accounting firms. Their research into how technology is reshaping firm performance is essential reading for anyone leading a firm in 2026. karbonhq.comDigits is the world's first AI-native accounting platform. It's accounting software that works for you to deliver real-time financials and automate the month-end close. digits.comFiled is the intelligent tax workspace for preparation and review automation and the only AI for prep, review and planning that runs inside your tax software especially made for high-volume firms. filed.comAccounting Voices is a senior sense-making platform for firm owners, managing partners and senior operators navigating the forces reshaping accounting firms. Host Rob Brown convenes structured conversations with leaders across the profession to interpret what AI, private equity, consolidation and leadership pressure mean in practice.This season, AI Reality Inside Firms, brings together senior accounting firm leaders answering the same five structured questions about how AI is actually landing inside firms, separating execution from narrative.Find all episodes on your preferred podcast platform or on the Accounting Voices YouTube channel. https://www.youtube.com/@accountingvoicesTo find out more or to explore season partnership opportunities, connect with Rob on LinkedIn. https://www.linkedin.com/in/therobbrown

Qumulo and Cisco Launch Bridge-to-Cloud Architecture to Help Enterprises Beat the Flash Crunch at Cisco Live 2026 By Doug Green “Capacity extends to the cloud instantly. Users and applications never know that the systems have been extended into the cloud.” At Cisco Live 2026, Doug Green spoke with Brandon Whitelaw of Qumulo about the company's new Bridge-to-Cloud architecture with Cisco, a solution designed to help enterprises respond to one of the most urgent infrastructure challenges of the AI era: fast-growing data workloads, constrained flash supply, longer hardware lead times and rising demand for high-performance storage. Qumulo describes itself as an accelerated data company. In the podcast, Whitelaw explains that Qumulo helps organizations store and manage mission-critical file and object data across data centers, edge environments and the major public clouds. The goal is to unify those datasets into a consistent, AI-enabled data fabric that can support both today's high-performance applications and tomorrow's AI pipelines. Qumulo's customers include autonomous driving companies, media and entertainment organizations, special effects shops, sports broadcasters, life sciences organizations, genomic research teams, hospitals, public sector agencies and government entities. The common thread is data: large, high-capacity, high-performance datasets that must be available, protected and ready for use. The Cisco announcement focuses on Cloud Native Qumulo Enterprise combined with Cisco Unified Computing System through Qumulo's Cloud Data Fabric. The solution is designed to let enterprises extend file workloads from on-premises Cisco UCS infrastructure into the cloud without forcing a disruptive migration, application refactoring or a rebuild of existing workflows. For enterprise IT teams, the problem is practical. AI infrastructure demand is reshaping the market for memory and NVMe systems, creating pressure on traditional capacity planning. Instead of waiting months for new hardware or overprovisioning all-flash systems, Qumulo and Cisco are offering a bridge: keep trusted on-premises infrastructure in place while extending selected workloads into the cloud as needed. Whitelaw says the architecture gives enterprises a way to free up on-premises infrastructure for the most critical applications, while using cloud capacity to handle growth, burst demand and AI-readiness. The result is a hybrid model that is not simply about cloud migration. It is about operational flexibility. The solution also positions enterprise data for AI and analytics. Qumulo says CNQ Enterprise includes Cloud Data Fabric and NeuralProtect and can run on Cisco UCS on-premises as well as across AWS, Azure, Google Cloud and Oracle Cloud Infrastructure. The architecture is intended to make enterprise datasets available for AI pipelines into services such as Microsoft AI Foundry, AWS Bedrock and Google Vertex AI. For Cisco partners, service providers and enterprise IT teams, the message from the podcast is clear: hybrid cloud is becoming a pressure-release valve for data infrastructure. The Bridge-to-Cloud model offers a way to gain capacity relief, preserve application continuity, support elastic scale and prepare data for AI without forcing customers into a disruptive replatforming project. Qumulo CNQ Enterprise is available now for deployment on Cisco UCS on-premises infrastructure and across AWS, Azure, Google Cloud and OCI. It is also available through Cisco for simplified enterprise procurement. Qumulo is exhibiting at booth 4018 at Cisco Live 2026 in Las Vegas. Learn more at: https://qumulo.com/product/cisco/

In 1994, Daragh Mahon won the green card lottery and moved from Ireland to Atlanta. His first American job was driving an eighteen-wheeler for Schneider. Thirty years later, he runs IT for Werner Enterprises, one of the largest trucking companies in North America, with 12,000 drivers moving freight across the country every day.In this episode of Kill Chain, host Terry Reinert sits down with Daragh to unpack a career arc most CIOs never take and a perspective on cybersecurity, AI, and the future of transportation that most haven't earned.What you'll hear:Why Daragh asked every autonomous trucking company the same security question and never got an answerThe 3 critical infrastructure sectors a foreign adversary attacks first (and why transportation is on the list)Why he wants the tech industry to "stop talking about AI"The AI backlash brewing in colleges that CIOs aren't trackingThe story of signing a contract he had no authority to sign and getting 12 months to make it workWhy real innovation only happens at the startup level, and what the big software companies stopped doingBuilding security into corporate DNA instead of bolting it onThe Werner Accelerator and why every corporation should run onePredictions for the next ten years (and why he refuses to make them)About the guest:Daragh Mahon is the EVP and CIO of Werner Enterprises (NASDAQ: WERN). Before Werner, he led IT at Vonage and held senior roles at Sage and Peachtree Software. He emigrated from Ireland to the US in 1994 through the Morrison Visa Program.About the show:The Kill Chain Podcast is a conversation series about cybersecurity, transportation, and the future of fleet operations, hosted by Terry Reinert, CEO of Fleet Defender. New episodes drop every other week.Want to learn more about securing your fleets, platforms, or mission critical systems? Contact us at FleetDefender.com.

In this May 2026 AI news roundup, we move beyond the headlines and look at the bigger shift happening across the AI world: agents are becoming real, enterprises are learning how to manage them, and trust is becoming the gatekeeper for scale.This episode explores how AI is moving from simple chatbots to governed, enterprise-ready agents that can work across business processes.AI agents are entering real workflows: from voice agents and coding assistants to tax, legal, customer service, and advisory use cases.Enterprises now need an agent control plane: with governance, identity, permissions, audit trails, and lifecycle management.Trust is becoming the adoption gate: as safety, observability, evals, and accountability become critical for scaling AI responsibly.The big question for this episode:Are we still talking about better AI models, or are we now entering the era of managed AI workers?You can reach @ Sesh @ Lukas @ Manjeet @ Raghu

Join Steven Walchek, Co-Founder and CEO of Liminal, for a deep dive into the "adoption paradox" facing the modern enterprise. Despite billions in AI investment, most organizations remain trapped in perpetual pilots. A serial entrepreneur with over $1.1B in exit value and a former CINO at FIS, Steven argues that the failure isn't technical—it's strategic. In this episode, we explore why forcing standardization kills impact and how the industry is shifting toward "Secure AI Enablement" that learns from actual user behavior to autonomously deploy capabilities where they matter most.

Tata Consultancy Services (TCS), a global leader in IT services, consulting and business solutions, who operate a Global Delivery Centre in Letterkenny, Co. Donegal, today announced a landmark strategic partnership with Mistral, one of world's leading AI companies. As part of this collaboration, TCS has become the first global systems integrator partner for Mistral Forge, Mistral's advanced system for enterprises to build frontier-grade AI models grounded in their proprietary enterprise knowledge and domain-specific data. The partnership combines Mistral's frontier AI capabilities with TCS' deep context of enterprise customers, domain knowledge and engineering excellence, to help organisations scale enterprise AI responsibly with greater speed. As part of this strategic collaboration, TCS will leverage Mistral Forge to build custom AI models for enterprises. It will help customers deploy their data and enterprise context to improve decision outcomes. This collaboration draws on TCS' strong global presence across North America, the United Kingdom, Europe, and Asia-Pacific to deliver AI solutions tailored to industry needs, operations and regulatory requirements. The partnership will initially focus on sectors like banking, financial services and insurance (BFSI), manufacturing, healthcare, and the public sector, where trusted AI adoption is becoming increasingly critical. TCS will also establish a dedicated Centre of Excellence for Mistral to drive joint innovation, build industry-specific solutions, support project delivery, and accelerate client value through early access to Mistral's beta models. The Centre of Excellence will serve as a strategic hub for advanced talent, focused training, and the capabilities needed to design, deploy, and govern AI solutions. Arthur Mensch, Chief Executive Officer and Co-Founder at Mistral, said, "TCS' global scale and contextual industry knowledge make them an ideal partner for Mistral. Together, we are enabling enterprises worldwide to move from experimentation to AI deployment with systems that are open, production-ready and aligned with their strategic and operational requirements." K Krithivasan, Chief Executive Officer & Managing Director at TCS said, "The partnership with Mistral reinforces TCS' commitment to scaling enterprise AI with trust, control, and measurable business outcomes at the core. This partnership expands TCS' AI ecosystem, uniquely positioning TCS to create a differentiated solution proposition for our clients. Together with Mistral, we will solve for specific industry challenges, regulatory requirements, and sovereign needs for our enterprise customers." As part of its broader Infrastructure to Intelligence AI strategy, TCS continues to invest across infrastructure, models, data, application, platforms and physical and digital intelligence. This aligns with TCS' ambition to become the world's largest AI-led technology services company, underpinned by a five-pillar strategy focused on embedding AI across the enterprise, scaling AI-led delivery capabilities, and driving measurable business outcomes for clients.

This week we have a technical segment focused on Linux! Paul released a script that helps you get a handle on Linux supply chain security, and new features allow you to assess the state of Secure Boot on your Linux systems (that also use MS certificates, ironically). The script is in his Git repo: https://github.com/pasadoorian/Linux_Hacks. In the security news: The CVE chase The new security basics Enterprises are lacking more than AI Detections are falling behind Why DOOM!?! Chromium vulnerability The ambitious Flipper One I'm still curious who was behind these leaks Mitre moves Caldera to Apache foundation Wind cybersecurity PQC updates YellowKey Bitlocker Bypass updates The software supply chain is in deep trouble Visit https://www.securityweekly.com/psw for all the latest episodes! Show Notes: https://securityweekly.com/psw-928

This week we have a technical segment focused on Linux! Paul released a script that helps you get a handle on Linux supply chain security, and new features allow you to assess the state of Secure Boot on your Linux systems (that also use MS certificates, ironically). The script is in his Git repo: https://github.com/pasadoorian/Linux_Hacks. In the security news: The CVE chase The new security basics Enterprises are lacking more than AI Detections are falling behind Why DOOM!?! Chromium vulnerability The ambitious Flipper One I'm still curious who was behind these leaks Mitre moves Caldera to Apache foundation Wind cybersecurity PQC updates YellowKey Bitlocker Bypass updates The software supply chain is in deep trouble Show Notes: https://securityweekly.com/psw-928

This week we have a technical segment focused on Linux! Paul released a script that helps you get a handle on Linux supply chain security, and new features allow you to assess the state of Secure Boot on your Linux systems (that also use MS certificates, ironically). The script is in his Git repo: https://github.com/pasadoorian/Linux_Hacks. In the security news: The CVE chase The new security basics Enterprises are lacking more than AI Detections are falling behind Why DOOM!?! Chromium vulnerability The ambitious Flipper One I'm still curious who was behind these leaks Mitre moves Caldera to Apache foundation Wind cybersecurity PQC updates YellowKey Bitlocker Bypass updates The software supply chain is in deep trouble Visit https://www.securityweekly.com/psw for all the latest episodes! Show Notes: https://securityweekly.com/psw-928

This week we have a technical segment focused on Linux! Paul released a script that helps you get a handle on Linux supply chain security, and new features allow you to assess the state of Secure Boot on your Linux systems (that also use MS certificates, ironically). The script is in his Git repo: https://github.com/pasadoorian/Linux_Hacks. In the security news: The CVE chase The new security basics Enterprises are lacking more than AI Detections are falling behind Why DOOM!?! Chromium vulnerability The ambitious Flipper One I'm still curious who was behind these leaks Mitre moves Caldera to Apache foundation Wind cybersecurity PQC updates YellowKey Bitlocker Bypass updates The software supply chain is in deep trouble Show Notes: https://securityweekly.com/psw-928

NEAR keeps showing up in strange places: cross-chain wallets, privacy apps, AI infrastructure, and now the emerging agent economy. Sal Ternullo, CEO of SVRN, joins us to explain why he thinks this is not another NEAR pivot, but the original thesis finally coming into focus. They dig into NEAR Intents, AI money, tokenomics, privacy, fee capture, agentic commerce, and why SVRN is trying to commercialize the NEAR ecosystem rather than simply hold the asset. ---

Send us Fan MailThis episode is for nonprofits searching for alternatives to traditional aid models and dependency-driven philanthropy. The conversation blends international development, nonprofit operations, sustainability, and social enterprise into a highly searchable leadership discussion.Sustainable nonprofit development in Africa requires more than donations—it requires long-term economic thinking, local leadership, and community ownership. In this Global Edition of The Nonprofit Show, Paul Smith, UK Director of MUSANA, shares how the organization is transforming rural communities in Uganda through healthcare, education, hospitality businesses, and locally driven enterprise systems designed to become financially sustainable.Rather than creating dependency on Western aid, MUSANA uses philanthropy as catalytic investment. Their model builds hospitals, schools, hotels, restaurants, and jobs that eventually generate enough local revenue to sustain operations and fund scholarships and outreach programs internally.Paul explains how MUSANA's district-based strategy has already created nearly 900 full-time jobs while building systems that communities themselves support, value, and grow. The conversation also takes an honest look at the ethical challenges facing international nonprofits, including poverty marketing, child sponsorship culture, and “white savior” dynamics that can unintentionally reinforce harmful power structures.One of the most compelling moments comes when Paul says:“No global economy has ever been built off charity. It's always enterprise, it's always industry that builds an economy.”The episode also introduces a powerful nonprofit leadership concept:“Every single charity should have an out vision.”If your nonprofit works internationally—or simply wants to build stronger, more sustainable systems locally—this conversation offers fresh thinking on what long-term impact can truly look like.  00:00:00 Introduction To MUSANA's Mission 00:02:32 Breaking Cycles Of Aid Dependency 00:05:17 Building Schools, Hospitals & Enterprises 00:07:19 How Local Revenue Funds Community Growth 00:10:30 Why Free Aid Can Create Dependency 00:11:49 Local Leadership Versus Western Control 00:14:20 The Ethics Of Poverty Tourism 00:17:48 Why MUSANA Rejects Child Sponsorship 00:19:49 When Western-Led Models Fail 00:22:20 Ego, Power & Nonprofit Leadership 00:25:23 Access, Opportunity & Economic Growth 00:27:03 Why Every Charity Needs An “Out Vision” #TheNonprofitShow #InternationalDevelopment #UgandaFind us Live daily on YouTube!Find us  Live daily on LinkedIn!Find us Live daily on X: @Nonprofit_ShowOur national co-hosts and amazing guests discuss management, money and missions of nonprofits!  12:30pm ET   11:30am CT  10:30am MT  9:30am PTSend us your ideas for Show Guests or Topics: HelpDesk@AmericanNonprofitAcademy.comVisit us on the web:The Nonprofit Show

Podcast: Tech TransformedGuest: Mihir Nanavati, GM and Product Executive in MarTech and AdTechHost: Doug Laney, Research & Advisory Fellow at BARC and Author of Infonomics & Data JuiceAI might have overtaken the industry with processing data, automating workflows, and creating content. The next big thing could be a major one, says Mihir Nanavati, GM and Product Executive in MarTech and AdTech, “AI is moving from managing data to making decisions with it.”In the recent episode of the Tech Transformed podcast, host Doug Laney, Research & Advisory Fellow at BARC and Author of Infonomics & Data Juice, sat down with Nanavati to talk about a larger transformation in data and decision-making systems driven by AI.They particularly focus on the integration of agentic AI in marketing and customer data platforms. They explore the challenges of fragmentation in ad tech, the importance of connecting customer data to revenue outcomes, and the transformative role of AI in decision-making processes. Mihir shares insights on how companies can leverage AI to enhance their marketing strategies and the future of first-party data."This is not a cost exercise, it's about how much more you can get done and how many more ideas you can execute," said Nanavati.For years, enterprises went through waves of technological change, including cloud infrastructure, mobile platforms, and customer data platforms (CDPs). Each development helped enterprises collect, store, and manage larger amounts of data. However, Nanavati asserts that humans making most decisions will never change. Now, AI agents are introducing a new model.How AI has Moved from Data Navigation to Making DecisionsIn the past, customer data initiatives aimed to create a unified view of customers. Enterprises built warehouses, ETL pipelines, and data platforms that were designed to be reliable. However, Nanavati suggests that AI agents are changing these expectations. "Machines can reason, and that is fundamentally different."Rather than simply serving as another analytical feature in existing systems, AI agents are increasingly acting as decision-makers. They weigh trade-offs, learn from results, and execute plans based on specific goals.This change has significant implications for customer data platforms. CDPs are not just repositories for customer information now. Instead, they are becoming layers that enable intelligent actions."The role of customer data platforms is evolving into ‘how do you make meaning of this?'" While, decisions about which customer segment to target, which message to send, or which offer to present may increasingly be guided by AI-driven systems.What's the Fragmentation Problem in Modern AdTechWhile AI agents create new opportunities, Nanavati pointed out a persistent issue in the AdTech and MarTech ecosystem – fragmentation. Brands today tend to lean towards deploying multiple advertising and customer engagement platforms. These include social platforms, retail media networks, email tools, and specialised ad technologies. Each system may optimise effectively within its own space, but often fails to connect at the customer level.Nanavati calls it a "paradox of choice." "Each system is optimising locally for its own clicks and conversions, but none of that is coordinated at the consumer level."The result is a customer experience that many consumers notice, alluding to repeated retargeting for products they have already bought, irrelevant recommendations, or disconnected interactions across channels.As enterprises adopt AI agents, fragmented data environments may become an even bigger problem. AI systems can process information quickly, but they still rely heavily on context. "AI doesn't need perfect data in many cases, but it needs context."What's Next for Enterprise Tech?As AI adoption continues, Nanavati believes that successful enterprises will be recognised not by how many experiments they run, but by how fast they learn and use the results."Learn very rapidly. Then scale what you've learned." For leaders, this may require a stronger commitment than just isolated pilot programs or limited rollouts. It may also need organisational changes that place AI decision-making and customer context at the centre of growth strategies.For companies navigating the intersection of AI agents, CDPs, and customer data, the question may no longer be whether AI can automate processes. The ultimate question is about who is calling the shots.Key TakeawaysAI is fundamentally changing how decisions are made in marketing.The shift from third-party to first-party data is crucial for businesses.Fragmentation in ad tech leads to a paradox of choice for brands.Connecting customer data to revenue outcomes is essential for success.AI can help marketers make better decisions without needing perfect data.Customer data platforms are evolving to support real-time decision-making.Companies can run significantly more marketing experiments with AI.Leaders must personally drive change in their Enterprises.Successful AI implementation requires a focus on revenue outcomes.First-party data collection is becoming more sophisticated and essential.Chapters00:00 Navigating the Shift in Data and AI03:03 The Evolution of Decision-Making in Marketing05:55 Challenges of Fragmentation in Ad Tech09:00 Connecting Customer Data to Revenue Outcomes11:56 The Role of AI in Customer Data Platforms14:55 Real-World Applications of Agentic AI18:05 Blueconic's Approach to Customer Growth21:14 The Future of First-Party Data24:02 Building Habits for Successful AI ImplementationListen to the full episode of Tech Transformed for a deeper discussion on AI agents, customer data platforms (CDPs), first-party data strategies and the future of AdTech. Subscribe for upcoming episodes and join the conversation across our social channels.BlueConic LinkedIn: @BlueConicEM360Tech YouTube: @enterprisemanagement360EM360Tech LinkedIn: @EM360TechEM360Tech X: @EM360TechFor more information, please visit em360tech.com and blueconic.com.

Over the last two decades, Eric Ries's ideas about continuous innovation, long-term thinking, governance, and market reform have reshaped company building and management practices. He is the creator of the Lean Startup method, and the author of the New York Times bestseller The Lean Startup; The Leader's Guide; and The Startup Way.  As a founder, he has put his own ideas into practice with The Long-Term Stock Exchange (LTSE); Answer.AI, an AI R&D lab; the Lean Startup Co, which teaches and supports the implementation of Lean Startup; Virgil, a legal services startup; and IMVU, where the ideas that became the Lean Startup method were forged. On his podcast, The Eric Ries Show, he talks to guests including world-class technologists, thought leaders, and executives working to build profitable companies for the long-term benefit of society. Eric has served as an entrepreneur-in-residence at Harvard Business School and IDEO. He lives in the San Francisco Bay Area with his wife and three children. This episode is sponsored by the coaching company of the host, Paul Zelizer. Consider a Strategy Session if you can use support growing your impact business. Resources mentioned in this episode include: Incorruptable site Miyoko Awarepreneurs interview The Lean Startup site Long Term Stock Exchange site Paul's Strategy Sessions Pitch an Awarepreneurs episode  

 Ramkumar Narayanan | EVP, Head of India and Philippines,AI technology Enablement,FIS  Ramkumar Narayanan is a global leader focusing on data driven, digital product innovation spanning consumer and enterprise markets. He brings a vast experience in product development, product management and product marketing having led both new market entry and turnaround of existing business areas. He has been an advisor to Enterprises, large and small, in the arena of digital transformation, product strategy and product marketing. Ram is currently EVP Technology & Services at FIS India and Philippines. Prior to joining FIS, he served in global leadership positions at VMware, eBay, Yahoo! and Microsoft. He started his career in the auto industry in US developing software solutions for design and packaging of automotive suspension and powertrain systems. Ram formerly served on the Executive Council of NASSCOM and was Chairperson NASSCOM Product/Deep Tech Council.Ramkumar Narayanan holds a B.E. in Mechanical Engineering from Anna University, Chennai, M.S. in Mechanical Engineering & MBA from University of Michigan, Ann Arbor.  

The number of overseas-invested enterprises in China has risen for three consecutive years, surpassing 530,000. Data from the Ministry of Commerce shows cumulative foreign direct investment has exceeded 3.6 trillion U.S. dollars.

Are your AI agents truly safe to deploy at scale? In this episode, two founders come together to tackle one of the most urgent questions for every AI startup and enterprise today: how do you build AI systems you can actually trust? Hosted by Preethy Padmanabhan and the 10x Growth Strategies community, this panel brings together Tatyana Mamut (WayFound) and Prukalpa Sankar (Atlan) - two founders redefining how enterprises govern, monitor, and scale AI responsibly. In this episode, we discuss: How supervisor/guardian agents help enterprises reach 3-nines and 5-nines reliability Real-world example: a customer service AI agent secretly offering refunds with perfect guardrails in place Why sampling logs isn't enough and why 100% monitoring is now a legal requirement How the OpenAI and Workday lawsuits are reshaping enterprise AI accountability How to architect AI-ready data systems with lineage, traceability, and explainability built in How enterprises across the US, Germany, and Australia are navigating evolving AI regulation Hybrid deterministic + AI system design for production-grade agents Whether you're an entrepreneur, a corporate executive, or a venture capital investor evaluating AI startup opportunities - this conversation on 10x growth, scaling up, and responsible AI is unmissable. 10X Growth Strategies is a community co-founded by Preethy Padmanabhan, built to bring together founders, investors, and executives for meaningful connection and growth. With thousands of members across LinkedIn, Luma, and Partiful, the community hosts monthly events on timely topics in tech, AI, and entrepreneurship. Chapters 0:00 - 3:32 - Introduction 3:32 - 7:59 - Understanding Enterprise Trust in AI 7:59 - 13:47 - Legal Challenges and Compliance in AI 13:47 - 19:00 - Architecting AI systems for Compliance 19:00 - 21:52 - Benefits of Working with this New Technology 21:25 - 25:21 - Proactive vs Reactive Compliance Strategies 25:21 - 41:35 - Audience Interactions 41:35 - 44:04 - What is your Leadership Principle? Connect:  Website: https://grow10x.podbean.com/ Luma: https://lu.ma/10xgrowthstrategies

Enterprises have agents. Most can't run them at scale. IBM's Suzanne Livingston explains what changes when you have hundreds — not two.Full Show NotesScaling agentic AI is not the same problem as building it. At IBM Think 2026 in Boston, I sat down with Suzanne Livingston, VP of Product for IBM watsonx Orchestrate, to talk about where enterprise organizations actually are on this journey — and what it takes to move from a pilot to a production environment running hundreds of agents across dozens of departments.Suzanne walks through the full watsonx portfolio, then goes deep on the challenge she hears from customers constantly: the agent worked in the demo, but now it needs to run reliably at scale, with proper governance, observable across the estate, and permissioned correctly for every user and every system it touches. That is a fundamentally different problem than building the agent in the first place. The new Orchestrate Agent Control Plane is IBM's answer to it.This episode is for enterprise technology leaders who have moved past "should we do agents" and are now asking "how do we run them well." If your organization is somewhere between first pilot and full production deployment, this conversation is the one to listen to this week.What We CoverWhy the jump from generative to agentic AI changes the operating model, not just the technologyWhat agent orchestration means in practice when you have 40 sub-agents reporting to one master agentWhat the Orchestrate Agent Control Plane does and why cross-estate visibility matters more than per-agent optimizationHow enterprises are treating AI agents like digital employees — with identities, goals, managers, and performance reviewsWhy governance isn't optional in an agentic environment and what "governance light" looks like for organizations just getting started.Guest BioSuzanne Livingston is Vice President of Product Management for IBM watsonx Orchestrate, IBM's enterprise AI orchestration platform. She leads the product team responsible for agent building, orchestration, evaluation, and the recently announced Orchestrate Agent Control Plane. Suzanne presented at IBM Think 2026 in Boston.IBM Think profile: https://www.ibm.com/think/author/suzanne-livingstonResources MentionedIBM watsonx Orchestrate 30-day free trial: https://www.ibm.com/products/watsonx-orchestrateIBM Think 2026 content: https://www.ibm.com/thinkLopez Research blog: https://www.lopezresearch.com/research/

In this Cloud Wars conversation, Bob Evans speaks with Matt Renner, Chief Revenue Officer at Google Cloud, about the explosive acceleration of enterprise AI adoption and how Google Cloud is scaling to meet it. Renner explains why customers are demanding immediate business outcomes, not experimental pilots years down the road, and shares Google Cloud's response through expanded field engineering investments, ecosystem funding, and deeper enterprise co-creation. The discussion also explores Google's differentiated AI stack strategy, the intensifying competitive landscape, and why AI security could become one of the industry's most significant next battlegrounds.Google's AI Scaling Play The Big Themes: AI Demand Has Moved Beyond Experimentation: Matt Renner makes clear that enterprise AI has entered a fundamentally different phase. Companies are no longer satisfied with proof-of-concept experimentation or exploratory pilots. Instead, executive teams want measurable business value quickly. This urgency is reshaping vendor expectations, deployment models, and customer engagement strategies. Google Cloud is seeing demand at a pace that traditional scaling models cannot satisfy, which is driving operational changes. This is not a speculative future trend, it is already happening. The $750 Million Ecosystem Expansion Multiplies Capacity: Google Cloud's $750 million ecosystem investment complements the FDE initiative by scaling partner-led implementation capacity. Renner explains that Google alone cannot meet enterprise AI demand, so partner ecosystems become force multipliers. The strategy is to expand from hundreds of specialists into thousands of technical practitioners capable of building agents, workflows, and AI-powered solutions. This reflects a practical recognition that enterprise AI requires broad execution capability, not just core platform excellence. The AI Market Reset Is Reshaping Cloud Competition: Renner describes AI as a market reset that is materially changing competitive cloud dynamics. Google Cloud's growth rates, contrasted against hyperscaler rivals, are presented as evidence that strategic positioning matters. The broader takeaway is that AI has altered enterprise buying criteria, infrastructure priorities, and vendor differentiation. Long-term investments in chips, models, data infrastructure, and platform integration are beginning to show commercial returns. Rather than incremental cloud evolution, Renner presents this as a structural shift in the market. Enterprises are reallocating attention and budgets around AI capability. The Big Quote: “We're seeing unprecedented demand for Google Cloud products infrastructure, all driven, frankly, from AI." More from Matt Renner and Google Cloud: Connect with Matt Renner on LinkedIn or learn more about Google Cloud AI. Visit Cloud Wars for more.

Join me, Jenny D. for a special edition of Spill with Me Jenny D. Meet Matt Rohm owner of LeWay Enterprises in the South Hills of Pittsburgh. Matt gave me a tour of his shop and showed me all that goes into screen printing. The people behind the scenes will amaze you! LeWay Enterprises is a family owned Pittsburgh business serving our community for over 26Years. From Custom screen printing, embroidery, team apparel and promotional products, their in-house creative design team has been helping businesses, teams, and organizations throughout Western Pennsylvania and beyond to bring brands to life. Thank you Matt for sponsoring Jenny D's Special Edition Episode with The Steelers Scouting Coordinator Casey Weidl on Wednesday May 20th. Also, a shout out to LeWay for being Jenny D's on-line store for over 4 years now! https://spill.itemorder.com/shop/sale/ To find out more about LeWay click the link below or call 412-942-0740 https://www.leway.com/ #supportlocal #supportsmallbusiness #screenprinting #embroidery #familyowned

 IBM's chief legal officer explains how governance drives AI success through trust, transparency, and employee adoption.  Enterprises are learning that employees won't use AI if they don't trust it. How can the right governance policies help companies improve AI adoption while also increasing innovation? Join Steve Odland and guest Anne Robinson, senior vice president and chief legal officer at IBM, to find out how AI trust ties directly to AI adoption, why companies need to be clear about the problems they're trying to solve, and how the public sector is grappling with AI.

Kris Lovejoy, Global Strategy Leader at Kyndryl, has spent her career at the intersection of IT infrastructure and security. Right now, she's one of the people enterprises call when they want to move from AI experimentation to real deployment. Her diagnosis is clear: agentic AI is a bullet train sitting on tracks built for 30 miles per hour. The technology is ready. Most organizations aren't, and the gap between a successful pilot and a production system running at scale is far wider than the hype suggests. In this conversation with Craig Smith, Lovejoy walks through why IT service management is the smartest entry point for agentic adoption, how cost savings of up to 90% in that area can fund broader modernization, and why the security risks in agentic systems are less about sophisticated hackers and more about misconfiguration, bad context, and human error. She closes with a specific prediction: half of traditional IT administration tasks will be handled by AI agents by 2031, and a surprising take on who will actually thrive in the agentic era: not coders, but people trained to ask the right questions. For anyone making decisions about AI adoption, this is the most practical conversation available right now. Subscribe to Eye on A.I. for weekly conversations with the people building and deploying the future of AI.

Dell's CTO built a 4-category agent framework from real production deployments. Most enterprises are ignoring two of the categories that matter most.Full Show NotesEnterprise leaders are mapping AI agents to org charts — building digital employees, agentic teams, AI workers — and then wondering why the results fall short. Dell's Global CTO John Roese has been running agents in production long enough to know exactly why that framing fails, and what to do instead.In this episode, Roese shares a framework Dell developed from actual production deployments, not pilots. It identifies four categories of AI agents defined by two dimensions: how much autonomy you grant the agent, and how complex the underlying process is. Most enterprises are focused on one category. Two of the four are widely overlooked — and they may represent the fastest path to measurable ROI.This is a practical, grounded conversation about where agents are actually delivering value today, how to think about infrastructure cost in the context of agent economics, and why the sequence in which you deploy agents matters as much as which agents you build. If your organization is trying to move from AI experimentation to production, this episode is required listening.3. Chapter titles:[00:00] — Introduction: Dell's dual role as tech vendor and enterprise AI user[01:38] — Why the org chart model for agents fails[03:12] — Decoupling human capacity from work capacity for the first time[04:23] — The two-by-two framework: autonomy vs. process complexity[06:14] — Productivity agents: what most enterprises already have[07:00] — Hygiene agents: the overlooked category that fixes foundational data problems[08:01] — The CRM data example: why every CRM is inaccurate and how agents fix it[10:05] — Latent infrastructure capacity: running agents in GPU white space to cut costs to cents[13:53] — Facilitation agents: removing entropy from complex cross-functional workflows[17:30] — The sequencing insight: hygiene and facilitation as the path to expert agents[19:24] — Why coordination agents aren't agentic bosses — and where human control actually lives[22:21] — Roese's closing advice: become literate, pick a few, get them into production4. Guest BioJohn Roese is the Global Chief Technology Officer and Chief AI Officer at Dell Technologies, where he is responsible for technology strategy, AI deployment, and research and development across the company. He has held senior technology leadership roles at Nortel, Enterasys Networks, Broadcom, and EMC. At Dell, he operates at a rare intersection: leading AI strategy for a major technology vendor while also deploying AI internally at enterprise scale — which means his frameworks are tested against real production constraints, not just market positioning.LinkedIn: linkedin.com/in/johnroeseDell Technologies: dell.comAbout This PodcastAI with Maribel Lopez is a podcast for enterprise technology leaders navigating AI adoption, agentic systems, AI infrastructure, and AI governance. Host Maribel Lopez covers enterprise technology and advises CIOs, CDOs, CMOs, and technology vendors on how to move from AI experimentation to measurable business outcomes. New episodes published bi-weekly.Subscribe on your platform of choice: buzzsprout.com/1947446

Snowflake is the AI Data Cloud behind some of the world's largest enterprises — $4.68 billion in annual revenue, 29% year-over-year growth, and over 760 Forbes Global 2000 companies as customers. Baris Gultekin, VP of AI at Snowflake, leads the product efforts that sit at the center of how those enterprises actually operationalize AI. Before Snowflake, he co-founded Google Assistant and scaled it from 10 million to 500 million monthly users.What you'll learn:Why our data isn't clean enough is a delay tactic — and the scoped approach to move past itWhat the semantic layer is and how it lets AI answer business questions accurately, not just fluentlyWhy running AI next to data (instead of sending data to models) makes governance dramatically easierHow Snowflake deployed AI internally: a CEO-level non-optional mandate combined with bottom-up access to their own Cortex coding agentWhy context — not just data — is what agents need to operate reliably at enterprise scaleKey takeaways:Start with one scoped use case, build the semantic model around it, layer governance — don't wait for perfect dataContext is a shared reality for agents: unified data + business semantics + codified workflowsAI adoption compounds when leadership sets a hard mandate and simultaneously gives everyone a tool to experiment withCredits:Host: Carlos Gonzalez de VillaumbrosiaGuest: Baris GultekinSocial Links:Find out more about Product School hereFollow our Podcast on TikTok hereFollow Product School on LinkedIn here

Welcome to Captain's Pod, a Star Trek podcast presented by Ian and Deneé! Join the crew as Ian over explains Enterprise design, Deneé forgets an episode of Captain's Pod, and they both help history never forget the name Enterprises?Next Week: Star Trek TNG: The Inner Light! (S5E25)1) Ten Forward - Thoughts on the episode; what did the crew love and what can go out the airlock! - (13:38) 2) The Jefferies Tubes- Bloopers and other goodies that didn't make it into the show. Don't tell Section 31! (1:32:43)Want to send us something the old fashioned way?P.O. Box 115Republic, MO. 65738Want early and ad-free access to the show PLUS other perks? Join the Tea-Flingers at the Ian and Deneé Patreon!https://www.patreon.com/iananddeneeConnect with us!Email: iananddenee@gmail.comDiscord: https://discord.gg/cm4nxyKd2SAnd live long and Podsper!Advertising Inquiries: https://redcircle.com/brandsPrivacy & Opt-Out: https://redcircle.com/privacy

Ryan Burke, VP of Worldwide Sales at Crogl, joins Sam Jacobs, AJ Bruno, and Asad Zaman on the new economics of enterprise cyber risk. Topics include Anthropic's Mythos model, AI for the security operations center, why vibe-coded apps are far more likely to have security issues, why Claude Design tanked Figma's stock, and what the Elon Musk versus OpenAI lawsuit signals for AI governance. Key takeaways: AI has crashed the cost of running sophisticated attacks, putting nation-state-grade tooling in the hands of low-skill operators. As Ryan Burke, VP of Worldwide Sales at Crogl, put it on Anthropic's Mythos model: "Mythos has lowered the cost to like the dollar menu equivalent of...running an attack...so more people can do it." Enterprises are staring down a multi-year patching backlog that runs from now until the end of time. Non-technical teams in finance, ops, and HR are shipping internal tools using Replit and Claude, and almost none of them are securing what they build. Ryan Burke flagged the research: "vibe-coded software is almost 3 times as likely to have security issues." When the employee who built the agent quits, the agent stays behind with no owner, no documentation, and quiet access to systems it never should have had in the first place. For founders eyeing an exit, security has joined revenue, IP, and hitting your numbers as a non-negotiable diligence pillar. As Ryan Burke explained: "lack of security can kill an acquisition...a fourth pillar now is you're secure." Acquirers like JPMorgan Chase will not buy a fintech startup that turns into a vector for attackers to walk straight into their environment. The market case for NRR-fortress legacy SaaS may be weaker than the last decade made it look. As Asad Zaman, CEO of Sales Talent Agency, argued: "there was a generation of software companies that had signs that they had really good customer relationships...but their customers felt more like prisoners." If AI makes switching cheap and a new generation of software actually delights users, the moats around system-of-record incumbents start to compress fast. Connect with the hosts and guest:  Host: Sam Jacobs, CEO at Pavilion - https://www.linkedin.com/in/samfjacobs/  Host: AJ Bruno, CEO at QuotaPath - https://www.linkedin.com/in/ajbruno3/  Host: Asad Zaman, CEO at Sales Talent Agency - https://www.linkedin.com/in/azaman1/  Guest: Ryan Burke, VP Worldwide Sales at Crogl - https://www.linkedin.com/in/ryan-burke-bos/ Topline is more than a YouTube Channel:  Subscribe to Topline Newsletter: https://toplinemedia.substack.com/  Tune into Topline Podcast, the #1 podcast for founders, operators, and investors in B2B tech: https://www.joinpavilion.com/topline-podcast  Join the free Topline Slack channel to connect with 600+ revenue leaders to keep the conversation going beyond the podcast: https://www.joinpavilion.com/topline-slack Chapters:  00:00 Introducing Ryan Burke 03:14 Anthropic Mythos and Cyber Risk 04:20 How Attackers Use AI at Scale  07:00 Dollar Menu Attacks Explained  10:41 AI for the Security Ops Center  14:53 Why Claude Tanks Figma's Stock  18:30 Sam's Advice on Falling Stocks  20:50 Are Legacy SaaS Companies Back?  24:04 The Vibe-Coding Risk Surface  27:56 Quiz Pro: Cybersecurity Edition  33:46 Replit Apps Inside Enterprises  40:18 Security as the M&A Fourth Pillar  44:17 Personal Data and Digital Legacy  47:24 Bulls vs Bears: Elon vs OpenAI  52:03 Will ServiceNow Hit $32B?

The AI discount is ending as agentic usage drives token consumption through the roof, forcing companies from GitHub to Anthropic to rethink pricing, limits, and compute access. NLW breaks down why usage-based billing is becoming inevitable, what it means for markets and job displacement, and how enterprises can adapt with cheaper models, cost audits, model bake-offs, escape-hatch architectures, and clearer AI cost scoreboards.5 Moves for Enterprises to Reduce the Cost of Agents: https://play.aidailybrief.ai/episodes/the-ai-subsidy-era-ends/April AI Usage Pulse Survey: https://tally.so/r/LZEyGySIGN UP FOR OUR NEW FREE PROGRAM: AGENTOS⁠⁠https://aidbagentos.ai/⁠⁠Brought to you by:KPMG – Agentic AI is powering a potential $3 trillion productivity shift, and KPMG's new paper, Agentic AI Untangled, gives leaders a clear framework to decide whether to build, buy, or borrow—download it at ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠www.kpmg.us/Navigate⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Granola - The AI notepad for people in back-to-back meetings. 100% off your first 3 months with code AIDAILY at ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠http://granola.ai/aidaily⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Mercury - Modern banking for business and now personal accounts. Learn more at ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://mercury.com/personal-banking⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Zenflow Work - Agents for knowledge work - ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://zenflow.free/⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Drata - The agentic trust management platform - ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://drata.com/⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Blitzy - Want to accelerate enterprise software development velocity by 5x? ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://blitzy.com/⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠AssemblyAI - The best way to build Voice AI apps - ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://www.assemblyai.com/brief⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Robots & Pencils - Cloud-native AI solutions that power results ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://robotsandpencils.com/⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠The Agent Readiness Audit from Superintelligent - Go to ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://besuper.ai/ ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠to request your company's agent readiness score.The AI Daily Brief helps you understand the most important news and discussions in AI. Subscribe to the podcast version of The AI Daily Brief wherever you listen: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://pod.link/1680633614⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Our Newsletter is BACK: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://aidailybrief.beehiiv.com/⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Interested in sponsoring the show? sponsors@aidailybrief.ai