Cloud Wars Live with Bob Evans

In today's Cloud Wars Minute, I examine how AI demand is reshaping rivalries between Google Cloud, AWS, NVIDIA, and Anthropic. Highlights 00:03 — According to reports, Anthropic has committed to a $200 billion five-year agreement for Google Cloud services and Google-designed chips, a deal that could account for more than 40% of Google Cloud's revenue backlog. 00:18 — This represents yet another escalation in the rapidly expanding partnership between Google Cloud's parent company, Alphabet, and Anthropic, following Alphabet's previously announced $40 billion investment into the company. 00:49 — The company also holds considerable infrastructure deals with providers, including AWS and NVIDIA, and what this deal underscores is the extraordinary scale of demand for AI services. The need for compute capacity has grown so large that even a $200 billion agreement may not be enough to meet future requirements. 01:33 — However, companies like Google Cloud, with the infrastructure required to support hyperscale AI development, are positioned at the very center of this massive transformation. Visit Cloud Wars for more.

In today's Cloud Wars Minute, I look at how Google Cloud is pairing technical innovation with go-to-market execution to fuel AI growth. Highlights 00:00 — One of the fastest-growing companies in the Cloud Wars Top 10 is Google Cloud, and it has just launched a program of Forward Deployed Engineers (FDEs), specializing in AI to help accelerate AI transformation at the point of the customer. 00:46 — I had a chance to speak about this new AI FDE program with Matt Renner, President and Chief Revenue Officer at Google Cloud, and he was talking about how this brings the innovation out at the point of the customer, the unique challenges customers are facing right now. 01:38 — It isn't Google Cloud's attempt to get into the services business so much as this is what the demand is from customers now: they need to get their AI capabilities up to speed as quickly as possible to become the AI-powered type of company they're going to need to be. 02:25 — Google Cloud, as I've mentioned before, has always been an on-the-front-edge technological innovator, but over the past couple of years, it's been bringing its go-to-market capabilities and go-to-market innovation up. 03:36 — These efforts are going to be ways to help ensure that customers have the support, the resources, the expertise from Google Cloud and the ecosystem to be able to evolve, innovate, and succeed more rapidly than ever before. Visit Cloud Wars for more.

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.

In today's Cloud Wars Minute, I connect SAP, Palantir, and Ford to AI's expanding economic disruption. Highlights 00:11 — Recently, both SAP, number four on the Cloud Wars Top 10, and Palantir, number five on the Cloud Wars Top 10, have asked: Are we reaching the end of the term software or software company? 00:47 — But I think their idea is that, what we've thought of as software, what we've come to picture it to be, the image we have in our head, the mindset we have around software, is just getting blown away by what AI is capable of. 01:07 — Last week at the SAP Sapphire event, CEO Christian Klein said, “Will SAP be a software company in the future?” He asked the SAP Joule AI Assistant to answer the question, and Joule said, “SAP is going to be a business AI company.” 02:00 — Palantir CEO Alex Karp said, “You can't just lump what we're doing into the term software.” He said, “We're going to have to create a new term, because what we're doing goes beyond software,” and suggested the term AI infrastructure. 04:07 — Ford had built an enormous factory to build electric vehicle batteries, but now is considering shifting toward batteries for AI data centers, showing how AI's impact is extending beyond tech into the broader global economy. Visit Cloud Wars for more.

In today's Cloud Wars Minute, I unpack SAP CTO Philipp Herzig's perspective on AI, APIs, and the company's next era beyond traditional software. Highlights 00:01 — As part of our ongoing analysis of the massive changes that SAP rolled out this past week at their Sapphire event in Orlando, I had an interesting one-on-one conversation with SAP Chief Technology Officer Philipp Herzig, where he discussed a range of things. Particularly this notion of how, as SAP begins to move beyond applications into the realm of AI, what that means across everything from their new Business AI platform [to] updates to their API policy.   00:37 — I think some people got their knickers in a knot unnecessarily over those API changes and the general pace of innovation that not only SAP is cranking out, but that customers are working very hard to consume so that those customers can become leaders in their industries. 01:24 — How does this shape the company that SAP is becoming in the future? And even as talked about with CEO Christian Klein posing the question during his keynote, will SAP be a software company in the future? 02:07 — One of the things that Herzig said was, we've got so many more people using more and more of our APIs, agents are going to access data from all across the company, and certain things just have to be tightened up. One of the biggest things [SAP] did, was try to ensure that there's more security. 03:20 — So, lively discussion here. I think this was a momentous event for SAP, the things they introduced, the way they're talking about going to market, the new sorts of expertise they're putting in. Philipp touches on a lot of this and gives a good insight into the foundational technology layer. Visit Cloud Wars for more.

Bob Evans speaks with SAP CTO Philipp Herzig from SAP Sapphire in Orlando about SAP's AI strategy, platform evolution, customer modernization challenges, governance, and enterprise-scale agent deployment. Herzig lays out SAP's positioning around openness, business AI, autonomous agents, security, and migration support, while addressing confusion around API policy changes and fair-use limits. SAP's AI Inflection Point The Big Themes: SAP's AI Platform Is Becoming Cohesive: A major theme in the conversation is that SAP is presenting a more integrated AI vision rather than a collection of disconnected announcements. Herzig describes a layered architecture spanning UX, autonomous assistants, business process orchestration, governance, and the underlying AI platform. The emphasis is on a consistent enterprise AI framework rather than isolated tools. Migration Support Is Becoming Strategic: Migration is no longer framed as a technical back-office concern. Instead, it's becoming a strategic AI enabler. Herzig discusses SAP's toolchain investments, including LeanIX, Signavio, migration automation, testing support, code modernization, and agent-assisted implementation. The idea is to reduce friction in modernization so customers can reach AI readiness faster. Instead of treating migration as merely an ERP upgrade journey, SAP increasingly positions it as foundational infrastructure for enterprise AI transformation. Change Management Extends Beyond Technology: Herzig acknowledges that deploying AI agents is not simply a software problem, it's an organizational transformation issue. While SAP can accelerate technical deployment through tooling, governance, observability, and automation, customers must still rethink workflows, roles, and operating models. The discussion around developer productivity, AI-assisted coding, and human-agent collaboration reinforces this broader perspective. The Big Quote: ““There are good agents out there… there's also a lot of really bad agents out there… and they, of course, set the enterprise system under risk.” More from SAP and Philipp Herzig: Connect with Philipp Herzig on Linkedin or learn about SAP Sapphire. Visit Cloud Wars for more.

In today's Cloud Wars Minute, I explore how SAP's AI Revolution could redefine enterprise software through agents, data, and industry-specific intelligence. Highlights 00:03 — We are reporting here from the Sapphire show floor in Orlando. It's been a wild week here, and I had a great chance to talk with SAP Chief Operating Officer, Sebastian Steinhäuser about some of the changes that are going on there inside what I call SAP's AI Revolution. 00:21 — Covering everything from what it's doing with agents, how it's redefining their apps, how it's building up its Data Platform, and more. Sebastian offers some great insights into all of that, and we talked about it in a full-length video linked to down below. 01:13 — (Sebastian offers insights about) the rise of data within SAP becoming the foundation for everything, the Business Data Cloud moving into a very powerful area, the Business AI Platform now consolidating some different sort of platforms and technologies that SAP had so that customers can gain more from that more quickly. 02:00 — SAP sees the world, and Sebastian describes this, where there's going to be tens, hundreds of thousands of agents, perhaps millions, you know, a few years out. And certainly SAP is not going to build all of those. So it's going to be the partners that do this. 03:09 — SAP is more focused than ever before on delivering not just code (that happens to be what they make) but what SAP's real focus is: delivering superb business outcomes for customers. Visit Cloud Wars for more.

At SAP Sapphire in Orlando, Bob Evans sat down with Sebastian Steinhäuser to discuss what may be one of the most consequential strategic shifts in SAP's history. As enterprise AI moves from experimentation to execution, Steinhäuser outlines SAP's vision for the autonomous enterprise: where AI agents, assistants, business data, and deep industry expertise come together to solve real operational problems. AI with Industry Depth The Big Themes: Customers Want Outcomes, Not AI Demos: A recurring theme in the conversation is that enterprise leaders are not buying AI for novelty. They want measurable business outcomes. Customers are focused on solving hard operational problems such as improving supply chain resilience, winning in retail execution, streamlining regulated manufacturing, and modernizing enterprise workflows. This reflects a broader evolution in enterprise buying behavior. The AI conversation has moved beyond experimentation into operational accountability. The Autonomous Enterprise Is SAP's North Star: SAP's central narrative at Sapphire is the autonomous enterprise. Steinhäuser describes a future where AI agents and human workers collaborate, with AI taking responsibility for repetitive, process-heavy, and data-intensive tasks while employees focus on higher-value decision-making. This is more than a product launch — it is SAP's strategic framework for the next phase of enterprise software. The company references hundreds of AI agents and dozens of assistants spanning functional domains. Importantly, SAP is positioning these capabilities as practical rather than speculative. Ecosystem Scale Will Determine Execution: SAP clearly sees its partner ecosystem as critical to AI transformation at scale. Steinhäuser points to thousands of ecosystem participants at Sapphire and outlines investments designed to accelerate migration, implementation, and AI activation. This reflects enterprise reality: large organizations rarely transform through software vendors alone. Systems integrators, consulting firms, implementation specialists, and migration partners often determine whether transformation succeeds. The Big Quote: “Building the technology is one thing. Really changing processes, people, and systems to adapt AI, it's a totally different one." More from SAP: Learn more about Sapphire and about Joule Assistants. Visit Cloud Wars for more.

In today's Cloud Wars Minute, I examine why OpenAI bringing frontier models to AWS signals a new era of AI platform pragmatism. Highlights 00:03 — Hot on the heels of the news that OpenAI and Microsoft have re-explored the terms of their partnership, leading to a much more flexible outcome for OpenAI, the company has introduced an expanded partnership with AWS to bring OpenAI's latest models to Amazon Bedrock. 00:23 — The new solutions currently in preview include the launch of Codex on Amazon Bedrock and Amazon Bedrock managed agents powered by OpenAI. Now AWS customers will be able to leverage the latest OpenAI models through their existing Amazon Bedrock APIs and controls. 00:46 — Customers will be able to utilize OpenAI's coding agents to scale software development on Bedrock. And with Amazon Bedrock managed agents powered by OpenAI, teams can build and deploy production-ready OpenAI-powered agents on AWS, benefiting from the global infrastructure and security AWS provides. 01:06 — At the heart of this expanded partnership, particularly in terms of messaging from AWS, is the delivery of frontier AI to the infrastructure millions of organizations already trust, and this is one of the cornerstones we're seeing now in the AI Revolution in terms of partnerships. 01:39 — Companies are focusing on their strengths, which is crucial for the parts of the business that customers rely on and that really define them in the eyes of their users. Ultimately, it's the customers who will benefit from these collaborations moving forward. Visit Cloud Wars for more.

Highlights 00:28 — Over the past couple of years, SAP has been the growth leader in applications, growing anywhere from 50% to 250% faster than some of its major competitors. 00:41 — The company has undergone a shift to consumption pricing. This is something that will be phased in over the next couple of years. CEO Christian Klein says it reflects the way that people are using AI and the value they're getting out of the product. 01:12 — SAP is developing tighter relationships with AI innovators. An interesting one is Palantir, which is now billing itself as an AI infrastructure company, serving as the software foundation enabling AI to do its best work. 02:00 — There are three recent notable acquisitions: Reltio for Master Data Management Dremio for more SAP and non-SAP data pulled together Polar Labs to help SAP move forward with structured data 02:52 — Evidently, SAP is trying to capitalize on what's happening with the AI revolution and the new capabilities that come with it. I think that Klein's leadership, focus, and willingness to take ambitious moves with acquisitions and strategic partnerships will be force multipliers in the market. 03:47 — Forward-deployed engineers will be a big part of SAP's new AI alignment with customers, to help those customers rapidly develop and deploy AI agents and applications. Visit Cloud Wars for more.

In today's Cloud Wars Minute, I unpack why Workday customers are demanding AI agents and agentic capabilities. Highlights 00:03 — I had a chance to speak with Workday co-founder, then CEO, then chairman, now back as CEO, Aneel Bhusri. And absolutely, Aneel, I would say, is back as CEO. He is unplugged in this conversation and definitely fired up about Workday's prospects, and the sort of reimagination of the company as an AI-first, AI-powered, agentic powerhouse moving into the future here. 01:27 — He said none of them is talking about vibe coding applications. He said the enterprise apps are here, but he said "it's our job at Workday to ensure that they are reinvigorated and kept as modern as possible, with as much AI and agentic capability as possible." 02:29 — He also said, “We've got to take on a startup culture, startup mentality, a startup mindset that lets us continually experiment, push new things out, and not get stuck in doing things a certain way.” 02:58 — The opportunity now that customers see is for the right sort of agentic AI to come in to enhance what the applications are already doing, to help these companies move faster, get better insights, allow people to be able to move up to higher-value work. Visit Cloud Wars for more.

In this Cloud Wars conversation, Bob Evans sits down with Workday Co-Founder and CEO Aneel Bhusri for a candid discussion about AI's disruptive impact on enterprise software, the future of agentic workflows, and why Bhusri returned to the CEO role during one of tech's most consequential transitions. The conversation explores whether AI will replace software or labor, why systems of record remain strategically vital, and how enterprise leaders should think about governance, security, and business transformation as intelligent agents begin reshaping the operating model of modern organizations. AI Changes Enterprise Work The Big Themes: AI Replaces Labor, Not Software: One of the most provocative points in the conversation is Bhusri's assertion that AI is not currently replacing enterprise software, it's replacing labor. That distinction changes everything. Rather than displacing systems like HR, finance, or ERP, AI is being layered on top of those systems to automate work previously performed by people. Bhusri sees this as both a business opportunity and a societal concern. Systems of Record Still Matter: Despite “SaaSpocalypse” chatter, Bhusri argues strongly that systems of record remain deeply entrenched. Customers are not planning to rip out core HR or ERP systems and replace them with loosely connected AI tools. Instead, the competitive battle shifts to what gets built on top of those platforms. That's a major strategic advantage for incumbents with trusted enterprise infrastructure, data models, and governance frameworks. Bhusri groups Workday alongside SAP, Oracle, and Salesforce as vendors with durable strategic relevance. AI's Social Impact Is the Bigger Story: The most human part of the discussion comes at the end, when Bhusri expresses genuine concern about AI-driven job displacement. Unlike past automation waves focused on repetitive tasks, he worries this generation affects reasoning and knowledge work. Yet he remains optimistic that technology ultimately improves society. Still, he insists enterprise leaders must become part of the solution, not simply profit from disruption. The Big Quote: “Great tech companies aren't built on one generation of technology.” More from Aneel Bhusri and Workday: Learn more about Workday and AI Connect and Workday Agent System of Record. Visit Cloud Wars for more.

In today's Cloud Wars Minute, I explore how Workday and Achievers are using AI-driven behavioral intelligence to transform employee recognition and workforce engagement. Highlights 00:03 — Workday has made Workday Recognition provided by Achievers, available to its customers. This offering has been developed alongside Achievers, the world's leading employee recognition and reward software, integrating its features into the Workday experience. The new offering leverages AI to make it easier for HR teams to evaluate performance drivers. 00:29 — The integration enables employees to recognize their peers and redeem rewards directly within Workday, while streamlining these processes for HR within Workday Human Capital Management, or HCM. This integration provides HR teams with insights into in-demand skills and creates a broader picture of performance. 00:55 — Ben Carter, Senior Vice President, Total Rewards at Workday, explained, “Recognition fuels engagement, and engagement drives productivity, making it one of the clearest indicators of a thriving workforce. By bringing Achievers into Workday, we are helping customers amplify those everyday moments of appreciation and turn them into actionable insights..." 01:22 — By embedding Achievers directly into Workday HCM, Workday is showcasing a significant use case for enterprise AI. That's behavioral intelligence. This really, to me, represents a shift away from automation and instead leverages AI's ability to provide insights at a human level. 01:45 — Businesses are pursuing tools that can offer them a competitive advantage, especially in a landscape where many are targeting similar goals and deploying the same strategies and tools to achieve them. I believe tools like this, which focus on behaviors and reward performance as a result, will undoubtedly become powerful assets in the competitive business arsenal. Visit Cloud Wars for more.

In today's Cloud Wars Minute, I look at how Palantir's soaring growth reflects rising demand for disciplined, outcome-driven AI platforms. Highlights 00:03 — For the past several quarters, the fastest-growing company in the Cloud Wars Top 10 has been Palantir. It upheld that mark in Q1, and what I wanted to talk about today was their combination of extraordinary growth and also the rise from Palantir of a couple new terms to describe what's going on in AI right now. 00:30 — Palantir believes it's been successful because it is offering real solutions when other tech vendors — many other tech vendors, it says — are offering only incomplete portions of it. Total revenue was up 85% to $1.63 billion. If you take the U.S., which is both commercial and government or defense business, it's up 104% to $1.28 billion. 01:31 — Palantir has blown past its guidance in each of the last several quarters. Its big point about AI slop is that customers are wasting time and money with incomplete AI solutions that don't offer enough precision, enough rigor, enough discipline, so that every move that agents are making can be tracked with great specificity about cost, security, and ROI. 02:30 — Alexander Karp says there's a new category here that he thinks is more befitting of what Palantir does: AI infrastructure. These results are remarkable because it shows that what it is that Palantir is putting together, customers are loving. It's passed now 1,000 customers, and its customers are rapidly increasing the spending they're doing with them. 03:24 — Karp says business leaders have to start thinking differently about what they want out of AI and what a high-quality AI vendor is going to deliver for them. Palantir has been around for 23 years, and despite seeming like a startup company, it continues pushing forward on customer expectations and the value it's imparting to customers. Visit Cloud Wars for more.

In today's Cloud Wars Minute, I unpack how flexibility and competition are reshaping the AI ecosystem. Highlights 00:08 — One of the most important tech partnerships in the past decade has undergone a radical shake-up. I'm talking about Microsoft and OpenAI, the two companies have revealed new terms for their partnership agreement in a joint statement. 00:38 — "Today, we are announcing an amended agreement to simplify our partnership and the way we work together, grounded in flexibility, certainty, and a focus on delivering the benefits of AI broadly. This new agreement frees both companies up to pursue opportunities independently while maintaining a relationship." 00:59 — There is an endpoint for the length of time that Microsoft has rights to OpenAI's model. OpenAI is going to benefit massively from wider partner opportunities, but still, there are additional benefits for Microsoft as well. 01:17 — Microsoft will remain OpenAI's primary cloud partner, with products shipping first on Azure. However, OpenAI can now serve all its products to customers across any cloud provider. Microsoft will continue to have a non-exclusive license to OpenAI IP until 2032. 01:54 — Despite the significant alterations, Microsoft will continue to participate directly in OpenAI's growth as a major shareholder. Microsoft will benefit by not having to allocate so many resources, allowing it to focus on areas that align with its evolving business goals. Visit Cloud Wars for more.

At Google Cloud Next in Las Vegas, Cloud Wars Founder Bob Evans sat down with Managing Director for Internal Innovation, KPMG, Aaron Purcell to discuss how KPMG is accelerating AI transformation with Google Cloud. As both a customer and partner of Google Cloud, KPMG offers a unique “client zero” perspective, using Gemini and Vertex AI internally while helping clients do the same. Purcell explains why Google's full-stack AI platform stood out, how governance and speed can coexist, and why employee familiarity with consumer AI tools is changing enterprise adoption faster than ever before. KPMG's AI Playbook The Big Themes: Why Google Won: KPMG evaluated multiple AI providers, but Google Cloud stood apart because it offered what Aaron Purcell called the “full stack.” Instead of piecing together separate providers for models, infrastructure, and agent development, Google delivered an integrated platform that included model creation, cloud services, infrastructure, and a mature agent-building platform through Vertex AI. That end-to-end capability gave KPMG confidence that execution would be faster and more scalable. Consumer AI Accelerates Enterprise Adoption: One of the biggest accelerators for enterprise AI adoption is that employees are already using similar tools at home. Purcell noted that many people already have experience with Google products in their personal lives, making workplace adoption much easier. Tools like NotebookLM and Gemini Enterprise feel intuitive because users recognize the patterns and workflows from consumer applications. Instead of learning entirely new systems, employees translate familiar habits into the workplace. This reduces resistance, shortens training time, and improves confidence. Keeping Up With Vertical Innovation: Purcell said the pace of AI innovation is no longer a hockey stick. It feels like a vertical line. New capabilities are arriving so quickly that organizations need systems to keep employees informed without overwhelming them. KPMG uses Gemini Enterprise itself as a communication platform, with announcement sections highlighting new features and important updates. They also run office hours, user sessions, and collaborative education efforts to keep professionals current. The Big Quote: “We're providing the general user with the ability to create their own agents for personal productivity.” More from Google Cloud and KPMG: Learn more about Google Cloud and KPMG and Google Cloud's alliance. Visit Cloud Wars for more.

In today's Cloud Wars Minute, I compare AWS's impressive quarter with the even faster momentum of its competitors. Highlights 00:01 — Wanted to talk today a little bit about the Q1 that AWS just had. I think they revealed an awesome acceleration in Q1, but in a competitive sense, it's still falling behind competitors like Google Cloud, Microsoft, and Oracle. 00:36 — After three years, our AI run rate now for AWS is $20 billion, compared to $58 million for cloud in its early years. Jassy emphasized how aggressively AWS is pushing into AI and highlighted four key reasons behind this acceleration. 02:05 — AWS revenue grew 28% to $37.6 billion, its highest growth in 15 years. However, Google Cloud is growing at 63%, Microsoft at 29%, and Oracle at 44%, with all three showing stronger backlog growth. 02:55 — A couple things can be true at the same time. AWS had a strong quarter and happy customers, but on a competitive basis, it ranks last in growth rate, backlog size, and backlog growth among hyperscalers. 03:52 — AWS remains strong in a massive market with many customers, but compared to competitors, it has the smallest and slowest-growing backlog. Those are the facts on the ground today in the cloud market. Visit Cloud Wars for more.

In today's Cloud Wars Minute, I break down how hyperscalers reached a staggering $2 trillion backlog and what it means for the future of AI infrastructure. Highlights 00:03 — The hyperscaler market (the four big companies that are helping to shape the world with the power of AI), their backlog has now hit $2 trillion. So not just their recent revenue, talking about future commitments, contracted business not yet recognized as revenue: $2 trillion. Talk about some responsibility. 01:21 — So you see Microsoft's backlog almost doubled: $627 billion. Oracle's up a whopping 325% to $553 billion. We've got Google Cloud with a huge jump, 93%, $462 billion, and AWS, very nice number, but relative to the others it is not quite up to snuff at 49%, $364 billion. 02:25 — So I think AWS is doing a good job; it's just its competitors are doing a better job — higher growth. All in all, this rolls up to more proof: this is the cloud AI market, the greatest growth market the world has ever known. 02:52 — Google Cloud, on its revenue side, 63% growth, and then by far its fastest growth backlog number here, 93%. This is a red-hot company, not just for the last few months — this backlog shows a huge number coming forward. 03:39 — This is a fantastic time to be a customer in this business because you've got unbelievable demand. The competition from these companies is showing they've got to continue to innovate as rapidly as possible and give their customers more choice. Visit Cloud Wars for more.

In this episode of the AI Agent & Copilot Podcast, Cloud Wars Founder Bob Evans, is joined by James Lennox, Director of Product, Microsoft, who shares his perspective on AI transformation, enterprise adoption, and the evolving human-AI relationship. Recorded live at the 2026 AI Agent & Copilot Summit NA, Lennox explores how tools like Copilot and Work IQ are reshaping productivity, governance, and innovation across industries. Key Takeaways Delegation is the New Productivity Model: Lennox underscores a fundamental shift: “I can delegate those long-running tasks to AI.” This evolution allows humans to move away from repetitive execution and focus on strategic, creative, and decision-driven work. With platforms like Work IQ acting as the “brain behind Copilot,” organizations gain end-to-end visibility into business processes. This changes not just efficiency, but the very nature of work — humans become orchestrators rather than operators, dramatically increasing output and impact across roles. Governance is the Gateway to Scale: One of the biggest blockers to AI adoption isn't capability, it's control. Lennox notes organizations ask: “How do I have the governance and oversight to roll this out at scale?” Tools like Microsoft Agent 365 aim to solve this with “full observability, full control, full security.” Without trust frameworks, AI remains experimental. With them, it becomes operational. This highlights that enterprise AI success depends as much on infrastructure and policy as it does on innovation. AI is Universally Applicable Across Industries: Lennox observed leaders from diverse sectors, manufacturing, healthcare, and food services, all exploring AI adoption. “There is so much broad applicability…to real business process automation.” This reinforces that AI is not industry-specific but function-specific. Whether it's document processing or supply chain optimization, AI can integrate into virtually any workflow, making it a universal transformation layer rather than a niche tool. Visit Cloud Wars for more.

In today's Cloud Wars Minute, I analyze the shifting balance of power between Google Cloud and AWS. Highlights 00:03 — Last week, we had three of the four hyperscalers report their Q1 numbers. It's been fascinating to look at those. While everybody did very, very well, Google Cloud just had an utterly exceptional, spectacular Q1, and I think the evidence of what we see in these comparative numbers shows why Google Cloud has risen to number one. 00:51 — If we compare side by side, Google Cloud and AWS in Q1 on the growth rate, their revenue, their backlog growth, and the backlog numbers — the growth: 63% to 28%. Now we will certainly hear from a lot of the AWS fanboys that that's just because there's a discrepancy in size. That's true, but it does not cover this discrepancy in growth rate. 01:35 — For Google Cloud, the backlog grew 93% to $462 billion. For AWS, the backlog grew 49% to $364 billion. Really impressive numbers here from AWS, but they play in a market with some other pretty good companies as well. Google Cloud shows 93% backlog growth versus 49%, and $100 billion bigger in backlog total versus AWS. 02:31 — AWS in Q1 had 85% more revenue than Google Cloud. Then how do you explain this backlog discrepancy? It shows that going forward, which is what the backlog shows us, future trends of business, Google Cloud is winning much more business in the future. Google Cloud is winning more new business, and that's where the game is being played. 03:25 — So clearly, the whole AI boom had a huge impact on these numbers. We saw Microsoft, just to toss this in, Microsoft's growth rate was 29% in Q1, its fiscal Q3, and its RPO, which is its version of backlog, was up, it said, 99% to$ 627 billion. Oracle, its RPO was up 325% to over $550 billion. So, it's just an incredible market here right now. 04:05 — For a long time, AWS has conditioned the market to say AWS is the king of the cloud and it will be forever. That's just not true anymore. Google Cloud, through innovation and jumping into the AI game early and aggressively, is booming right now, and its core cloud business is doing very well. Visit Cloud Wars for more.

At Google Cloud Next in Las Vegas, Bob Evans sat down with Karen Dahut, CEO of Google Public Sector, to discuss how AI, security, and open cloud strategies are reshaping government services. Dahut shared how Google Public Sector was built on the belief that government agencies deserve the same advanced commercial technologies as private enterprises, and why that decision is now proving critical in the era of agentic AI. AI Reinvents Government The Big Themes: Commercial Cloud for Government: Karen Dahut explained that when Thomas Kurian became CEO of Google Cloud in 2019, he challenged the outdated assumption that public sector organizations should receive different or lesser technology than private enterprises. Instead of building a separate, restricted GovCloud environment, Google chose to accredit its full commercial cloud for government use. This gave agencies access to the same scalability, resiliency, and innovation cycles as Fortune 100 companies. That decision is especially important now because AI workloads demand enormous scale. Leadership Makes AI Real: Technology alone does not create transformation — leadership does. Dahut highlighted examples from the FDA, Department of Transportation, and the City of Los Angeles, where visionary leaders are actively driving AI adoption rather than waiting for change to happen. These executives are not simply buying software; they are rethinking how agencies operate, from transportation systems to drug discovery to citizen services. Dahut stressed that real AI success requires courage, education, and enablement alongside strong technology. Open Cloud Is Responsible Government: Dahut strongly argued that openness is not optional in public sector technology, it is the only responsible approach. Governments operate with decades of legacy systems, massive backlogs of information, and multimodal data spread across many environments. Forcing all of that data into one cloud platform would be expensive, slow, and ultimately harmful. Google's approach is to leave the data where it already exists and analyze it there, avoiding costly ingress and egress fees and preventing vendor lock-in. The Big Quote: “AI and agentic AI is truly going to be one of those technologies that we look back on 10, 15 years from now and say that was truly the most transformational piece of technology since the transistor.” More from Karen Dahut and Google Cloud: Connect with Karen on LinkedIn or learn more about Google Cloud Public Sector. Visit Cloud Wars for more.

In this special episode of Cloud Wars Live, Bob Evans sits down with Steve Miranda, Executive Vice President of Applications Development at Oracle, from Oracle Park in San Francisco to discuss one of the biggest shifts happening in enterprise technology: agentic AI applications. Miranda explains how Oracle is moving beyond embedded AI and AI agents to fully agentic applications that can act on business objectives rather than just automate transactions. From finance and supply chain to HR and customer service, he shares how this transformation is changing operations, competitiveness, employee roles, and the very mindset organizations need to succeed in the AI Era. Rise of Agentic Apps The Big Themes: From AI Features to Agentic Applications: Steve Miranda explains that Oracle's AI journey has evolved in three major stages. First, Oracle embedded AI directly into applications to help generate and enhance content, improving the traditional user experience. Next came AI agents — workflow-driven systems capable of handling transaction sequences across ERP, HCM, supply chain, and CX. Now Oracle is introducing agentic applications, which represent a full redesign of enterprise software. These systems allow users to set business objectives rather than manually manage transactions. Instead of handling purchase orders, invoices, or approvals individually, users provide strategic guidance while AI agents execute, monitor, and optimize outcomes. Competitive Advantage Comes from Speed: Miranda stresses that agentic AI is not only about reducing costs through automation — it is about increasing business speed and adaptability. In competitive markets, companies need to react instantly to supply chain disruptions, shifting cash positions, pricing opportunities, and customer demands. Human-driven workflows create delays, while agentic applications can monitor both internal operations and external market conditions in real time. AI can identify early payment discounts, detect supply chain disruptions, or recommend immediate operational adjustments faster than traditional teams. This responsiveness creates a major competitive edge. Companies that adopt agentic applications can operate faster and more efficiently, while those that delay risk falling behind competitors who are able to move at machine speed Oracle's Pricing Philosophy Supports Adoption: Miranda explains that Oracle's pricing philosophy for AI remains intentionally customer-friendly. Core AI improvements — including embedded AI and standard agentic capabilities — are included within existing application subscriptions. Customers subscribing to financials, HCM, supply chain, or other Fusion applications receive these enhancements as part of the normal service evolution, much like database upgrades. Additional charges apply only when customers extend applications further, such as building custom agents or adding specialized workflows through Agent Studio. Those extensions use token-based pricing, which reflects current industry standards for AI usage. This model gives customers both innovation and flexibility: they benefit from improved core functionality without surprise costs, while paying incrementally only when they choose to expand AI into additional areas of the business. The Big Quote: “We're essentially rebuilding our applications from the ground up to make them agentic.” More from Steve Miranda and Oracle: Connect with Steve on LinkedIn or learn more about Oracle AI Agent for Fusion Applications. Visit Cloud Wars for more.

In today's Cloud Wars Minute, I explore how Oracle is redefining enterprise software with AI agentic applications. Highlights 00:03 — One of the biggest stories of the year, maybe the next few years, is going to be the rise of generative AI, the animating force behind business innovation and unlocking new ways for businesses to work, to run, to see the future, to adapt, and to give people higher-value opportunities as well. 00:29 — Oracle, I think, has been the most articulate and the most active in framing out how agents and applications are going to work together in the future. There has been this false choice brought up that it would be apps or agents, but that is not where things are headed. 01:09 — What we're seeing now is not going to be apps and agents. Oracle is fusing them together, calling them AI agentic applications. Steve Miranda explained in a longer conversation I had with him how these applications are different, what the business benefits are for customers, and how this new AI agentic revolution is changing enterprise software. 02:34 — Oracle is saying these AI agentic applications will trigger a shift of applications being systems of record to systems of actual outcomes. The agents are going to pursue not just task by task, but business outcomes, business goals, and business objectives. 03:51 — Companies that move quickly will be able to reposition their people to do higher-value work instead of drudge work. The risks of waiting are growing scarier as the pace of innovation increases, and leaders need to aggressively and confidently take on these new technologies. Check out my longer conversation with Steve Miranda here. Visit Cloud Wars for more.

In this episode of the AI Agent & Copilot Podcast, host Giuseppe Ianni speaks with Parmesh Rajan, VP of Technology for HSO US, live from the AI Agent & Copilot Summit NA in San Diego, California.Rajan explains how organizations are moving beyond experimentation and embedding AI directly into business processes, implementation delivery, and workforce productivity. The discussion highlights a shift from standalone copilots toward operational, production-grade AI agents that deliver measurable outcomes. Key Takeaways AI Embedded in Core Operations, Not Add-On Tools: Organizations are moving from experimenting with AI to embedding it directly into enterprise systems and workflows. As Parmesh Rajan explains, the goal is to shorten complex ERP implementations and integrate AI into core business processes like finance, operations, and customer engagement rather than treating it as a standalone capability. Automation Across the Entire Implementation Lifecycle: HSO is applying AI across the full delivery stack—from gap-fit analysis and solution design to coding assistance and data transformation. This is helping reduce manual effort in traditionally lengthy 12–18 month implementations while improving accuracy and accelerating time to value for customers. Adoption Depends on Workflow Fit, Not Agent Quantity: Industry-specific AI agents are critical for real-world adoption because they align with how users actually work. Examples like automated timesheets and AI-driven expense processing show that success comes from embedding agents into daily workflows, with effectiveness ultimately measured by usage rather than the number of agents deployed. Visit Cloud Wars for more.

In this episode of the AI Agent & Copilot Podcast, Cloud Wars Founder Bob Evans is joined by Dona Sarkar, Chief Troublemaker of AI Adoption at Microsoft, who shares her perspective on how leaders should approach AI adoption, why fear around AI replacing jobs is misplaced, and how executives can create a culture of experimentation. Speaking from the 2026 AI Agent & Copilot Summit NA in San Diego, Sarkar explains why organizations need AI-first thinking, stronger leadership involvement, and a focus on solving impossible problems rather than simply improving existing workflows. Key Takeaways AI Won't Replace You — But Someone Using AI Might: Sarkar strongly pushes back against the fear-driven narrative around AI replacing workers. She explains that change does not happen overnight and that professionals should focus on becoming AI power users instead of waiting for disruption to happen to them. As she puts it, “We will be relevant, irrelevant. Who's they? Exactly. You can be they.” She encourages workers to learn AI within their own discipline (legal, finance, sales, or operations) and become the person who understands how to train, guide, and supervise it. The future belongs to those who learn to “harness its power.” AI Should Solve Impossible Problems, Not Just Existing Ones: Rather than using AI only to optimize familiar work, Sarkar believes organizations should target the problems they have never been able to solve. She says, “Let's go solve the problems we've never been able to solve because we just don't have the human capital.” This shift moves AI from being a cost-cutting exercise to a growth engine. Leaders should use AI to uncover opportunities, identify market gaps, and rethink what their companies are capable of delivering in the future. Focus on Team Productivity, Not Personal Productivity: Sarkar argues that many companies are stuck in outdated AI use cases like meeting summaries and individual task optimization. She believes the real opportunity lies in workflow transformation across teams. “You have to get outside the personal productivity experiments.” By identifying full workflows — like sales enablement or content operations — and improving them with AI agents, companies reduce fear and unlock capacity for new work. AI should create room for innovation and experimentation, not simply make individuals feel more replaceable. Visit Cloud Wars for more.

In today's Cloud Wars Minute, I explore how Stellantis and Microsoft are launching one of the most ambitious enterprise AI collaborations yet, spanning engineering, cybersecurity, and large-scale operational transformation. Highlights 00:09 — Stellantis, the automaker responsible for well-known brands such as Dodge, Jeep, Peugeot, and Ram Trucks, has partnered with Microsoft in a five-year strategic collaboration. 00:19 — The goal of the partnership is to accelerate the company's digital transformation through advanced AI systems, enhanced cybersecurity measures, and next-generation engineering capabilities. Stellantis has already been an early adopter of AI, embedding the technology directly into its vehicles. 00:38 — Now, by collaborating with Microsoft, the company plans to accelerate this AI momentum across the enterprise. Judson Althoff, EVP and Chief Commercial Officer at Microsoft, explained that combining Stellantis' global scale and engineering expertise with Microsoft's trusted cloud, AI, and security platforms will deliver real value for millions of drivers worldwide. 01:03 — In total, the partnership will lead to more than 100 AI initiatives designed to enhance customer care, product development, and operations. This includes AI-powered product development and validation, predictive maintenance and testing, and faster deployment of new digital features and services. 01:48 — This is an incredibly ambitious project — one of the most significant I've seen not only in the automotive sector but across AI transformation initiatives overall. I'll continue following developments closely and sharing updates. Visit Cloud Wars for more.

In this episode of Cloud Wars Live, Bob Evans sits down with Tirthankar Lahiri, Senior Vice President for Mission-Critical Data and AI Engines. Lahiri explains how agentic AI is transforming enterprise applications from simple question-answer systems into action-driven platforms that can reason, remember, and securely execute tasks. He details Oracle's strategy around unified agent memory, private agent factories, deep data security, and open development standards, all designed to help customers build scalable, secure, and flexible AI systems without added cost. AI Built Securely The Big Themes: Agentic AI Becomes Action-Oriented: Tirthankar Lahiri explains that agentic AI represents the next major step beyond generative AI. While generative AI focused largely on answering questions and producing content, agentic AI is designed to take action. It allows businesses to build systems that can reason, decide, and execute tasks autonomously. Oracle sees this as the future of application development, where AI becomes embedded into workflows rather than functioning as a standalone tool. Oracle Builds AI Directly Into the Database: Rather than forcing customers to move data across multiple isolated systems, Oracle's approach is to bring AI directly to the data. Lahiri argues that data is the “ground truth” and moving it creates technical debt, silos, inefficiency, and security vulnerabilities. Oracle's converged database architecture supports multiple data types, including relational, graph, spatial, and vector, inside one unified environment. This eliminates the need for separate repositories and allows AI agents to access all relevant context without fragmentation. Deep Data Security Protects Against AI Risks: Lahiri strongly emphasizes that traditional application-layer security is no longer enough in the age of AI. Since AI can generate SQL and potentially bypass interface restrictions through prompt injection, businesses must secure data directly at the source. Oracle calls this “deep data security.” He uses the analogy of protecting valuables in a safe bolted to the floor rather than simply locking the front gate. Even if someone gets inside the house, the valuables remain protected. Similarly, Oracle enforces security policies at the database level, ensuring agents can only access data users are authorized to see. The Big Quote: "You need to secure data. Need to lock your valuables into the safe deep inside the house." More from Tirthankar Lahiri and Oracle: Connect with Lahiri on LinkedIn or learn more about Oracle AI Database. Visit Cloud Wars for more.

In today's Cloud Wars Minute, I break down Google Cloud's $750M partner ecosystem investment and its aggressive push to lead the agentic AI transformation race against Microsoft, AWS, and Oracle. Highlights 00:03 — Last week in Las Vegas, we saw Google Cloud roll out an incredibly broad, deep set of agentic AI technologies and solutions. They're making a massive push on this. Google Cloud is the number one player in the Cloud Wars Top 10, and they're looking to really take the big lead in agentic AI transformations for their customers. 00:24 — Now, in parallel with that, we also saw Google Cloud — in addition to all what they're doing on the tech track — on the go-to-market side. They have put together what they're calling a $750 million fund for their ecosystem and partners to help them drive AI transformations for customers, right — to help them get better training, to be more technically proficient, to help deploy engineers, and more. 00:53 — So I'm wondering now, in light of this, both the tech splash that Google Cloud made at Next but also now with this push for their partner ecosystem, will Microsoft and AWS match this massive, I would say unprecedented, investment in the ecosystem? 02:26 — You've got, not so long ago, I think you could look at what we called broadly the hyperscalers, and it was a little bit hard to differentiate, right? They were just sort of known as this one blob. I think the companies Microsoft, AWS, and Oracle are differentiating themselves now to a vast degree. 02:47 — I think what Google Cloud is trying to do here is say, “Hey, we're going to do all the stuff we did for you before, but we are going to focus more intensely than any company on Earth on the agentic AI revolution, to provide not just the technology, but the skills that you need from the partner ecosystem." 03:37 — And then it's putting the money behind this to ensure that those partners have the capabilities to do it — and to do it very quickly — because this is a race to see who is going to get that first-mover status. So far, I believe Google Cloud is in that for agentic AI transformations for customers across the globe and across industries. Visit Cloud Wars for more.

In today's Cloud Wars Minute, I break down how SAP is outperforming Oracle, Salesforce, Workday, and Microsoft in the applications race. Highlights 00:03 — We saw some first-quarter numbers from SAP late last week, and I think it's fascinating to see how, in the light of these very, very strong numbers from SAP, we still seem to hear about this idea that these doomsayers are saying that AI is going to destroy the enterprise apps business. That's certainly not happening. 00:33 — The three big numbers here: cloud revenue up 27%, almost $7 billion. Within that, its Cloud ERP Suite was up 30% to $6.1 billion, and looking out at contracted business not yet recognized as revenue, it calls it current cloud backlog, up 25% to well over $25 billion. 00:57 — That's pretty healthy-looking business for one that is, you know, doomed to the apocalypse and Armageddon any day now, according to some of these wizards of smart who believe that AI is going to come in and just decimate the enterprise apps business. 01:52 — The only thing I can think of that gives them this idea that the whole industry is heading for Armageddon here, they must believe that companies like SAP are unprepared for or unable to participate in the AI revolution, but that notion ignores where the data really is. 02:28 — Agentic AI is the future. Agents need data to run, and who has more and better business data than SAP? So this just confounds me. 02:43 — We continue to see SAP outperform Oracle's applications business, Workday, Salesforce, and also the apps business part of Microsoft Dynamics 365. I think this is a very strong quarter by SAP, and the future here is very bright. Visit Cloud Wars for more.

ogle Cloud Next, Cloud Wars CEO and Founder Bob Evans sits down with Karthik Narain, Chief Product and Business Officer, Google Cloud, to discuss how AI is fundamentally changing enterprise expectations. Narain explains why customers no longer judge technology providers by licenses sold or cloud consumption, but by measurable business outcomes. From forward-deployed engineers to agentic workflows and the evolving role of product design, he outlines how Google Cloud is rethinking engagement, product development, and enterprise transformation in what he calls the third major wave of technology innovation. AI Demands Outcomes The Big Themes: Outcomes Replace Consumption Metrics: Narain explains that enterprises are no longer measuring technology providers by how many licenses they sell or how much cloud consumption occurs. Instead, success is now judged by outcomes delivered. Customers expect providers like Google Cloud to share equal responsibility for business results, not just provide tools and leave execution to the customer. This represents a major shift from prior eras where businesses viewed themselves as the sole owners of converting technology into value. AI's speed and sophistication have raised expectations dramatically. The Third Technology Wave: Narain frames today's AI era as the third major wave of enterprise technology over the past 60 years. The first wave from mainframes through ERP, focused on codifying business processes into repeatable systems. The second wave centered on delivery model innovation, moving software into SaaS and cloud environments. The third wave is fundamentally different because the technology itself learns and evolves. Rather than giving software fixed instructions, enterprises must feed it data, context, and reasoning. This changes how software is designed and deployed. Every Feature Must Become a Skill: Products must now be designed for both humans and AI agents. Narain explains that every feature inside enterprise software needs to be exposed as a “skill” that agents can activate directly. This means software can no longer assume a human user is the only operator. Agents must be able to trigger workflows, execute tasks, and coordinate processes independently. This changes how products are structured from the ground up. The Big Quote: “The application's user interface is no longer clicks and drop-downs. It is going to be prompts and agentic workflows." Visit Cloud Wars for more.

In this Cloud Wars conversation, Bob Evans sits down with Shub Bhowmick, CEO and Founder of Tredence, alongside Yasmeen Ahmad from Google Cloud to explore how enterprises are moving from AI applications to AI agents. Their discussion focuses on what it takes to turn intelligence into action — covering data foundations, semantic layers, agentic architectures, and the operational shifts required for businesses to scale AI successfully. Turning AI Into Action The Big Themes: AI Agents Redefine Applications: Traditional AI apps assist by querying data, generating recommendations, and supporting limited workflows. AI agents, however, represent a much deeper operational shift. As Ahmad explains, agents are multi-step reasoning engines that can access multiple systems, coordinate actions, and execute entire business processes autonomously. Instead of simply helping humans decide, they can perform work across ERP systems, supply chains, and customer interactions. This changes the role of the database itself — from a storage and query engine into a reasoning engine with vector search, graph RAG, and semantic understanding. Examples like Home Depot and Danfoss show how this creates massive efficiency gains Why Questions Require Agentic Intelligence: Shub Bhowmick draws a critical distinction between “what” questions and “why” questions. A conversational BI system can answer what happened — such as how much sales dropped — but a “why” question demands deeper reasoning. Why did sales decline? Was it pricing pressure, competitor behavior, inventory constraints, or macroeconomic events? These problems require hypothesis-driven exploration. Tredence addresses this through business semantic layers, knowledge graphs, and hypothesis banks that support open-ended reasoning. Closed Systems Create Long-Term Risk: Bhowmick warns against enterprises rushing toward closed, inflexible platforms simply because they promise faster short-term value. While packaged solutions may accelerate deployment, they often restrict ownership, adaptability, and future innovation. In contrast, open architectures built with hyperscalers like Google Cloud allow customers to own the IP, customize solutions, and evolve as the market changes. The Big Quote: “Gone are the days when these migrations used to take 12 to 18 months. Nowadays, you have to complete these migrations in less than three to four months.” More from Tredence and Google Cloud: Learn about the partnership between Tredence and Google Cloud and AI agents on Gemini Enterprise. Visit Cloud Wars for more.

In this special episode of Cloud Wars Live from Google Cloud Next, Bob Evans speaks with Andi Gutmans about Google Cloud's newly announced Agentic Data Cloud and what it means for enterprise customers entering the AI-driven future. Gutmans explains how businesses must rethink data platforms for an era where autonomous agents, not just people, need instant access to trusted enterprise knowledge. The New Data Foundation The Big Themes: The Agentic Data Cloud Is a Reinvention: Google Cloud is not simply rebranding its existing Data Cloud, it is fundamentally redesigning it for the agentic AI era. Gutmans explains that data must evolve from being a passive repository into active business knowledge that agents can reason over. He describes this as moving from a “system of intelligence” to a “system of action.” The newly announced Agentic Data Cloud includes innovations across databases, analytics, storage, and governance so agents can securely access and act on enterprise information. Culture Matters More Than Technology: According to Gutmans, the organizations moving fastest are the ones embracing cultural transformation, not just deploying models on top of old systems. Companies succeeding in the agentic era are rethinking how their data platforms work and how employees engage with AI. Instead of treating agents as copilots, they view every employee as an orchestrator of agents. That mindset shift drives faster ROI because it creates readiness for change and willingness to innovate. Google's Vertical Stack Is a Major Advantage: Gutmans says that Google Cloud is uniquely positioned because it owns the entire stack: AI infrastructure, models, and the data platform itself. This allows what he calls “closed-loop innovation” between models and data systems, where improvements in one directly enhance the other. He says many people underestimate how important that relationship is because model reasoning must evolve alongside the platform serving enterprise data. Products like BigQuery, Spanner, and Gemini benefit from Google's decades of operating at massive scale, including multiple billion-user businesses. The Big Quote: "We're moving from this reactive, agentic experience to agents truly being autonomous, being able to drive outcomes for the business, and that's also now steering how we're thinking about the data cloud." More from Google Cloud: Learn more about what's new in the Agentic Data Cloud and security in the AI era. Visit Cloud Wars for more.

In this episode of the AI Agent & Copilot Podcast, Giuseppe Ianni sits down with Ryan Grant, Chief Strategy and Revenue Officer at sa.global, who shares insights on how organizations are approaching AI adoption, where they're struggling to get started, and how industry-specific agentic solutions can drive efficiency and revenue protection. Their discussion, recorded live at the 2026 AI Agent & Copilot Summit NA, spotlights the urgency, complexity, and opportunity surrounding AI transformation. Key Takeaways Starting Is the Biggest Challenge: Many organizations are not lacking interest, but direction. Grant says that customers are struggling to prioritize use cases across departments. The range of entry points (from finance to customer experience) creates confusion. The key is narrowing focus and identifying high-impact starting points. Without clarity, companies risk paralysis or misaligned investments. Industry-Specific AI Is the Real Differentiator: Grant discusses the importance of tailoring AI solutions: “what we're really trying to do… is figure out how to help those industries optimize.” Generic AI tools fall short without context. By focusing on sectors like construction, engineering, and legal, sa.global builds agents that understand workflows, billing models, and operational nuances. AI Must Understand Your Business to Work: One of the most powerful insights: “you can go plug an agent in, but if it doesn't know your business… it's never going to work.” AI is not plug-and-play. Like a new employee, it needs training, context, and alignment with company processes. Organizations must integrate AI into their workflows thoughtfully, ensuring it reflects how they operate. This alignment is the difference between failed pilots and transformative success. Visit Cloud Wars for more.

In today's Cloud Wars Minute, I look at why Google Cloud's new Gemini Enterprise could reshape enterprise AI and force competitors to raise their game. Highlights 00:44 — I think we're going to see Google Cloud leapfrog the competition with Gemini Enterprise. I believe it's absolutely a breakthrough product — enormously impressive. I'll have a longer, detailed article later today on cloudwars.com where I go into more depth, but let me offer a few thoughts here. 01:06 — First of all, it's going to force all the AI and cloud players to step up to a different level. For roughly the past three and a half years — since the launch of ChatGPT 3.5, when the AI Revolution kicked off — the tech industry has released an incredible array of dazzling, powerful, highly capable, and truly breathtaking technologies. At the same time, most of those technologies have required customers to assemble everything themselves. 01:37 — Gemini Enterprise, in its new format, pulls together everything Google Cloud offers — very open, easy-to-work-with technologies from other companies, plus access to all the data customers have. That's where I think it will really help customers who have been spending far too much on integration costs trying to rationalize their AI investments. 02:08 — Second, it connects systems of record. Google particularly called out data from applications like Workday, Salesforce, platforms such as Palantir, and ServiceNow — making it easy for customers to pull data from all those places. Industry-specific and domain-specific agents are also central to what Google Cloud is building into this new Gemini Enterprise version. 03:05 —Third, security. Google Cloud is introducing everything from an agentic security operations center to autonomous security agents that continuously look for threats, report back, and take action. This isn't passive security — hoping nothing happens — but an active stance: getting ahead of threats. 03:56 — Finally, the powerful partner ecosystem. This has always been a major part of Google Cloud's strategy. Thomas Kurian has made partnerships a centerpiece — not just Google Cloud technologies, but the force-multiplying effect of partners playing a huge role in what customers can now achieve with the new and improved Gemini Enterprise. Visit Cloud Wars for more.

In today's Cloud Wars Minute, I explain why Oracle's AWS partnership signals a new era of cloud interoperability. Highlight 00:03 — Recently, my colleague Bob Evans reported on a new initiative from AWS called Interconnect multicloud aimed at enhancing the company's multi-cloud offerings. Now, Oracle has announced that it will leverage AWS Interconnect multicloud to expand its multi-cloud networking capabilities. 00:31 — Oracle is enabling high-performance connectivity between Oracle Cloud Infrastructure and AWS by connecting Oracle Interconnect with AWS Interconnect multicloud. Now, as a result, Oracle customers will gain, and I quote, access to "a fast, private, managed connection to run applications and move data seamlessly between OCI and AWS." 01:00 — This new connectivity will support both full and split-stack multi-cloud deployments, empowering customers to confidently leverage the benefits of both cloud providers without the management complexity that previously posed major challenges. 01:14 — Nathan Thomas, Senior Vice President, Product Management at Oracle Cloud Infrastructure, said the following: "Oracle continues to advance multi-cloud connectivity as part of its commitment to help customers unlock flexibility, agility, and performance across clouds." 01:40 — Once again, we see Oracle at the forefront of multi-cloud connectivity, quickly integrating with a competitor's product to ensure that its customers are always in a position to realize their business ambitions, most notably in the AI space, without the issues of dispersed systems, data silos, and latency. Visit Cloud Wars for more.

In this episode of the AI Agent & Copilot Podcast, Giuseppe Ianni is joined by Tad Remington, Chief Commercial Officer at Solver, who discusses how AI is transforming financial planning and analysis through intelligent agents. Key Takeaways The Rise of AI in FP&A: Remington emphasizes that AI is no longer experimental in finance, it's operational. Organizations are increasingly relying on AI agents embedded in FP&A tools to enhance analysis and planning. As he notes, “they really like the analysis capabilities that we have built in,” highlighting strong adoption of AI-driven insights across finance teams. Trusted Data Is the Foundation: A major differentiator for Solver is its reliance on curated, governed data. Remington explains that AI outputs are only as good as the inputs: “it works off of the reports that they've developed….” This ensures accuracy, security, and trust in AI-generated insights. Autonomous Finance Is Coming Fast: One of the most forward-looking insights is the move toward autonomous agents. Remington shares, “we want to get to… the autonomous agent kind of era,” where financial processes run independently and take action without prompts, signaling a major shift in how finance teams operate. Visit Cloud Wars for more.

In today's Cloud Wars Minute, I preview Google Cloud Next and share three bold predictions around AI security, sovereignty, and Gemini Enterprise. Highlights 00:03 — We've got Google Cloud Next coming up this week in Las Vegas. The world's number one cloud and AI provider is going to, no doubt, roll out a lot of interesting technologies, partnerships, go-to-market plans, and new ways for customers to thrive in the AI Economy. 00:31 — First, I think big launches around AI security. This has been a differentiator for Google Cloud in the whole run of the hyperscaler competition, and it's distinguished itself with Mandiant and threat intelligence capabilities. And it recently closed the acquisition of Wiz. So it's got some very good foundations there to build upon in AI security and sovereignty. 01:23 — Similarly, AI sovereignty is huge now, and it's only going to get bigger here in the AI Era, as data becomes more vital, privacy becomes more vital, security becomes more vital, and a lot of nations and regions are going to become even more specific in trying to say here's what's possible with the movement of not only data, but applications, where things have to be based. 02:08 — Too many technology vendors and customers were falling into a trap of thinking there's a false choice, you can either be fully compliant or grow aggressively. Google Cloud says that's a false choice and customers can do both. 03:43 — My prediction for the third big area is Gemini Enterprise, a breakthrough product with strong customer adoption, enabling companies to build agents and integrate AI into workflows at scale. Visit Cloud Wars for more.

In today's Cloud Wars Minute, I explore the growing divide between cloud innovators and followers in the AI Era. Highlights 00:03 — Now we see here in April of 2026 a distinction between leaders and followers in the cloud and AI markets. And this came through quite distinctly here. AWS has just launched what it calls its multi-cloud interconnect service, and it's going to be good for some customers. 00:51 — In spite of the fact that AWS cloud revenue is much, much larger than Oracle, size matters, but it is not the only differentiator. Their service is going to start with Google Cloud, and AWS is going to add both Microsoft and Oracle later this year to allow secure data exchange across these clouds. 01:42 — Oracle followed that up with what I call the Microsoft miracle, where it set up these multi-cloud partnerships with its three primary rivals — first Microsoft, then Google Cloud, then AWS — allowing customers to buy and deploy the Oracle database through those other clouds. 02:22 — As far as who is setting the agenda and driving innovation, it's very much more Oracle and Google Cloud, and AWS now is proven a follower. I can't even call them a fast follower, because it's been about three years since they followed up on this. 03:10 — In the midst of the AI revolution and the beginning of the global AI economy, it's much more important to find tech partners who help you create the future, not just improve the past, and that's why innovation that drives rapid business outcomes matters most. 03:56 — So with businesses now being in a situation where they don't have lots and lots of time to tinker and experiment and wait to see what the competitors do, they've got to move very quickly. That's why with the Cloud Wars Top 10, I've put such an emphasis on innovation that drives rapid business outcomes. Visit Cloud Wars for more.

hts 00:09 — Microsoft has introduced new capabilities to Copilot Studio to enhance automated operations by combining AI agents and workflows. Currently, Copilot Studio users can choose between agents and workflows to create automations. 00:27 — While agents are inherently flexible when it comes to business use cases, Microsoft has recognized that, as they state, pure agent autonomy doesn't always hold up to production requirements. On the other hand, workflows, which are more rigid and rule-based, can be inflexible and may have limitations in their capabilities. 00:58 — The first pattern involves workflows calling agents to make judgment calls on structured automations. To support this, Microsoft is introducing agent nodes. This allows users to call an existing agent from a workflow, send a message to the agent, retrieve the agent's response, and use it in subsequent workflow steps if necessary. 01:31 — Now, the second pattern that Microsoft has identified is using workflows as tools. In this scenario, when an agent is working through a complex task, instead of trying to learn how to handle it independently, it can call an existing workflow to execute the subprocess and then continue its reasoning based on the results. 02:29 — Microsoft states that these two approaches combine agents and workflows to provide users with the flexibility to build automations that better address real-world needs—and that's the key here: real-world applications. Visit Cloud Wars for more.

In today's Cloud Wars Minute, I explain why success in the AI Economy demands bold, uncompromising leadership from CEOs — and why many aren't ready. Highlights 00:03 — It's been fascinating to see that recently, AI transformation has begun to hit hard at the CEO rank. Up until now, as we've all seen, there have been hundreds of thousands of job losses that have taken place in lower-level or mid-level jobs. And I think now we're starting to see that the new victims of AI are going to be CEOs. 00:25 — And I think we can put those into three categories: those who are unable to see what's happening and deal with it, those who are unwilling to acknowledge the reality of what's changing, and then there's those who are unseeing. They choose not to see what's going around them, or they're not willing to recognize just how serious it is. 01:15 — But I think what we're really starting to see now, and I'll offer some tangible examples here, is this is going to come down to be a real issue for CEOs, because companies that want to succeed in the AI Economy will not be able to do so unless they've got full, unbridled, uncompromising leadership and support for the business transformations being wrapped around AI. 02:30 — By every measure, Doug McMillon, the CEO of Walmart, has been a terrific CEO. But late last year, when he announced that he was going to step down as CEO, he said, “I just don't think I'm the right person for this job. We've started a lot of AI changes and transformations. I'm not sure I'm the right person to finish those. We need somebody who's faster.” 03:20 — Now, another group here is the kind I'm calling the unwilling, and they are the ones that are big on, “Well, let's have a committee. Let's form a SWAT team. We'll see what the threats are to our company. We'll see what we need to do, and we'll give them six months or nine months or a year, and they'll report.” And by then, their company is sort of over the cliff and is not going to be able to make it. 04:08 — Marc Benioff, the CEO of Salesforce, said AI has become a convenient scapegoat for everything. He said there are a lot of CEOs right now who are just saying whatever happens, good, bad, indifferent, it's all due to AI. “We had to make a lot of layoffs — that's because of AI. We had to stop doing this — we had to stop doing that — well, it's all because of AI.” He said that's a cop-out. 04:55 — So for business leaders, you can smell this in your company. You can feel it. Are we a company that is bullish and going after this thing with AI, or are we going to be one of these people who are unwilling, unseeing, and just not ready to jump in? There are brutal times coming for companies that are not willing to get into this. It starts with the CEO. Visit Cloud Wars for more.

In today's Cloud Wars Minute, I explore how governance gaps are slowing AI agent adoption in enterprises. Highlights 00:05 —The role of AI agents in enterprise has advanced enormously in recent months, evolving from passive Q&A bots to systems that can take real actions in production environments. This is things like managing finances or accessing confidential patient data for healthcare organizations. 00:23 — However, a major hurdle often remains, and that's compliance. In many cases, audit and risk teams are reluctant to endorse these new capabilities because it's difficult to prove what an agent has done, which policies were in effect, and whether those policies were actually enforced. 00:45 — Panoptic Systems is a Mississippi-based firm developing runtime governance infrastructure for AI agents. Now, the team there recognized early on that as businesses deploy agents capable of taking these significant actions within production environments, a crucial missing layer of the technology stack was deterministic infrastructure-level governance that provided audit-grade evidence. 01:36 — Panopticore offers four possible outcomes for agent actions: allow, warn, block, or require human approval. Every decision is recorded in a cryptographically signed audit trail that can be verified offline by any internal auditor or third party. 02:28 — Panopticore delivers the controls and evidence that compliance teams, auditors, and often insurers need before agents can move from pilot to production. In simple terms, this technology is unblocking agents that are stuck in limbo. Visit Cloud Wars for more.

In today's Cloud Wars Minute, I analyze Q4 performance to reveal who's truly leading in cloud growth right now. Highlights 00:03 — We're just a couple weeks away from getting Q1 results of the hyperscalers and some other companies in the Cloud Wars Top 10, I wanted to take a look at these world-shaping companies. Let's start off by taking a quick look back at Q4 and some numbers for Google Cloud, Microsoft, and AWS. 00:34 — I'm not including Oracle in this hyperscaler comparison because it's on a different financial reporting schedule, and I recently covered Oracle's most recent financial results in detail. So if we compare the Q4 growth rates for Google Cloud, Microsoft, and AWS: 48%, 26%, 24%. Now some people say, “Oh, that's not fair. That's not legit. Google Cloud is so much smaller.” 01:01 — Let's look: $17.7 billion for Google Cloud, $51.3 billion for Microsoft, $35.6 for AWS. So AWS is about twice as big as Google Cloud, and relative to Microsoft, Microsoft is three times bigger than Google Cloud. Riddle me this: how then, if you look at Q4 cloud and AI revenue versus Q3, Google Cloud came up with more revenue — more incremental Q4 over Q3 revenue — $2.5 billion versus $2.4? 02:23 — Yet AWS came up with more — significantly more — revenue Q4 over Q3 than Microsoft did: $2.6 billion versus $2.4. Now what does that mean? Well, it could be a temporary blip. It could be an anomaly. I think all of these things are valid. They all are pointing toward bets that customers are making about who is the company best equipped to take my company into the AI future. 03:49 — Google Cloud came up with almost as much as AWS. And to me, that just says Google Cloud is the hot company right now. So let me wrap up here with an outlook for Q1. I think both Google Cloud and Microsoft say that they will be releasing their financial results for Q1 on April 29. I think we're going to see Google Cloud report a growth rate of 44%, Microsoft 25%, and AWS 23%. Visit Cloud Wars for more.

Highlights 00:09 — Microsoft's global investments continue to grow. Latest news is the company plans to invest $10 billion into Japan over the next three years to build out AI infrastructure, improve cyber resilience, and train a million engineers and developers by 2030. 00:28 — Our key partnerships include internet infrastructure provider Secura Internet, whose share price rose over 20% following the announcement, and SoftBank, already a major player in the AI revolution. Now, thanks to Secura Internet's data infrastructure, the data used to develop various AI systems, including domestic large language models, will be processed in Japan. 00:57 — Now, in terms of training, Microsoft is also partnered with five other Japanese IT firms, including NTT Data Corp, NEC, Fujitsu, and Hitachi, to deliver this ambitious target. Now, the two-point focus here on both infrastructure and training is becoming a common strategy for companies building the next generation of AI systems. 01:22 — However, instead of solely focusing on the domestic market, Microsoft is continuing its global investment drive by enabling in-country training, leveraging the incredible skills base already available within existing organizations. Now, let's not overlook the importance of data sovereignty, either. 01:41 — It's increasingly important to adhere to the laws governing where data resides, and these laws are only becoming more stringent. Not only is Microsoft future-proofing itself, it's also cultivating the next generation of Azure customers and AI-native enterprises aligned with its platforms. Visit Cloud Wars for more.

In today's Cloud Wars Minute, I break down OpenAI's massive $122 billion funding round and what it means for the future of AI infrastructure. Highlights 00:04 — OpenAI has completed its latest funding round with $122 billion in committed capital. The company explained the reasoning behind such a massive investment by highlighting that after reaching a billion dollars in revenue in its first year, it's now generating $2 billion in revenue per month, more than 40% of which is driven by the company's enterprise products. 00:54 — So what will it do with all of this funding? Well, the answer to that is a lot, but for the purposes of this minute, I'm going to dig into its core goals. Now, one of the major expansion areas is in infrastructure, as demand for AI systems is increasing. 01:13 — OpenAI recognizes that no single architecture can meet the demands of this diverse range of needs and expectations. So to that end, the company is building a broader infrastructure portfolio that incorporates cloud services, chips, and design partners. 01:43 — And then there's the AI Super App. OpenAI said in a blog post, our Super App will bring together ChatGPT, Codex, browsing, and our broader agentic capabilities into one agent-first experience. 01:58 — This is not just product simplification, it is a distribution and deployment strategy. Adding the capital being deployed today is helping build the infrastructure layer for intelligence itself. Visit Cloud Wars for more.

In today's Cloud Wars Minute, I explain how ServiceNow is enabling secure, scalable adoption of AI agents across the enterprise. Highlights 00:03 — ServiceNow is joining forces with Zenity, the first security and governance platform that's been purpose-built for AI agents. Zenity is becoming a ServiceNow build partner, bringing with it a range of capabilities to ServiceNow Security Operations, including agent security, posture management, and vulnerability assessment. 00:25 — Deepak Kolingivadi, VP of Product Management and Head of Security Products at ServiceNow, said the following about this new partnership: “AI agents are transforming how work gets done across the enterprise, including Security Operations. Our partnership with Zenity strengthens the ServiceNow AI control tower and Security Operations solutions.” 01:01 — Now, collectively, these new capabilities bring to ServiceNow customers a greater ability to scale the use of AI agents safely and with full confidence as part of their existing SecOps processes. And what we're seeing here is ultimately a new category, AI Security Operations, or AI SecOps. 01:26 — It's also important to note that by embedding this governance layer through its build partnership, ServiceNow is demonstrating that it's truly ahead of the curve here. All new products delivered by software vendors need integrated security and governance, and agentic AI is no exception. 01:58 — The key word here is scale. ServiceNow has the tools to drive AI across the breadth of a business, and now through Zenity, it's delivering the ability to do this at scale. Visit Cloud Wars for more.

In today's Cloud Wars Minute, I explore how Microsoft's latest Windows changes reveal a strategic shift toward more intentional AI integration and focused Copilot experiences. Highlights 00:09 — It was only a short paragraph in a blog post by Microsoft's Pavan Davuluri, Executive Vice President of Windows and Devices, discussing the changes the company is making to Windows in response to community feedback. However, it has significant implications and, if you pick it apart, could provide a better understanding of where Microsoft is directing its AI ambitions. 00:36 — Here's the paragraph in full: “With craft and focus, you will see us be more intentional about how and where Copilot integrates across Windows, focusing on experiences that are genuinely useful and well crafted,” says Davuluri. “As part of this, we are reducing unnecessary Copilot entry points, starting with apps like Snipping Tool, Photos, Widgets, and Notepad.” 01:05 — When Microsoft went all out on the Copilot rollout across its massive ecosystem of products, platforms, and services, some commentators argued that this push could overwhelm consumers. Instead, a more targeted approach would perhaps make it easier for customers to see the benefits and, critically, the use cases that Copilot can amplify. 01:28 — It seems that Microsoft has taken these concerns into consideration and is now scaling back the areas where Copilot is utilized. This is a smart move from a Windows perspective, as it prioritizes value over volume, and this approach aligns well with the evolving direction of Copilot Studio, which focuses on creating agentic experiences. 01:53 — Now Microsoft is consolidating its AI offerings by moving away from the idea of having Copilot everywhere. Instead, agents developed through Copilot Studio will be able to plug into specific execution environments, just like Windows. Visit Cloud Wars for more.

In today's Cloud Wars Minute, I explore how Salesforce is betting big on Slackbot to power the AI agentic enterprise. Highlights 00:02 — We are seeing enormous changes take place among the leading enterprise applications vendors, with the rise of AI. Business customers are expecting a different way of working here in the emergence of the AI Economy. So at Salesforce, I believe Marc Benioff has decided to go all in on Slackbot to drive what Salesforce is calling the AI agentic enterprise. 00:29 — Now this is critical, because Salesforce is the largest enterprise applications vendor in the world. It also has an $800 million Agentforce business that it has built up, and it's taking both of those key components from agentic AI and also their enterprise apps business, and sort of putting those under the control of the orchestration of Slackbot, a brand new product. 01:15 — Benioff said that we are seeing in the business world the very beginnings of an AI agentic divide, where he said, on the one hand, there are customers that have understood the way they need to get into this, how to use agentic AI to do things better. And then, on the other hand, coming in there, saying, "Ah, you know, I'm not sure. I'm going to sit back and wait for this." 02:08 — He said Slackbot is already the fastest-growing feature ever in the history of Salesforce. He said it might be the fastest-growing feature in all of enterprise technology. And secondly — this is pretty wild — he said Slackbot and Slack are already disintermediating Salesforce. 04:36 — And he said, it's our job not to just sit back and scratch our heads about this, but to help companies be able to address these changes, get out in front of them, get on top of them. And Salesforce believes that Slack and Slackbot, in particular, are going to be the ways that that happens. Visit Cloud Wars for more.

In today's Cloud Wars Minute, I examine how Business Central is transforming ERP with strong financial returns and AI-driven capabilities. Highlights 00:10 — A new Forrester report commissioned by Microsoft, entitled "The Total Economic Impact of Microsoft Dynamics 365 Business Central," has revealed some remarkable findings regarding the financial impact this standout cloud ERP is having on customers. 00:36 — And here's what it found: 209% ROI over three years, an estimated $464,000 net present value, and potential payback in just six months. The researchers aggregated the findings from interviewees and created a fictitious composite organization to develop this model. 00:58 — In their modeling, the researchers found that by year three, the composite company was experiencing a 30% reduction in monthly close time and up to 50% time savings for accounts payable, accounts receivable, and billing. It reduced audit preparation time by up to 30%. 01:19 — Consolidating outdated ERP products and systems led to more than a 10% reduction in total cost of ownership and over $170,000 in present value savings from withdrawn systems and decreased maintenance. 01:37 — Microsoft links these impressive results to how Business Central represents an AI-ready ERP foundation, enabling organizations to leverage Copilot, Power BI, and intelligent agents while emphasizing clean data, integrated systems, and standardized processes. Visit Cloud Wars for more.

In this AI Agent & Copilot Minute, Mason Siefert explores how Dynamics 365 is evolving into the agentic era — transforming financial reconciliation and accounts payable into continuous, intelligent processes, and previews what's ahead at Summit North America 2026. Key Takeaways Agent Evolution: The journey from manual processes to copilots and now fully autonomous agents marks a fundamental shift in enterprise finance. While early tools accelerated workflows, today's agents proactively execute tasks end-to-end, reducing human intervention and enabling finance professionals to focus on higher-value strategic work rather than repetitive operations. Continuous Finance: Financial reconciliation has transformed from a stressful, multi-day effort into an always-on background process. Autonomous agents continuously match and verify records across systems, eliminating bottlenecks and dramatically improving efficiency, accuracy, and consistency across financial operations without requiring manual initiation. Fraud Reduction: Accounts payable agents not only automate invoice matching but actively reduce fraud risk by cross-referencing invoices against purchase orders and learning from human corrections. With organizations facing high rates of fraud attempts, these adaptive systems provide a critical layer of intelligence and protection while minimizing costly manual errors. Visit Cloud Wars for more.

In today's Cloud Wars Minute, I unpack how Oracle is redefining data activation with agentic AI capabilities. Highlights 00:03 — I recently talked about some big plans that Oracle has for fusing agentic AI into its applications and calling those Oracle agentic applications. Now it's extended its whole mantra from a couple of years ago that came from Chairman and Founder, Larry Ellison, where he said AI changes everything. 00:28 — Oracle's taken that very much to heart, and they're extending their agentic AI push deeply into their AI Database. There's a couple things I want to point out. In the larger sense, I think what's going on here is we're seeing the hunted turn into the hunter, right? 01:20 — I think in large part, not so much that the theory was wrong, although I do think it is wrong, but more because Oracle took the initiative, and instead, its pace of innovation and change and product development and customer-centric enhancements have been at a pace far beyond what any of these single-purpose competitors are doing. 02:12 — Now with AI, the point of Oracle's move here is to say we're going to bring AI to the data, instead of having to move all the data around here. And nobody's in a better position to be able to do that now than Oracle. 03:03 — [Oracle Executive Vice President Juan Loaiza] said, with the Oracle AI database, customers now, they don't just store data passively in a warehouse. Instead, he said, customers will be able to activate their data for AI and make decisions around data with stock-exchange-level robustness in every leading cloud. 04:00 — But the larger point here, too, is about, when Larry Ellison said publicly AI changes everything, that was a pretty clear indication that he was going to be leading this entire effort to go completely across the entire company, every facet of Oracle's massive portfolio is going to become AI-first. Visit Cloud Wars for more.

In this episode of Cloud Wars Live, Bob Evans sits down with Bonnie Tinder, Founder and CEO of Raven Intelligence, to unpack a whirlwind week in enterprise software. As AI reshapes the landscape at breakneck speed, the two explore major announcements from Oracle and Workday. Bonnie offers sharp analysis on the strategic differences between Workday's user-centric AI assistant approach and Oracle's autonomous, end-to-end agentic applications. Episode 59: Enterprise AI Showdown The Big Themes: Oracle's Autonomous AI Vision: Oracle is taking a more aggressive approach with its agentic AI applications, introducing 22 AI-driven tools that can execute entire business processes. Unlike assistive AI, Oracle's agents can reason, decide, and act with minimal human intervention. This represents a shift toward AI as a “digital workforce,” capable of handling complex, cross-functional operations. End-to-End Business Process Automation: One of Oracle's biggest differentiators is its ability to automate complete workflows across multiple business functions. For example, designing a product while simultaneously evaluating supply chain risks and costs. This eliminates the traditional handoffs between departments and enables a holistic, real-time view of operations. By integrating data across systems and processes, Oracle's AI can deliver more comprehensive insights and faster execution — potentially transforming how enterprises manage complex workflows. ROI and Consumption-Based Models: AI is also changing pricing and operating models. Workday's shift toward consumption-based pricing means customers pay based on usage rather than per-employee licensing. This can make adoption more flexible and cost-effective, but it also requires careful ROI analysis. Companies must consider not just technology costs, but also potential workforce changes, efficiency gains, and redeployment of employees. Understanding the financial impact of AI investments is critical for long-term success. The Big Quote: “The high-risk areas you don't want to touch necessarily. You want to look at the high volume potentially first, to fully automate." More from Bonnie Tinder: Connect with Bonnie on LinkedIn. Visit Cloud Wars for more.