Cloud Wars Live with Bob Evans

In this episode of the AI Agent & Copilot Podcast, John Siefert, Founder and CEO of Cloud Wars, is joined by Cedric Wells, IT leader and former Senior Manager of Infrastructure and Operations at Gorilla Glue. Together, they explore how AI is reshaping IT leadership, software development, governance, and enterprise transformation. Wells shares why continuous learning, balancing strategic vision with execution, and maintaining strong security and data governance will define successful organizations in the AI Era. Their conversation also reflects many of the leadership themes that attendees explored at the 2026 AI Agent & Copilot Summit NA. Key Takeaways Growth mindset is becoming the most valuable IT skill. Wells believes technical expertise alone is no longer enough. The speed of AI innovation requires professionals at every level to continuously refresh their knowledge and remain adaptable. He explains that technologies evolve so rapidly that learning has become a permanent responsibility rather than a periodic exercise. As Wells notes, "Having a mindset that's really around learning as much as I can as things are changing" is essential. He also reminds listeners, "It's changing so fast," making curiosity and adaptability foundational qualities for future IT leaders. AI enhances leadership — but doesn't replace technical understanding. Wells argues that AI is helping close the gap between technical specialists and business leaders, allowing executives to understand complex technologies more quickly. However, leaders still need enough technical context to ask intelligent questions and make informed decisions. As he explains, "Being able to really as a leader leverage AI as much as possible" creates significant advantages. He also emphasizes that "bridging that gap with your leadership skills and leveraging AI on the technical side" will define successful IT leadership moving forward. Governance and security are becoming even more important. Throughout the conversation, Wells repeatedly emphasizes that AI initiatives require close collaboration between infrastructure, information security, governance, and data teams. Without proper oversight, organizations risk exposing sensitive information, creating compliance issues, or building unreliable AI systems. Wells reminds listeners that "It's very important to make sure that those two departments are aligned" and warns that "Employees are doing it whether or not you like it," making proactive governance and secure enablement far more effective than restrictive policies alone. Visit Cloud Wars for more.

In today's Cloud Wars Minute, I look at why Salesforce's new Help Agent represents a major shift toward performance-based enterprise AI. Highlights 00:03 — Salesforce is launching the Agentforce Help Agent, a pre-built AI customer service agent that customers can deploy in a matter of minutes. It's designed as an alternative to custom-built agents, connecting to existing Salesforce knowledge articles and support content, which means only minimal configuration is required. 00:23 — I'm going to walk you through the features of this new agent before getting to the part I'm most excited about, and I think you will be too. The agent was built on the Agentforce platform and uses the Salesforce Data Cloud and CRM data for context, incorporating the responsible use and governance policies there too. 00:43 — It delivers enterprise-grade customer support by answering customer questions, troubleshooting issues, escalating complex cases to a human support agent. Salesforce validated the agent internally before the launch, and the company has reported that its own Help Agent handled 4.3 million customer conversations and resolved around 70% of inquiries autonomously, really showcasing its effectiveness. 01:16 — Here's the kicker: the new Help Agent operates on a resolution-based pricing model. This means that customers are only charged when the agent successfully resolves a customer's issue. There's no charge if the conversation is handed off to a human agent before resolution, and this approach is quite groundbreaking. In many ways, Salesforce is testing a new pricing model for enterprise AI. 01:50 — From an AI in the workplace perspective, this agent operates on a performance-based pricing scenario, similar to how a gig worker is paid for successful tasks completed, right? So, Salesforce is not the first company to use outcome-based pricing for software, but bringing it to Agentforce and pushing it further into enterprise AI is remarkable stuff and a great step forward from Salesforce. Visit Cloud Wars for more.

In today's Cloud Wars Minute, I explain why hyperscalers are rewriting the rules of deal-making to build the next generation of AI infrastructure. Highlights 00:01 — We are seeing the beginnings here of an incredible round of innovation, not just in technology, but in deal-making, partnerships, alliances, and financing, all by the hyperscalers trying to meet this insatiable AI demand. We're seeing these companies undertake some very innovative, bold, distinctive new strategies to build the capability and capacity to get these AI data centers built out to meet this insatiable demand. 00:49 — Google Cloud did a joint venture with Blackstone, in which Blackstone invested $5 billion into the joint venture. We have seen Amazon issue a series of debt and bond offerings totaling over $100 billion. AWS has said that in calendar year 2026 it will spend $200 billion on CapEx, most of which is going into AI data centers. Oracle announced $50 billion in debt and equity financing. 01:57 — This funding, this raising of funds to build out the data centers, is because there is, among these hyperscalers, over $2 trillion in committed contracted business. While Oracle right now is the smallest by revenue of the hyperscalers, it has the largest backlog, and in order to meet that, it has to spend a lot of money to build the capacity. 02:46 — Microsoft is using proceeds from its brilliant early relationship with OpenAI to help secure some of the funding. Under a newly restructured agreement between the two companies, Microsoft now will receive 20% of OpenAI revenues for the next few years. Plus, Microsoft has a huge ownership stake in OpenAI. 04:17 — Remarkable things are going on here as the technology buildout by all these companies has helped create this incredible demand. What we're seeing now is extraordinary efforts by the hyperscalers to combine with other companies, move into different industries, and do everything possible — at staggering expense — to meet this insatiable customer demand for AI. Visit Cloud Wars for more.

In today's Cloud Wars Minute, I look at how reasoning-focused AI will strengthen SAP Joule agents with enterprise-grade security and governance. Highlights 00:03 — SAP has partnered with Giotto.ai to explore the integration of Giotto.ai's AI reasoning capabilities into SAP Joule agents. Now, for some background, Giotto.ai is a Swiss AI company that has developed compact, reasoning-focused AI models designed for deployment in secure and controlled enterprise environments. 00:25 — Quick recap here: reasoning-focused AI models are designed not just to generate answers, but to really work through problems in a more structured and logical way before giving a response. The partnership will initially focus on pilot projects aimed at enhancing SAP Joule agents in enterprise scenarios that require structured reasoning, reliability, and integration with enterprise data. 00:50 — The collaboration will also serve as an opportunity for Giotto.ai to validate its technology in demanding real-world business environments. According to CEO Aldo Podestà, the partnership will demonstrate the practical value of the company's reasoning-focused models in an enterprise setting. 01:10 — For SAP, the collaboration provides an opportunity to explore how reasoning-focused AI can enhance its enterprise agents, particularly in use cases that require dependable decision support and close integration with the business data processes available there. 01:29 — For SAP customers, the partnership could result in AI agents that provide more reliable recommendations, better decision support, and greater automation of more complex business processes, critically, and this is the USP of Giotto .ai critically, while maintaining enterprise-grade security and governance. Visit Cloud Wars for more.

As enterprise AI rapidly evolves from isolated assistants to autonomous systems capable of executing complex business processes, organizations are looking for practical ways to turn AI into measurable business outcomes. In this episode of Cloud Wars Live, Bob Evans speaks with Chris Leone, Executive Vice President of Oracle Applications and AI, Oracle about Oracle's latest innovations in Fusion Agentic Applications, the new Fusion Builder Experience, and AI Studio Skill. Leone explains how Oracle is combining enterprise applications with AI agents to automate work, empower both business users and developers, and help organizations accelerate AI adoption while maintaining enterprise-grade security and governance. AI That Delivers Outcomes The Big Themes: Outcome-Driven AI Changes Everything: Oracle's vision for agentic AI begins with a simple premise: enterprise software should no longer focus primarily on completing tasks — it should focus on delivering business outcomes. Leone explains that Oracle has intentionally designed Fusion Agentic Applications around measurable objectives rather than individual transactions. Instead of asking users to manually coordinate dozens of activities, organizations define a goal, such as reducing supplier spending or shortening inventory lead times, and the application orchestrates the work required to achieve it. Teams of AI agents collaborate, monitor progress, recommend next steps, and increasingly automate execution while keeping humans involved whenever appropriate. Autonomous Work Is Gradual: Oracle isn't advocating for immediate, fully autonomous enterprises. Instead, Leone introduces the idea of an "autonomy dial" that organizations can gradually increase as confidence grows. Initially, AI agents recommend actions while employees remain responsible for approvals and execution. Over time, companies can allow the system to automatically perform more routine work while humans supervise exceptions and strategic decisions. Leone illustrates this using Oracle's Sourcing Command Center, where customers establish objectives like lowering supplier costs or reducing lead times. The application identifies shortages, creates RFQs, manages supplier auctions, recommends winners, and continuously guides employees throughout the process. As organizations become more comfortable, more of these steps can execute automatically. This phased approach helps customers balance productivity gains with governance, compliance, and trust while steadily reducing repetitive work and allowing employees to concentrate on higher-value business decisions. Customers Are Moving Fast: Leone describes Oracle's customer base as spanning the full spectrum of AI adoption. Some organizations are already experimenting aggressively with Oracle's newest Builder Experience, posting demonstrations almost immediately after release. Others have successfully deployed Oracle AI capabilities into production, with more than 7,000 customers already using Oracle AI services. Still, others remain cautious, focusing primarily on traditional transactional systems while gradually evaluating AI opportunities. Despite these varying adoption rates, Leone believes Oracle must continue innovating at the leading edge because tomorrow's competition may come from AI-first startups rather than traditional enterprise software vendors. The Big Quote: "We're truly moving from this system of record that we've been delivering for many years to truly delivering outcomes for our customers." More from Chris Leone: Follow Chris Leone on LinkedIn or send a message via Oracle AI for Fusion Applications.   Visit Cloud Wars for more.

In today's Cloud Wars Minute, I compare Microsoft's and AWS's dramatically different branding strategies for AI deployment services. Highlights 00:01 — We see here, in the unfolding AI Deployment Wars, some interesting naming conventions from Microsoft and AWS. And if you look at the comparison of these two, I wonder what they were hoping to achieve by this. I mean, I'm sure they wanted to have these names resonate clearly with people, but they picked wildly different names. 00:48 — AWS calls it Forward Deployed Engineering. Now, that is wildly unimaginative, but it's very clear. This is what you're going to get: forward-deployed engineers. That's the heart of it. It'll be both AWS's own FDEs and also some partners. They have three different tiers of services that customers can tap into. 01:22 — Microsoft is calling its company Microsoft Frontier Company, and I think, in a way, that's a little bit of a cross between Star Trek and Little House on the Prairie. Microsoft is sort of positioning this like companies really want to be the first in their field, out on the frontier. 03:13 — I think what business leaders are looking for isn't so much about frontier. What they want is: let's make this stuff work. Let's make it work clearly. Let's show quantifiable results. Let's get our culture right. Let's get our processes optimized. Let's get not only costs taken out of the company, but let's get new revenue streams building here. 04:07 — So I guess, of the two, if I had to pick one that I think was better, I'd have to give the nod to AWS. They're not going to try to impress anybody. They're not going to try to confuse anybody. You want this? This is what it is. So we'll see how this all plays out. But wild times are coming along here. Visit Cloud Wars for more.

As artificial intelligence accelerates both innovation and cyber risk, organizations are facing unprecedented pressure to secure sensitive data while deploying AI at scale. In this episode of Cloud Wars Live, Bob Evans speaks with Vipin Samar, SVP, Software Engineering, Database Security, Oracle, about Oracle's expanded AI security strategy and how the company is helping customers defend against increasingly sophisticated AI-powered attacks. Samar explains Oracle's three-part security philosophy and why removing barriers to rapid patching and risk assessment has become essential in the emerging era of agentic AI. Winning the AI Security Race The Big Themes: AI Has Fundamentally Changed the Cybersecurity Landscape: Vipin Samar argues that artificial intelligence has dramatically shifted the balance between defenders and attackers. While organizations are rapidly adopting agentic AI to improve productivity and automate business processes, the same advances are empowering cybercriminals. Modern large language models can now write software, analyze applications, identify vulnerabilities, and even recommend methods for exploiting those weaknesses. Tasks that once required highly trained hackers and weeks of effort can now be completed in hours by individuals with far less technical expertise. Speed Has Become a Critical Security Requirement: One of the interview's strongest themes is that cybersecurity now operates on AI timelines rather than human timelines. Samar explains that attackers no longer wait weeks or months to exploit newly discovered vulnerabilities. AI allows them to identify weaknesses, analyze patches, and develop exploits almost immediately after updates become available. That makes rapid patch deployment essential. Oracle is responding by simplifying and accelerating the entire patching lifecycle through automation, database lifecycle management tools, application testing capabilities, and deployment technologies that reduce operational complexity. Oracle Is Removing Adoption Barriers: Oracle's strategy extends beyond developing new security technology. Samar explains that many organizations delay implementing security improvements because of procurement hurdles, lengthy approval processes, limited budgets, or concerns about operational disruption. Oracle is attempting to eliminate those obstacles by making several enterprise-grade security products available free for a limited time, including Oracle Data Safe, Database Security Assessment capabilities, Database Lifecycle Management Pack, and Exadata Management Pack. Visit Cloud Wars for more.

In today's Cloud Wars Minute, I compare Google's ecosystem-first AI strategy with the hybrid deployment models of Microsoft and AWS.Highlights 00:03 — A crazy new trend here in 2026 has been AI deployment, or agent deployment, agentic transformation. The connection is this remarkable technology that all these AI companies have been pumping out with the desired business goals that business leaders are demanding. You see a couple of different approaches emerging here. 00:26 — The five big AI companies leading the way on this are Google Cloud, Microsoft, AWS, OpenAI, and Anthropic. The only one of those that is going with an exclusively partner ecosystem-led approach for these AI deployments is Google Cloud. I think the big thing is it's going 100% with its ecosystem partners for these AI deployments, for what Google Cloud calls agentic transformation. 01:51 — President, Global Partner Ecosystem, Kevin Ichhpurani has been a very successful in his efforts. He's also been a staunch supporter of this [approach], he says: "We're a technology company. We're really good at doing the technology, and we want to surround ourselves with force multiplying partners who are really good at the deployment. And Google Cloud will be connected with them in some ways." 03:16 — Partner-driven revenue was up 80%. Bookings driven by partners were up 100%, so they doubled. And sales of partner-created solutions on the Google Cloud Marketplace were up 90%. As high-growth as Google Cloud was in 2025, they're moving and growing, expanding at an even more blistering pace here in 2026. 04:36 — Google Cloud has said, "Hey, what we've been doing so far has been working really well. We're going to double down on that with lots of training and incentives for our partners," whereas AWS and Microsoft say, "You know what? We're going to keep working with partners. In some ways, we need to build our own capabilities and expertise." Visit Cloud Wars for more.

Key Takeaways Solgari's leading innovations: Grant explains that Solgari provides a customer engagement platform built on Azure that extends Microsoft Teams and Dynamics 365 (as well as other CRMs) to capture customer conversations and centralize that data for better engagement. Customers are adopting it to quickly solve specific engagement challenges, gain fast ROI, and apply it to AI strategies to drive more intelligent business outcomes. AI's role in customer engagement: Companies that centralize customer conversations into a single data platform gain an advantage because AI is only as effective as the data it can access. Grant says customer engagement is "ground zero for AI" as it enables capabilities like automation, sentiment analysis, and sales or service intelligence that improve customer satisfaction, reduce costs, and deliver measurable ROI. Use case: Grant shares details on Solgari's involvement with AMB Sports & Entertainment, who own the Atlanta Falcons. Solgari helped them unify fan engagement across voice, SMS, email, and WhatsApp within Microsoft Teams and Dynamics 365, creating a repository of fan conversations in Dataverse. By consolidating this data, AMB Sports & Entertainment is now well positioned to "create momentum around their AI strategy." Final thoughts: In closing, Grant shares why Solgari has shifted its customer and partner conversations away from product demos and toward business outcomes, showing how customer engagement data can evolve into valuable AI use cases over time. Visit Cloud Wars for more.

In today's Cloud Wars Minute, I explain why the next phase of agentic AI is all about governance, security, and business processes. Highlights 00:03 — Salesforce has expanded its partnership with Databricks to help organizations better connect enterprise data with business outcomes in the era of agentic AI. At its core, the expanded partnership is about recognizing that as AI agents take on a larger role across the enterprise, they need access to complete, connected data that's paired with business context, security controls, and enterprise processes. 00:51 — Access to data alone really is not enough for AI agents to deliver meaningful business value. "Customers consistently tell us they want AI agents to become a larger part of how work gets done across the enterprise," said Andy Kofoid, President of Global Field Operations at Databricks. "To make this a reality, they need access to trusted data, business contexts, and governance controls wherever that information lives." 01:32 — "Together, Salesforce and Databricks are helping customers connect governed data and business contexts across platforms, giving humans and agents the shared foundation they need to search, reason, and act with confidence." 01:46— I think this partnership is, yet again, part of a pattern that's emerging here. It's representing a broader shift that's taking place across the AI industry as organizations move beyond experimentation and toward large-scale deployment of AI agents. 02:00 — As this is happening, success really depends less on the models and more on the ability to unite these agentic capabilities with data governance, security, and business processes. Salesforce and Databricks are betting that enterprises need all of those elements working together cohesively if agentic AI is to deliver on the promises it has made. Visit Cloud Wars for more.

Minute, I look at how Google Cloud, Microsoft, AWS, OpenAI, and Anthropic are redefining enterprise AI adoption. Highlights 00:11 — So, in what I'm calling the AI Deployment Wars, we see the five largest AI companies — that is, Google Cloud, Microsoft, AWS, OpenAI, and Anthropic — are now all saying, or realizing, that in addition to this incredible technology they're pumping out, they have to actually ensure that all that cool stuff works for customers and that it delivers quantifiable business outcomes. 01:29 — One, we see these tech companies, who've always said, "I don't want to be in the services business," now they have to get a little bit into the services business. They are all relying on the coolest three-letter acronym of the year, FDE, for forward deployed engineers, and they're all saying they're doing this to help customers, to co-create and collaborate with customers. 02:22 — So first, Google Cloud, number one on the Cloud Wars Top 10, it announced a $750 million ecosystem fund to help partners develop agentic AI applications and capabilities that will help its customers get up to speed. OpenAI, $4.15 billion that it's investing in this — $4 billion so far itself, and outside investors have put into a new deployment company. 03:03 — Anthropic, it's about $1.5 billion, and all these companies, other than Google Cloud, it's a combination of forward deployed engineers and partners. AWS said, "We're going to put a billion dollars into it." Microsoft, $2.5 billion. It's calling it's the Microsoft Frontier Company. These numbers here together add up to $9.9 billion. I rounded up to $10 billion. 04:02 — They're (customers are) saying, "We're spending a lot of money on it, we're devoting a lot of time, we're devoting a lot of thinking and energy and focus to this, but we're not seeing the tangible business outcomes." We need to get this deep-seated engineering capability from these big tech vendors to ensure that these new AI transformation initiatives aren't just talk. Visit Cloud Wars for more.

In today's Cloud Wars Minute, I explain why Microsoft's newest AI initiative could reshape enterprise engineering and customer success. Highlights 00:09 — Some huge news from Microsoft today. The company has launched Microsoft Frontier Company, a brand-new business that's entirely focused on helping customers achieve frontier transformation with AI. 00:28 — Now, Microsoft, despite not coining the term [Frontier Firm] itself, has been using it extensively to really outline its strategy in terms of how it sees its AI tools transforming companies, essentially enabling them to become frontier firms. This Frontier Company, to me, feels like the culmination of all that forethought and clarity around Microsoft's enterprise AI mission. 00:56 — Microsoft is investing $2.5 billion into the initiative, which will see 6,000 industry specialists and AI engineers embedded into customer organizations to help them co-design, deploy, and continuously improve AI systems. You can think about it as forward-deployed engineering, but on a much broader scale. 01:19 — Judson Althoff, CEO of Microsoft Commercial Business, calls it the "largest, most capable, outcome-driven engineering organization in the industry." Ultimately, Althoff explained the aim of Microsoft Frontier Company is to focus on end-to-end frontier transformation and enable customers to "amplify their IQ with AI while refining their differentiated value in the markets that they serve." 01:51 — Microsoft has said it will be working closely with its partner ecosystem, particularly with partners including Accenture, Capgemini, EY, KPMG, and PwC, to scale the company, extend its capabilities to organizations across many sectors globally. It's an incredibly interesting and strategic move from Microsoft, and one that I'll be following up with a deeper analysis in a written article publishing shortly. Visit Cloud Wars for more.

In this episode, I consider an argument that Palantir recently made: While traditional ERP has been valuable for many businesses over the last few decades, as we move into the AI Economy, is it possible that some of the rigor, discipline, and standards that traditional ERP has brought to organizations and their processes are beginning to cause a problem? Highlights 00:58 — Palantir challenged traditional ERP in a recent blog post. Although there's a great value it can offer, the company prompted the idea that too much standardization — in the current economy, which is very fluid, and in the age of AI — can become a problem. 01:44 — Standardization leads to everything being uniform. So, how do companies stand out? Palantir noted that uniqueness is not a bug that software should erase but rather a feature that keeps you ahead. Another note it made was that it means sacrificing the organization's identity, its differentiated processes, and the ways it creates value for customers. 02:34 — This isn't a case of Palantir saying that ERP overall is bad; it's the mindset and how the business operates. Now, we have to pick and choose where the approach of standardization applies. This overly standardized traditional ERP approach is going to stifle the ability of companies to create competitive advantage by those unique capabilities, qualities, and personality that traditional ERP, in the view of Palantir, stifles. 03:42 — In its blog post, Palantir suggests a solution to this, that the company can help customers interconnect these new ways of doing things — a modern layer with traditional ERP. Palantir is deepening its partnership with SAP so they can deliver greater capabilities to customers. Visit Cloud Wars for more.

In today's Cloud Wars Minute, I explore Microsoft's shift to usage-based Copilot Cowork pricing and what it reveals about the changing economics of enterprise AI. Highlights 00:10 — Microsoft is moving Copilot Cowork from a fixed-price subscription model to usage-based pricing, and this is really reflecting the fact that heavy users are racking up massive compute costs compared to others. 00:55 — More and more, the focus is shifting to how organizations can scale those (AI) capabilities in a way that's financially stable, but beyond that, Microsoft has also said that it's considering a Microsoft-hosted version of DeepSeek as a lower-cost model alternative. 01:16 — Right now, at the moment, Copilot Cowork workloads are powered by models from OpenAI and Anthropic. We should expect to hear from Microsoft regarding DeepSeek, or another low-cost model choice, within the coming weeks. 01:32 — So, what are we really seeing here? Well, Microsoft's AI strategy is evolving beyond simply offering access to the most powerful models. Increasingly, it's about giving customers the right balance of performance, economics, and choice. 01:49 — This is also highlighting, for me, a big divide between how governments and businesses view the AI race. Governments often frame this AI race as a competition between nations, but enterprises are more likely to focus on which models deliver the best outcomes at the lowest cost for their customers. Visit Cloud Wars for more.

In today's Cloud Wars Minute, I examine what OpenAI's latest move reveals about the maturation of the enterprise AI market. Highlights 00:03 —My colleague Bob Evans has already covered the specifics of OpenAI's new partner network, so I don't want to spend too much time on the ins and outs of the program itself today. Instead, what I want to do is focus on what this announcement really tells us about the wider state, the broader state of the AI market. 00:25 — Now, for much of the past two years, the conversation around AI has focused on models, questions like: "Which model is best? Which company is ahead? How quickly are capabilities improving? Now, while those questions still matter, they're not the most important ones for many enterprises today. The challenge is more about scalable deployment. 00:44 — Most large organizations have already experimented at this point with AI in some way. They've run pilots, they've tested use cases, and identified areas where AI can really create value for them. The issue now is turning those successes into a scalable business strategy. 01:17 — And that's why OpenAI's partner network matters in this instance. For me, the announcement is less about OpenAI launching another program and more about the company realizing that, although it has the technology, that alone isn't enough for companies to scale in the AI era. They need an ecosystem that includes consultants, partners, and specialists as well. 01:49 — The winners in this next phase will not necessarily be the organizations with access to the most powerful models; they'll be the ones that can successfully embed AI into day-to-day operations and generate real business outcomes. When you look at it like this, OpenAI's partner network is not just a new customer program, it's a sign that the industry is entering a new chapter. Visit Cloud Wars for more.

In today's Cloud Wars Minute, I discuss the growing challenge of balancing AI demand, budgets, and business priorities across the enterprise. Highlights 00:02 — We’ve got an emerging dilemma here for CEOs in the early days of the AI Revolution, and a new solution from OpenAI has brought that to light. The dilemma is this: when everybody wants AI tokens, as many as they can get, as quickly as they can get them, but AI tokens are in limited supply, who gets them? Who decides that? How do companies measure that? 00:54 — So, OpenAI has come out with a new tool. This new solution from OpenAI is aimed at AI administrators, so they can sort of turn them on and off, see who’s using what, which ones align with business impact, more over here, less over here. As a tool, that’s all great. But who sets, on high, the policies that those AI admins then can use as their guide? 01:47 — The current state of reality in the marketplace is that the technology is outpacing a lot of corporate cultures. Perhaps there are some CEOs who have sat down with their executive teams and very rigorously hammered this out: a very clear, transparent policy. The current state of the market, though, is one where I don’t see that happening in too many places. 02:49 — The problem sits on top of that solution. Who sets the policies that the AI admins will then follow? You’ve got salespeople over here screaming, “I need more,” product development saying they need more, marketing saying they need more, and every part of the company saying, “I need more.” Who sets the guidelines for how that is determined? 03:30 — The enormous burden is resting on the shoulders of AI administrators who are just not equipped to see across the company and determine where these resources should go. For CEOs, the AI clock is ticking, not only to set a high-level strategy, but also to build the culture that allows companies to be successful in the AI Revolution and AI economy. 04:33 — Great tool from OpenAI, but there’s got to be a lot of education done at the top level for customers. As AI tokens begin to be recognized as incredibly valuable, companies may need entirely new approaches to allocation, governance, and business prioritization. Visit Cloud Wars for more.

In today's Cloud Wars Minute, I examine three very different approaches to turning breakthrough AI technology into real-world business transformation. Highlights 00:11 — The AI Deployment Wars involve Google Cloud, OpenAI, and Anthropic. Each has evolved from being almost lab-focused companies with tremendous AI models, and now the pace of innovation of these models is remarkable. The capabilities, power, is stunning, but what that leads to is a huge demand among customers now to not just slip in a piece of technology, but to change companies dramatically. 00:45 — So, that's why the focus here now is on these Deployment Wars. I want to take a look at the three different approaches that these companies are taking. How are they going to take this very cool technology and turn that into customer success at the point of deployment for these customers? There are different approaches here. Money's not the issue here. 01:45 — The challenge is, how do they set themselves up to be not just great creators of technology, but deployment enablers for some of the world's largest companies doing unbelievably complex projects and betting their futures on AI? The technology is enabling the real goals, which are transformation and the ability to move and grow quickly. 02:21 — How are they going to ensure customer success at every level? How are they going to change the processes companies have, the way they do business, the mindset, the technology, the opportunities they have, the strategy, and the cultures of these companies? How are they going to tackle technical challenges that nobody has really ever handled before? This is remarkably different. 03:56 — Google Cloud is going to go almost exclusively with partners. Both Anthropic and OpenAI are saying that they have both funded, along with a lot of partners, deployment companies that will use deployed engineers who are employees of either OpenAI or Anthropic out at the point of the customer to complement or supplement some of what partners are doing. Visit Cloud Wars for more.

In today's Cloud Wars Minute, I discuss how one of the Big Four consultancies is using Microsoft technology to simplify AI scaling for customers worldwide. Highlights 00:10 — Some big partner news today: KPMG and Microsoft are expanding their existing partnership to help firms scale agentic AI initiatives. Another example of how far things have progressed in a few short years, as companies become increasingly AI-mature and start to incorporate these transformational technologies across their businesses. 00:34 — Within the new agreement, KPMG will leverage Microsoft 365 Agent to enhance its trusted AI framework in order to help KPMG clients deliver agentic AI across their enterprises, while KPMG member firms will also be deploying Microsoft 365 Copilot on a global scale, totaling over 267,000 users. 01:02 — So, a massive rollout of Copilot there. But the big story here is how KPMG is further integrating, this time from an agentic AI stance, Microsoft technology into its client service delivery platforms. What this means is that it's making it easier for KPMG clients to scale AI because of the consistency this provides. 01:25 — It's consistency, governance, deployment, management, and production, and that's the real customer benefit here. This is a deepening of the relationship between Microsoft and KPMG. 01:36 — I think partnerships like this are so important because the amount of options and strategies for AI deployment is really quite mind-boggling. So, when you have one of the Big Four consultancies showing the way, using a consistent set of tools in-house and with its customers, the outcomes are just going to be that much better. Visit Cloud Wars for more.

In today's Cloud Wars Minute, I explain how AWS is using AI-driven automation to reduce technical debt and free up budgets for innovation. Highlights 00:03 — As the AI Revolution has kicked into full swing this year, we've heard a lot of stories — interesting ones — about companies blowing through their AI budgets because everybody loves this stuff; everybody wants to use it. That brings up this notion of technical debt. 00:46 — AWS has introduced an autonomous tool that's primary job is to slay the technical debt monster that is grinding up so much of so many companies' IT budgets and limiting their abilities to do the things going forward that they need to do. It said it consumes 30% of IT budgets, and this is a staggering number. 01:51 — This party that's been going on here now — the big AI kegger during the AI Revolution — is going to come to an end. And what always follows those parties is a hangover. That hangover is going to be centered on technical debt, budgets, and money decisions that have to be made. 02:44 — AWS gave a list of some of the benefits of it [the tool] but, AWS is missing a huge audience, business people who say, “God, we're spending incredible amounts of money on IT. Why are we not getting as much sort of innovation oomph out of this?” It's because so much has to be spent to sustain this already in place technology that's there, the technical debt that builds on that. 04:33 — I think AWS has to find somebody to package this as an agent, that if they call this agentic AI, it goes from being some sleepy thing with a ho-hum name to something that could be very cool. It's the technical debt killer agent, something like that. This is what it does: it autonomously operates, takes care of stuff, makes decisions, evaluates data, does all that. Visit Cloud Wars for more.

Highlights 00:08 — Now, in a slight tangent away from what we're used to from Microsoft, the company is developing two new AI-powered gadgets for workers that tap into AI for daily tasks. Both are currently in the concept stage. 00:22 — The first is a small cube designed to sit on a desk that can be activated by voice or touch. Second is a wearable access badge that would give wearers access to AI-driven workflows. Now, the two devices are already being used by a couple of hundred Microsoft employees, but the company has not said when they'll become commercially available. 00:44 — Both were showcased at the recent Build conference. They're part of Microsoft's Project Solara, and here's what Stephen Pattison, CVP and Technical Fellow, Applied Sciences Group at Microsoft, had to say about the overall project. 01:07 — "The mission of Project Solara, a new software platform coupled with tailored hardware solutions, is to pioneer agent-first experiences that are shaped around you, your agents, your tasks, your environment, under your control." 01:27 — "These new devices are not meant to run traditional apps. They're designed for agents, and that shift gives us more flexibility in the user interface because the experience can adapt to the device, screen size, content, and even the mode of interaction, whether visual, voice, touch, or multimodal." 02:07 — I think it's particularly interesting that Microso Visit Cloud Wars for more.

In today's Cloud Wars Minute, I look at why two of the fastest-growing Cloud Wars companies are joining forces around data, AI, and industry solutions. Highlights 00:03 — When heavy weather rolls in, it's good to have friends around. It's good to have partnerships, and I don't think the AI Revolution is so much heavy weather, but that depends on how well prepared businesses are to take advantage of it, how aggressively, how thoughtfully they're moving into this AI Revolution. 00:41 — It's interesting, Google Cloud and Palantir, on the Cloud Wars Top 10, these are the two fastest-growing companies. Google Cloud grew 63%; Palantir grew 70%. Palantir's commercial business grew 133% in the first quarter, so they've got enormous momentum. 01:30 — The Palantir Foundry platform for enterprise data management is now available on Google Cloud infrastructure and on the Google Cloud Marketplace. Google Cloud and Palantir have built connectors between Foundry and Google Cloud's BigQuery, allowing data from those platforms and others to be pulled together for businesses to analyze. 02:09 — Not just the technical integrations, which have to happen, but also this desire for these two companies to say, "We're going to jointly develop industry-specific solutions around data and AI for vertical markets." The first two they picked are retail and financial services. 03:15 — This is a dream partnership, I think. And it's also probably an example of how, with the enormity of the prospects of what can happen here in the AI Revolution, we're going to see more of the Cloud Wars Top 10 companies form these sorts of wide-ranging partnerships. 04:19 — There's a big emphasis from both of these companies on keeping things open and fully accessible for whichever specific routes customers want to take. We're seeing these inextricably bound connections here through this partnership of data, which is the fuel for AI, helping companies transform into AI-powered enterprises. Visit Cloud Wars for more.

Highlights 00:27 — It's not just business as usual for these companies, their customers, and others who are tied into these extraordinary enterprises. We're also seeing booms in innovation, not just in technology but in go-to-market models, business models, and more. 01:32 — The big part of this is that it's not just big numbers, but big numbers driving widespread, deep, and profound innovation. Here's how the $2.1 trillion breaks out across the four hyperscalers: Backlog RPO Total Backlog RPO Growth Rate Oracle $638 Billion 363% Microsoft $627 Billion 99% Google Cloud $462 Billion 93% AWS $364 Billion 49% Total $2.091 Trillion   02:32 — With this high level of innovation, we're seeing a convergence of industries including technology, energy, and construction. Because of extreme demands, the tech industry has to start getting into the energy business. Construction is entering the picture as well, as these facilities are some of the largest built in such a short period of time, meeting demanding specifications and aligning with supply and demand. 03:25 — This convergence is leading to the hyperscalers developing new business models. These companies are coming up with unique models to solve this unprecedented demand and business challenge. Customers are coming up with different models based on what's happening, too. 04:15 — I have been a huge fan of the potential of fusion energy to meet this need. The convergence of tech and energy is only going to accelerate what's happening to break even with fusion energy. Visit Cloud Wars for more.

In today's Cloud Wars Minute, I examine why the Google Cloud-EQT deal signals a major shift in how AI is being distributed at scale. Highlights 00:03 — The rapid pace at which deals are being struck and portfolios are expanding among the leaders in the race for AI dominance isn't new. Significant partnerships are being forged, and contracts are being signed all the time. However, every so often, a deal comes along that stands out not only for its scope, but also for what it indicates about the direction of travel for the industry as a whole. 00:33 — One such deal recently announced is between Google Cloud and the Swedish private equity firm EQT. Ultimately, this partnership sees EQT commit to accelerating AI adoption through Google Cloud for over 300 companies within its portfolio, and this is, of course, a big win for Google Cloud, as it gains access to hundreds of potential enterprise AI customers. 01:04 — Beyond this, those companies will not only benefit from Google Cloud's wide-ranging AI offerings, including the Gemini Enterprise agent platform, as well as its cybersecurity portfolio, but also from its vast partner network, which includes over 330,000 consultants from major firms like Deloitte and KPMG. 01:27 — For me, the biggest takeaways here are that, firstly, agentic AI is clearly going mainstream, with equity firms eager to roll it out among their entire portfolios. We're obviously well past the experimentation phase now. 01:42 — Secondly, this really presents a major opportunity for AI infrastructure companies to leverage this growing acceptance to enhance AI distribution at the portfolio level. This shift could result in AI adoption accelerating much faster than when companies go down the traditional enterprise sales route. Visit Cloud Wars for more.

In today's Cloud Wars Minute, I look at how OpenAI is transforming from an AI innovator into a full-scale enterprise powerhouse. Highlights 00:02 — Well, a couple weeks ago, we talked about some moves made by OpenAI to capitalize on its booming business in the enterprise. One of the things, just to offer some context here, is OpenAI said about a month ago that 40% of its revenue now comes from the enterprise, but by the end of the year, it expects that to be 50% enterprise business. 00:56 — It's added a million business customers in the last 12 months. They want to rapidly get to the right business outcome. OpenAI has launched a couple of go-to-market initiatives here, focused around deployment, and it's doing this in two separate, closely coordinated, ways. 02:06 — It's going to be with them deeply to help guide these AI transformations. OpenAI has set up a $150 million fund in this OpenAI Partner Network to support the initiatives of these partners as they go through, to help them move quickly, get the resources they need, and establish the right sort of capabilities to work with customers to get these high-level outcomes. 02:32 — Also, the OpenAI Partner Network says that it wants to certify 300,000 consultants by the end of the year on OpenAI's technology for businesses. We're about halfway through the year, so roughly that's close to 50,000 certified consultants per month starting July 1 through the end of the year. That's a very ambitious pace. 03:21 — Now, the second part of this two-part deployment effort is the OpenAI Deployment Company, launched about a month ago. This is one where OpenAI is the majority owner, but they've also taken lots of outside investments from other companies, including investment firms, consultancies, and systems integrators. 03:28 — Currently, the forward deployed engineers have come from OpenAI's acquisition of Tomorrow. That is an AI engineering and deployment company that currently has 154 deployed engineers, and OpenAI says they want to crank that up to 250 very rapidly. Visit Cloud Wars for more.

In today's Cloud Wars Minute, I break down how DynaTech Systems enabled Solmax to turn operational complexity into global efficiency with D365, Power BI, and Microsoft Fabric. Highlights 00:03 — Today I want to take a bit of a dive into a specific case study: the story about the impact of digital transformation enabled by one company on the business outcomes of another. I love having the opportunity to explore stories like this because, as important as it is to discuss the technology itself, how it's implemented and what that implementation can lead to is just as critical. 00:41 — Solmax is a leading geosynthetics manufacturer focused on civil and environmental infrastructure, operating across four continents through 32 legal entities. This broad reach, although great from a growth perspective, was creating challenges such as data silos, inconsistent processes, and a lack of standardized reporting, which affected financial and operational insights. 01:08 — Beyond this, manual processes led to inefficiencies. Complex sales price calculations hindered productivity, and reliance on outdated Microsoft systems resulted in slower Power BI report refresh times. To address these challenges, Solmax had a core goal: the One Organization, One Data, One Reporting initiative. 01:52 — DynaTech has a number of solutions it will tailor to suit the outcomes of an individual client. In the case of Solmax, the company opted for its finance optimization solution. After process consulting, DynaTech enabled a greenfield implementation of D365 Finance and Supply Chain Management with unified processes across 32 entities. 03:17 — Beyond this, unified real-time dashboards enhanced global reporting, supported faster decision-making, and improved the company's audit readiness. Solmax was able to reduce freight costs, accelerate delivery cycles, improve truck utilization, minimize penalties, and shorten accounts payable and receivable processing times. Less manual intervention meant fewer errors. Visit Cloud Wars for more.

In today's Cloud Wars Minute, I look at how Oracle's leadership transition reflects Larry Ellison's long-term succession plan. Highlights 00:05 — I wanted to mention here that after 40 years, the long-running show called Larry Ellison's Story Hour has ended. Now, I'm taking a little bit of license here. The Story Hour was the quarterly earnings call for Oracle, and it was 40 years ago that Oracle went public. 00:30 — While he would certainly talk occasionally about the numbers, the financial results, he used those occasions, those earnings calls, to tell the stories of what was going on not just within Oracle, but in the outside world, the direction in which technology was headed, where the business world was headed, and then where the technology was following. 01:15 — Larry Ellison did not make any opening remarks for the first time in 40 years. Last week on their Q4 earnings call, Ellison wasn't even on the call itself. The three executives handled everything. I believe they did a great job, so no disrespect toward them, but it's just kind of not going to be the same. 02:24 — In about two months, Larry Ellison is going to have his 82nd birthday. He has been building up to this moment for about the last 12 years. Larry Ellison, I think, clearly believes he does not need to be on these earnings calls anymore because the company is in great hands with its new CEOs. 04:10 — I am not trying to say that Larry Ellison is riding off into any sunset, but I do think it was just a momentous occasion here when he decided 40 years of the Larry Ellison Story Hour on these earnings calls is enough, and time for a new chapter. Larry Ellison has a lot of work in a lot of different areas, and clearly he is deeply focused on them. Visit Cloud Wars for more.

In today's Cloud Wars Minute, I compare Oracle, Microsoft, Google Cloud, and AWS through the lens of backlog growth and future demand. Highlights 00:02 — I talked last week a little bit about Oracle's Q4 results, very strong across the board. I wanted to go into a little more detail today about one number in particular: its RPO, remaining performance obligation. That's contracted business not yet recognized as revenue. 00:18 — Some people refer to it as RPO. It's also known as pipeline or backlog. But with what Oracle reported for Q4, its AI and cloud backlog, pipeline, or RPO is now the largest in the world: $638 billion. It's even bigger than Microsoft's. This reveals a lot about who's got momentum into the future. 01:02 — So, as I said, Oracle's RPO for the quarter ended May 31 was $638 billion, up 363%. A couple of months ago, when Microsoft reported its fiscal Q3 and calendar Q1 numbers for the period ended March 31, it reported RPO of $627 billion, up 99%. So, Oracle beats them slightly on total RPO, but look at the difference in the growth rate: 99% versus 363%. 02:20 — But when we flip the arrow of time from the recent past, which revenue reflects, into the future, that's where we see Oracle is just winning an outlandish share of the business going forward, even more than Microsoft. We're seeing more and more of that pipeline, or RPO, over time convert to revenue for both of these companies. 03:40 — These are multiplier effects, and again, my point here is about who's growing faster and who is moving into leadership positions going forward. Clearly, as Microsoft and AWS led the first chapter of the cloud, here in the AI chapter, the leaders jumping out in front, growing faster, and finding new ways of doing things are Oracle and Google Cloud. 04:12 — Speaking of AWS, how does it fit into this whole RPO tale of the tape? AWS refers to this as backlog, and in its most recent quarter, ended March 31, it said that its backlog was $364 billion, up 49%. For Google Cloud, its backlog is $462 billion, growing at 98%. So clearly, all three companies are outperforming AWS in this backlog/RPO space. Visit Cloud Wars for more.

In this Cloud Wars Special report, Bob Evans speaks with Jan Gilg about how AI is reshaping enterprise software and why the next phase of innovation will depend on trust, governance, business outcomes, and clean data. Gilg explains how SAP is positioning its Autonomous Suite as a foundation for the autonomous enterprise, combining ERP, business processes, and AI agents. Trust Powers Enterprise AI The Big Themes: Autonomous Enterprise Vision: Jan Gilg said Sapphire generated strong enthusiasm because customers finally heard a clear vision for enterprise AI. Rather than focusing solely on AI models or isolated features, SAP presented an integrated strategy built around the Autonomous Suite and Business AI. While consumer AI has dramatically improved personal productivity, enterprise leaders need AI that can help make critical business decisions and automate end-to-end processes. SAP's message resonated because it connected AI directly to business execution, positioning enterprise systems as the foundation for autonomous operations rather than treating AI as a standalone technology layer. AI Economics Matter: Another major topic was the cost of AI. Gilg noted that enterprises are becoming increasingly focused on transparency, consumption, and measurable outcomes. As AI usage expands, costs can grow rapidly, creating new concerns for business leaders. Customers want detailed visibility into which agents are being used, how resources are consumed, and whether the resulting business value justifies the expense. Gilg compared this need for transparency to a detailed telephone bill. Data Quality Determines Success: The interview concluded with examples demonstrating that AI success depends heavily on modernized systems and clean data. Gilg spoke of initiatives involving retailers such as H&M, where AI can improve customer experiences, fulfillment, and revenue generation. He also referenced work with Bayer and discussed ExxonMobil’s modernization journey. These examples reinforced a key point: AI delivers the greatest value when built on standardized processes, strong master data, and simplified architectures. The Big Quote: “You have to lead with value. Yes, technology is exciting, but it does nothing if the customer doesn't see the outcome." More from Jan Gilg and SAP: Follow Jan Gilg on LinkedIn or learn more about Autonomous Suite. Visit Cloud Wars for more.

In today's Cloud Wars Minute, explore how SAP's Autonomous Suite could become the operating system for AI-powered enterprises Highlights 00:02 — The company that more than 50 years ago really started the whole enterprise applications business, SAP, last month at its big Sapphire event rolled out the latest, greatest, newest AI-powered version of their long-running ERP suite, but this time it's called the Autonomous Suite, so that's a huge change. 00:33 — I had a chance to sit down with Jan Gilg, who's Global President for Customer Success for the Americas at SAP headquarters and asked about a number of things that customers have the opportunity to move into with this newer, more fully integrated, more AI-powered Autonomous Suite. And I know there's been some risk that SAP took in selecting this name. 01:49 — Jan's been in SAP for about 15 years. He was on the development side for a long time, and he was leading, several years ago, the development of S/4HANA and that whole version of the suite. 02:36 — We talked about this issue of trust. Autonomous is right there in the name. It's one thing for different autonomous technologies to manage things. But, when you talk about the autonomous enterprise ... we got into the discussion of what SAP has to do to build up trust among its customers. 03:28 — What's the interplay between agentic AI and applications going in both directions? Oracle can now refer to its Fusion Applications as Agentic Applications. Is SAP doing everything it can to clarify in the minds of customers where applications end and agents begin, and the same thing in the other direction? Jan has some great thoughts on that. 04:12 — Everybody in the company, I guess, was running tokens 24 hours a day. So, Jan has some good thoughts on this. And then we talked about customer examples. Let's see, there was one from the retailer H&M, there was one from a manufacturing company, and we had some different ones in here that he brought up. But he really brought some good perspectives on that. Visit Cloud Wars for more.

In today's Cloud Wars Minute, I dive into Oracle's remarkable Q4 earnings report, where the company delivered results that exceeded expectations across the board. Highlights 00:02 — We had a monster Q4 report from Oracle yesterday, absolutely crushed their numbers for Q4, led by an astonishing leap in their backlog or remaining performance obligation (RPO) of $638 billion, That's an increase of 363%. And no, those are not misprints. 00:29 — RPO represents business that's fully contracted, not yet recognized as revenue, so it's pipeline backlog, as opposed to revenue, which has already been posted for what has happened in the past. So I wanted to quickly pop out a couple highlights here that go along with that. Just remarkable RPO growth, cloud revenue overall was up 47% to 9.9 billion. 00:56 — Within that, cloud applications grew 10% to 4.1 billion, and the big star of the company, now their cloud infrastructure business was up 93% to $5.8 billion. One other number that Oracle put in its Q4 press release, that is pretty darn impressive, their multi-cloud AI database business, they said, was up 404% and they said that now makes this the fastest growing product in the company's history. 02:11 — Looking ahead a little bit, Oracle guided in Q1, they said their cloud business will grow between 57 and 63% so caught about 60% and that extends a long running streak of fast growing numbers there for Oracle's cloud revenue or cloud business. 02:33 — Oracle also said in its Q4 press release that it will be doing no more borrowing to fund its data center expansion throughout for calendar 2026, certainly possible for next year, but for this calendar year, no more borrowing. I think most people would yawn or overlook that fact. There have been a lot of folks on Wall Street, though as I've mentioned, that this has caused them fainting spells and pearl clutching, because they, nobody's done this before. 03:44 — Now, I don't know, I don't think there's a lot of companies that have run into that challenge before. It's a delightful challenge to have, but it is not something that you know a lot of companies can just, you know, reach into the petty cash box and say, you know, here's $100 billion $200 billion dollars to fund it. Visit Cloud Wars for more.

In today's Cloud Wars Minute, I analyze how Sana is helping Workday transform from a system of record into a system of action. Highlights 0:00 — Workday has announced two new agents: Sana for IT Service Management, or ITSM, and Sana Travel Agent. To recap, Workday acquired Sana at the end of 2025, and since then, the technology has evolved into Workday's employee AI layer, what the company describes as its "front door for work." 0:42 — Sana for ITSM automates workflows for tasks like employee onboarding, off-boarding, access changes, and standard IT requests, while the Sana Travel Agent helps employees plan work trips, book travel, and manage expenses. Both agents are built directly on Workday, meaning they have the same security and governance protocols by default, and tap into the bespoke contextual company data and policy information contained within the platform. 00:57 — Cloud Wars founder Bob Evans commented on the development in the official Workday press release: "Extending agents into adjacent workflows like onboarding, travel, and expenses, where Workday already has the people and finance data and policies, is not only practical but also a transformational way to help HR and finance leaders meet and exceed their objectives." 01:25 — Workday's acquisition of Sana was a pivotal moment in the company's recent history and accelerated its push in the enterprise AI era. The deal signaled a strategic evolution beyond Workday's traditional role as a system of record for HR and finance processes. 01:44 — At the same time, that deep system of record foundation is exactly what makes Sana's autonomous AI agents such a strong fit, because the agents can operate with rich context, permissions, policy, and workflow data already embedded within the platform.     Visit Cloud Wars for more.

In today's Cloud Wars Minute, I analyze how a trillion dollars in cloud backlog is driving innovation beyond technology and into corporate finance. Highlights 00:03 — In the Cloud Wars, all sorts of crazy things are going on with the technology, what customers are doing with it, but also in how this whole remarkable time is being funded. I want to talk a little bit today about how Google Cloud and Oracle are choosing to fund this unprecedented market demand and why new possibilities require new ways of doing things. 01:25 — In Oracle's most recent quarter, it reported that its RPO, or Remaining Performance Obligation, similar to backlog, is over $550 billion. For Google Cloud, it had an amazing jump as well in its most recent quarter, ended March 31, $462 billion in backlog, almost double what it had been a year before that. So there's amazing demand, these two companies totaling a trillion dollars. 02:09 — Six months ago, Oracle reached out and said, “No, no, we're going to go to some outside funding, some borrowing, to do that.” But the market reacted with a panic. “Oh my God, nobody's ever done this.” And, you know, "What if they can't pay it back?” So there was a lot of skepticism about Oracle's plan six months ago. 02:58 — Now, a week ago, we see Alphabet step up and say, “Hey, we're going to do some equity financing. We're going to take $10 billion from Warren Buffett and some other places. We need this money. We think it's the best way to pursue funding our own data center expansions, our own CapEx needs, which will be somewhere between $185 and $190 billion.” Oracle's will probably be around $75 billion. 04:37 — Oracle and Google Cloud have risen to the top of the Cloud Wars Top 10 because they brought innovation at levels in technology and go-to-market, how they think about customers, deployment models, and so forth, that have really set the new standard for what's happening in the AI cloud business now. Seeking outside funding to meet this demand shows another way to do it. Visit Cloud Wars for more.

In this special report, John Siefert, CEO, Dynamic Communities and Cloud Wars, speaks with Robbie Morrison about Velocio's acquisition of Domain Six and what the move means for customers, partners, and the broader Microsoft ecosystem. Morrison explains how the acquisition expands Velocio's enterprise capabilities, vertical-industry expertise, and delivery capacity while strengthening its ability to help organizations modernize around cloud, data, and AI. Velocio Expands Expertise The Big Themes: Domain Six Expands Velocio's Reach: Velocio's acquisition of Domain Six represents more than a simple expansion of headcount. Robbie Morrison describes the acquisition as a strategic move that adds highly skilled consulting talent, enterprise delivery capabilities, and valuable intellectual property in specialized vertical markets. Domain Six brings expertise in areas such as rental businesses and professional services, allowing Velocio to broaden its market reach while deepening its industry-specific knowledge. Consulting is fundamentally a people-centric business, making the addition of experienced professionals especially valuable. Customers Gain Access to Broader Expertise: One of the biggest benefits of the acquisition is the expanded access customers receive to specialized talent and services. Morrison notes that existing Velocio customers will gain access to Domain Six's industry expertise, while Domain Six customers will benefit from Velocio's larger global team and deeper Microsoft platform knowledge. The combined organization can now offer expertise spanning Azure, Dynamics, Microsoft 365, Fabric, data platforms, and business applications. Governance Has Become a Competitive Advantage: Data governance is no longer just a security requirement. Morrison explains that governance, access controls, documentation, and process discipline have become business enablers. Proper governance ensures that the right employees can access the right information at the right time, allowing organizations to move faster and make better decisions. As AI systems increasingly depend on organizational data, governance frameworks become essential for both compliance and performance. The Big Quote: “Everything that we do is people-centric. We're a consulting business at heart, and a consulting business is built on the knowledge and the abilities of the people you bring in, so bringing in that great team at Domain Six was key." More from Velocio and Robbie Morrison: Connect with Robbie on LinkedIn, read the press release about the Domain 6 acquisition,  or check out the Velocio website. Visit Cloud Wars for more.

In today's Cloud Wars Minute, I look at how ServiceNow's AI strategy, open platform, and workflow data fabric are driving its next phase of growth. Highlights 00:02 — ServiceNow is off to a hot start, not only with its quarterly results, but also in how CEO Bill McDermott is framing where the company is right now and, in terms of that, how that new position, which he says is, "We're 100% AI native," is going to allow them to pursue five what he called hyper-growth markets for quite some time. 01:06 — Who is AI native, and who is just sort of glossing over, applying some AI lipstick to their traditional solutions and technologies? The term that ServiceNow uses to refer to that latter category is AI sidecars, where they say that's just a little AI glomming onto traditional technology, and that's becoming less appealing to customers. 02:34 — Among the highlights he pointed out to support the strength of the company, he said, "We've got a $28 billion RPO, remaining performance obligation, that grew 23.5% in Q1." In addition to that, he said, "We've got the most open enterprise platform." 03:14 — First, its core ITSM business. He said with the complexity that's going on in enterprises and the more reliance on data that's going to be taking place here in the AI era, we're going to see a 50x —not 50%, 50x — boom in the number of tickets that are being sent through for IT support. 04:12 — He talked about what's going on there with Moveworks and the changes that ServiceNow has made to that, and how that's going to simplify things and help bring down the anxiety some people have about AI. And finally, he said, "Our workflow data fabric," which helps pull all the data together, is so essential for what's going on now with AI. Visit Cloud Wars for more.

In today's Cloud Wars Minute, I discuss how Workday's Extend platform is helping developers build faster while maintaining governance and trust. Highlights 00:03 — Earlier this week, Workday held its DevCon conference in Las Vegas. It was the biggest DevCon that Workday has ever had. They had 8,000 attendees, and of course, these days, the star of the show was new agentic capabilities that, in this case, Workday is pumping into its Workday Extend platform. 00:53 — This Developer Agent is being added to a number of new capabilities within the Extend platform, and I listened to this whole roundtable discussion, and a number of things jumped out. I just want to share some of the reactions with you because they give a sense of what's going on here among developers in the early stages of the AI revolution. 01:58 — One person called it a real game-changer, this Developer Agent, and she said, "What used to take me days, I can now do in about one hour." Another person said that, with Workday ensuring that all the guardrails around security, trust, and governance are there, "I can build now without losing any sleep every night." 03:08 — This person said actually hiring for software engineers here in the AI era is way up. I think what came across in this roundtable that Workday held at DevCon was the optimism that these folks showed. We're not only surviving the changes brought by AI, we're going to have chances to do more than we ever have before. 04:12 — Here they see that now the work, the time, the effort, the energy, the brain muscle that they are putting into their work is going to result in better output, more impact on the business, more capability, because the technology through these agents is both taking care of lower-level work and ensuring governance, trust, and security are wired in. Check out this press release outlining the major introductions at DevCon. Visit Cloud Wars for more.

In this episode of the AI Agent & Copilot Podcast, Giuseppe Ianni, podcast host and industry interviewer, is joined for a second time by Nandita Puri, PhD Researcher at Georgia Tech working at the intersection of bioinformatics and biochemistry. The conversation explores how AI is transforming drug discovery, accelerating hypothesis generation, reducing experimental costs, improving success rates, enabling rare disease research, and paving the way for virtual cell simulation. Key Takeaways AI Is Creating a New Drug Discovery Workflow: Puri describes a major transition from traditional laboratory-first research toward a hybrid approach combining computational and experimental science. Researchers can now use AI, machine learning, and pattern recognition to analyze massive biological datasets before conducting expensive laboratory work. According to Puri, "I see a healthy combination of 50% dry lab and wet-lab validation becoming the emerging standard." This shift allows scientists to move beyond manual analysis and leverage computational intelligence to generate stronger hypotheses, identify promising targets faster, and focus laboratory resources on the most promising opportunities. Higher Success Rates Mean Lower Costs and Less Waste: One of the most immediate benefits of AI in drug discovery is improved experimental efficiency. Puri notes that individual experiments can cost "$10,000-$12,000" and historically have carried significant failure risk. By consolidating fragmented datasets and identifying meaningful biological signals, AI helps researchers prioritize stronger hypotheses before entering the laboratory. Puri explained that some AI-assisted binder-development efforts achieved "40% 50% of success rate," compared with previous rates of "10% 5%." These improvements reduce wasted resources, shorten research timelines, and allow scientific teams to evaluate more potential treatments with the same budget. AI Is Unlocking Opportunities for Rare Disease Research: Rare diseases have historically faced funding and development challenges due to limited patient populations and expensive clinical validation requirements. Puri explains that AI is helping overcome these barriers by generating synthetic datasets, identifying hidden biological relationships, and revealing common signaling pathways between diseases. She notes that "AI is really, really helping rare disease industry to go forward." Visit Cloud Wars for more.

In today's Cloud Wars Minute, I explore why OpenAI could soon rank among the world's biggest enterprise software companies. Highlights 00:03 — Early this year, OpenAI joined the Cloud Wars Top 10 in the number 10 spot. Because of the impact OpenAI has had, moving from the ChatGPT explosion three and a half years ago up to now, and their move very aggressively into the enterprise, they are a player of a major type with huge potential, both in what they're doing themselves and the partnerships they have. 01:07 — The biggest one turns out to be that right now the enterprise part of the OpenAI business is very soon going to be the biggest, and I think it is currently the fastest-growing part of OpenAI. Denise Dresser [Chief Revenue Officer, OpenAI] said that enterprise revenue at OpenAI is now 40% of total revenue, and by the end of this year it'll be 50%. 02:05 — OpenAI Enterprise has two million enterprise customers right now. A year ago, she said it was one million. They're not all giant companies and they're not all paying OpenAI a lot of money, but what they're doing is seeding the way for future opportunities and growth. OpenAI hinted that they're on about a $25 billion run rate. 03:04 — If OpenAI grows 60% this year, making that $25 billion run rate $40 billion, then 50% of that going to enterprise would be a $20 billion business at a fairly conservative guess. It could be closer to $25 billion, making them a bigger, faster-growing enterprise AI software player than Workday, Palantir, and ServiceNow. 04:33 — Customers see that there's a lot of potential in the technology that OpenAI has, but they also want to know if OpenAI has the capability to support it. Dresser said that by the end of this year, OpenAI plans to have 300,000 trained consultants for the OpenAI Enterprise business. Competition is great. It's going to make everybody better. Visit Cloud Wars for more.

In this Cloud Wars conversation, Bob Evans sits down with Bonnie Tinder, Founder and CEO of Raven Intelligence, to discuss how AI is reshaping the systems-integrator (SI) market. Their discussion explores how AI-powered migration agents, deployment assistants, and new implementation models are dramatically reducing project timelines, staffing requirements, and costs. Bonnie explains why traditional implementation approaches are giving way to leaner, expertise-driven engagements centered on outcomes rather than labor hours. Episode 60 | Outcomes Beat Implementations The Big Themes: AI Compresses Implementation Costs: Tinder notes that organizations often spend 10 to 11 times the cost of software licenses on implementation services. AI is beginning to challenge that model by automating some of the most labor-intensive aspects of projects, particularly data migration and system conversion work. Migration agents and deployment assistants can significantly reduce the need for large teams of junior consultants performing repetitive tasks. As implementation timelines shrink and staffing requirements decline, customers will increasingly expect lower costs and faster results. Vendors are also pushing for these efficiencies because lengthy implementations delay customer value realization. The result is mounting pressure across the SI industry to adopt AI-enabled delivery models that are leaner, faster, and more outcome-focused. Outcome-Based Thinking Is Accelerating: Throughout the discussion, Bob and Bonnie discuss the growing demand for measurable business outcomes. Customers are increasingly unwilling to tolerate expensive implementations that fail to deliver value. This pressure is encouraging software vendors and SI firms to move toward outcome-oriented engagements and pricing models. Instead of charging primarily for labor and project duration, firms must demonstrate tangible improvements in efficiency, productivity, or business performance. Boutique Firms May Gain an Advantage: Bonnie sees a major opportunity for boutique consulting firms in the AI Era. Historically, large global systems integrators benefited from scale, brand recognition, and access to specialized tools. AI is leveling parts of that playing field by making sophisticated capabilities more broadly available. Smaller firms can now compete using many of the same technologies while offering highly experienced teams and direct client engagement. Visit Cloud Wars for more.

In today's Cloud Wars Minute, I look at Microsoft's latest moves to help organizations deploy and scale AI agents without sacrificing control. Highlights 00:10 — In the latest updates to Copilot Studio, Microsoft has introduced a series of improvements focusing on visibility and governance, allowing users to expand automation while maintaining control. Regarding visibility, the new analytics viewer role provides read-only access to an agent's analytics page. 00:36 — On top of this, Microsoft has expanded its agent usage estimator to include Dynamics 365 agents, enabling users to forecast Copilot credit consumption across both Copilot Studio and Dynamics 365 from one place. Microsoft already enables users to embed Copilot Studio agents into workflows using its agent node function. 01:16 — Other updates to workflows are designed to enable scaling without introducing governance risk. Workflows can connect to a larger toolkit, such as MCP server-enabled tools, to make it easier to take actions in systems, yet still within the Microsoft Security Framework. Users can also utilize agents built in Copilot Studio to bring interactive app experiences directly into Copilot Chat. 01:48 — This means they can review data, update records, approve requests, or create assets, all without having to switch tools. These are just some of the updates that Microsoft has been working on throughout April, and I really enjoy following the trajectory of these updates because they illustrate to me the current stage of our collective journey with AI. 02:11 — It's clear that agents are integrated into many systems, and now is the time to scale them securely. So, if you're still considering when and if to introduce AI-driven practices into your business, major directional changes like this should serve as a cautionary tale. Visit Cloud Wars for more.

In this episode of the AI Agent & Copilot Podcast, Giuseppe Ianni, AI Practice Lead and industry thought leader, is joined by Nandita Puri, PhD Candidate at Georgia Tech and founder of Illumia.bio. Puri discusses how AI is transforming drug discovery by creating massive therapeutic libraries, connecting fragmented biomedical knowledge, and dramatically accelerating research timelines. Their conversation explores the convergence of AI, structural biology, and life sciences. Key Takeaways AI Expands the Search Space for New Therapeutics: Traditional drug discovery focuses on identifying a single drug for a single target, but Puri argues that diseases are complex biological systems requiring broader approaches. Her team is building an AI-generated library of more than 10 billion molecules across multiple therapeutic modalities. By treating drug discovery as a combinatorics problem, researchers can explore vastly larger therapeutic possibilities. Connecting Fragmented Scientific Knowledge Accelerates Discovery: One of the biggest bottlenecks in pharmaceutical research is the fragmented nature of scientific information. Researchers often spend years reviewing hundreds of papers before forming a hypothesis. Puri describes how her team is integrating 60 to 70 public databases into a connected knowledge platform that links diseases, genes, proteins, pathways, and drug candidates. As she notes, "When we type a disease, we know exactly the gene, we exactly know the protein." This consolidation dramatically reduces research time and enables scientists to make more informed decisions earlier in the discovery process. AI Creates New Opportunities for Rare Disease Research: Rare diseases have historically been underserved because of the high costs and long timelines associated with traditional drug development. Puri says that bringing a drug to market can require "$1 billion and about 10 years." By shortening research cycles from years to months, AI lowers the barriers to investigating diseases that pharmaceutical companies may have previously avoided. This acceleration enables smaller teams to pursue treatments for conditions affecting fewer patients while increasing the likelihood that promising therapies can move forward to validation and clinical testing. Visit Cloud Wars for more.

In today's Cloud Wars Minute, I examine how Google Cloud is using AI Threat Defense to help customers fight AI-powered cyberattacks. Highlights 00:03 — If you're going to be number one on the Cloud Wars Top 10, you've got to fight to keep that position and stay ahead of the incredible and highly capable competition across the Cloud Wars Top 10. Google Cloud, I believe, has taken yet another big step in ensuring that it remains the number one company on the Cloud Wars Top 10 by launching a new cybersecurity approach. 00:57 — The person leading that is Francis deSouza, who is the Chief Operating Officer of Google Cloud, but also president of its security products. In a blog post last week outlining what this new AI Threat Defense is all about, deSouza said it's time now that business customers be able to fight AI with AI, to defend against these very powerful incursions that the bad guys are going to be making using AI. 01:58 — So, there needs to be, among customers, a big shift in how they do things. It can't be, "Let's just do a little bit more of what we've always done." There's got to be a new approach, and Google Cloud believes it's got that now with this AI Threat Defense for Google Cloud. I believe this is the latest in an ongoing series of steps they've made around cybersecurity. 02:54 — About a year ago — or several months ago — the company announced its intention to acquire Wiz, with its end-to-end threat monitoring and awareness capabilities. That deal has now been completed, and the most recent step, I believe, is the launch of this new solution called Google AI Threat Defense. 03:56 — Now, I'm not trying to read more into that than needs to be said. Maybe Google Cloud AI Threat Defense seemed overly clunky, but I wonder if, in some ways, parent company Google is riding this high now. Google Cloud itself had a growth rate of 63%, up from 48% in the prior quarter, so the company is definitely on a run here. Visit Cloud Wars for more.

In today's Cloud Wars Minute, I analyze how Marc Benioff is using Agentforce to drive larger deals, stronger customer spending, and new AI metrics. Highlights 00:02 — We see Salesforce is off to a good start here in its fiscal '27. For Q1 ended, let's see, April 30, it reported that overall revenue was up by 13% to $11.1 billion. I want to look into some of the big numbers within the Q1 presentation, and also the earnings call. It, I think, revealed just how heavily AI, and in particular Agentforce, have become the growth engines here inside Salesforce. 00:31 — Salesforce, after wandering for a few years trying to get its margins right to please institutional investors, is now riding the AI Revolution. So, I've got 10 numbers that I pulled out from that presentation and the earnings call. Agentforce was involved in, and Benioff said drove, almost half of the company's 100 largest Q1 deals. It had 98 that were $1 million or more. 01:15 — Agentforce was in about half of those. The most active AI users that Salesforce has, the ones doing what it calls agentic work units, detailing specific tasks that agents have completed, it said the most active AI users now have increased their spending with Salesforce by 1.5x from the previous year. So clearly customers are seeing the value in this now. 01:46 — Benioff said that over the years Salesforce has generated many, many millions of leads, more than its human salespeople could follow up on over that time. It put Agentforce on it, and autonomously it contacted 220,000 of these customers interested in Salesforce but who never got a call back, generating $42 million in pipeline from that. 02:45 — One other interesting point I'll note here is that Salesforce began to list Now tokens processed in the quarter, and it said it was 28.3 trillion tokens processed in Q1 through Salesforce as agents and applications. Now that's a number that it says it's going to be revealing every quarter here, and I think it's a great idea. It carries some risks. 03:13 — It's a great idea because it shows not just what people are spending on AI, but the work that is getting done in what they call these AWUs, or Agentic Work Units. Salesforce said that relative to Q1, the average work units undertaken by Salesforce customers was up 152%. That's sequential, quarter-to-quarter. Visit Cloud Wars for more.

In today's Cloud Wars Minute, I look at how Microsoft and EY are combining engineering and consulting expertise to scale AI transformation. Highlights 00:10 — Microsoft and EY have announced a substantial enhancement to their existing partnership, committing to invest over a billion dollars over five years into a new initiative aimed at helping organizations to scale AI. 00:40 — So, what's the plan for it? Well, it will combine Microsoft's forward-deployed engineers, or FDEs, with the expertise of EY industry professionals to accelerate AI adoption. Their approach focuses on, and I quote, “change management delivery models powered by Microsoft's FDE AI-native hypervelocity engineering approach.” 01:05 — Now, this initiative will see teams of EY business consultants and Microsoft engineers co-develop AI solutions tailored to address clients' highest-value business opportunities. This collaboration is steering companies toward the goal of becoming frontier firms. It's a term coined by Microsoft that I've used many times, that's gaining traction across the industry. 01:29 — Frontier firms are organizations that integrate agentic AI with the human workforce at scale and continuously optimize AI initiatives while adapting their company culture to thrive in this new future. Now, an interesting aspect of this collaboration is that EY, already closely aligned with Microsoft in terms of partners, was in fact the client zero for the initiative. 01:56 — This means they [the EY team] have an insider's understanding of what works well, how to adapt to Microsoft products, and how to effectively share this knowledge with potential customers and clients. Visit Cloud Wars for more.

In today's Cloud Wars Minute, I break down why Workday sees agentic AI as the key to defending its 80 million-user base. Highlights 00:02 — Workday co-founder Aneel Bhusri resumed his position as CEO. He wanted to help guide the company through the AI Revolution and help bring a solid knowledge of what's happening and how Workday as a company has to be able to innovate and create and get with the AI-native program as rapidly as possible. 00:45 — It's got to be able to move fast, and the margin for error is slight. The Q1 results, which came out last week, I think prove that Bhusri's got the company on the right track. Subscription revenue up 14.3%, almost $2.4 billion. Their total subscription revenue backlog was up 11% to over $27 billion. 01:23 — It's now got 80 million users under contract. Now, the good and the bad of that is those are 80 million users who are heavily dependent right now on yesterday's technology. So, the good thing for Workday is they've got these 80 million users, and Workday's got the first shot at converting them. 02:23 — Bhusri said, “In technology transitions — and I’m old enough to have lived through a few of them — you have to put that new technology front and center. It’s got to be your absolute top priority in everything you do.” 03:38 — Bhusri said customers seem to want to have both open technology and the ability to use agents from lots of vendors, but they've also got to ensure that they've got the proper guardrails for compliance and legal compliance, and ensuring the privacy and safety of their customers. He also said it's really important for Workday to reinstitute and reinvigorate a startup mentality. 04:48 — So, Aneel Bhusri is one of the good guys in the tech industry. He's been around a long time. His return here, I called him back in February “the reluctant CEO,” because he was eager a few years ago to get out of the CEO role, but he knows now that with what's going on in the market and this vast change of technology brought forth by AI, he needed to be CEO. Visit Cloud Wars for more.

Bonnie Tinder is the founder and CEO of Raven Intelligence, an independent B2B peer review site that amplifies the voice of the customer. She focuses on software customers, consulting partners, and software vendors and helps identify the best partners for their needs. In this episode, she and Bob Evans speak about Workday’s accelerating AI transformation following its Innovation Summit. Bonnie offers a practitioner’s perspective on how Workday is rethinking enterprise software around agentic AI, faster deployments, embedded governance, and a startup-like culture shift under returning leadership. Episode 59 | Workday’s AI Reset The Big Themes: Workday’s Startup Reboot: Bonnie Tinder’s biggest observation was that Workday appears to be entering a new operational chapter defined by urgency, sharper execution, and a startup mindset. Rather than behaving like an incumbent defending market share, Workday seems to be restructuring around focused AI ownership and entrepreneurial velocity. Bonnie connected this directly to Aneel Bhusri's leadership style, comparing it to Steve Jobs returning to simplify Apple’s priorities. No One Wants DIY Enterprise AI: A major theme was the rejection of the “build it yourself” narrative for enterprise core systems. Bonnie and Bob both strongly challenged the idea that enterprises will vibe-code their own payroll, financials, or HCM systems. The reason is simple: risk. Enterprise systems are compliance-heavy, operationally critical, and intolerant of failure. Bonnie’s “you can’t get payroll 90% correct” line perfectly captured the reality. CEO Leadership Is Non-Negotiable: AI transformation must be CEO-led. Bottom-up experimentation alone is unlikely to produce meaningful enterprise change. AI affects operating models, workflows, investment priorities, talent strategy, governance, and competitive differentiation. That requires executive sponsorship and strategic ownership. Bob argued that companies cannot approach AI using 2023 or 2024 decision frameworks. Instead, leadership teams must rethink vendor evaluation, operational transformation, and business outcome measurement. Bonnie reinforced that major transformation initiatives succeed when leadership drives adoption from the top. The Big Quote: “The real AI gold rush isn't in the models, it's really that unglamorous work of moving 30-year-old legacy systems to a point where agents can actually do something with the data.” More from Bonnie Tinder: Connect with Bonnie on LinkedIn. Visit Cloud Wars for more.

In today's Cloud Wars Minute, I examine why Agentforce Operations could remove one of enterprise AI’s biggest adoption barriers. Highlights 00:03 — While the flow of innovative and transformational agentic AI technologies has certainly shifted from a trickle to a flood, there are still many barriers to success, albeit barriers that companies across the board are diligently working to address and overcome. 00:33 — [Many] workflows were built for manual human oversight, often loosely governed and entirely unsuitable for agentic AI. Now, Salesforce aims to tackle this back-office issue and eliminate these bottlenecks with a new product called Agentforce Operations. 01:24 — The result is a system where, after manual processes are digitized, a task [can] take a mere amount of minutes [and] agents can handle the heavy lifting with human oversight. Business users can continually improve these processes without needing any coding knowledge. 01:48 —Aman Naimat, SVP and GM of Agentforce Operations at Salesforce said the following about this new product: “As companies accelerate AI adoption to become agentic enterprises, most are still burdened by an underlying layer of fragmented manual processes across supply chain, procurement, finance, and the broader back office.” 02:43 — This, particularly, is a clear example of a seamless interaction between agents and human operators. The human in the loop can specify the task that needs to be automated, while the system improves the quality of how the agent operates. Visit Cloud Wars for more.

In today's Cloud Wars Minute, I cover a recent court case leading to OpenAI having to clarify that ChatGPT is not a lawyer. Highlights 00:10 — There has been confusion about what OpenAI's core product, ChatGPT, is and isn't, particularly in a recent court case. OpenAI clarified that ChatGPT is not a lawyer after an individual used the AI tool to build her case and would cite it as a source. 01:30 — In its motion for dismissal, ChatGPT had to very specifically note that it's not a lawyer, it is not a person, and it does not practice law. OpenAI defined ChatGPT as a set of rules and words that help people understand what's going on around them. 02:30 — One of the world's most technologically advanced companies and innovators had to spell this out in court. There is a fair amount of humor to be found in this. 03:00 — To quote Pogo, "We have met the enemy, and it is us." Humans should be rightly proud of the tech innovations and AI advances emerging. However, there's always going to be this goofiness out on the fringes where things have to be spelled out. Visit Cloud Wars for more.

In today's Cloud Wars Minute, I unpack Microsoft’s Work Trend Index and what it reveals about the rise of agentic AI in the workplace. Highlights 00:09 — Microsoft's 2026 Work Trend Index annual report is titled "Agents, Human Agency, and the Opportunity for Every Organization." Microsoft analyzed trillions of anonymized M365 productivity signals, surveyed upwards of 20,000 workers in 10 countries, and consulted with experts in AI, work, and organizational psychology. Here are some of the most revealing insights. 01:25 — An analysis of 100,000 Copilot chats found that 49% of conversations were focused on supporting cognitive tasks, ultimately enhancing the capabilities of these human participants. On top of that, 66% of surveyed AI users reported that AI has enabled them to dedicate more time to high-value work. 01:49 — Microsoft states that close to one in five workers are in what they call the frontier zone, which refers to what they describe as "the sweet spot where organizational capability and individual readiness reinforce each other." 02:14 — Microsoft says that the key to alignment is for companies to focus on AI absorption rather than simply AI adoption, and this involves redesigning how work is done and turning AI outputs into actionable insights. Visit Cloud Wars for more.

In today's Cloud Wars Minute, I unpack why Palantir’s customer-first AI approach is outperforming much larger rivals. Highlights 00:06 — One of the drivers in 2025 and 2026 of that surge in the greatest growth market here has been Palantir, relatively small. It'll probably do seven and a half, $8 billion in the coming year. 00:42 — So I had a great chat, you can see it all, a one-on-one video conversation with Palantir architect Chad Wahlquist. Palantir's titles are a little peculiar, right? It has its own way of doing things, as it does in a number of ways. Chad's not just a typical enterprise architect. 01:23 — One of the things that's unique about Palantir is how its customers will come, sign an original deal, and then in a very short period of time, three, four, six months, greatly increase that deal because it's showing the value of the AI to the customer. 02:18 — Palantir is the company, I think, in sort of the more modern era, that's really brought this to the forefront. Chad and I talked about the partnership and the significance of that for customers, bringing together the immense data and industry expertise that SAP has. 03:15 — It's not a big rip-and-replace thing. How can we build on what you have and get you some very quick returns on this? Palantir's number one on the growth chart at 70%. Google Cloud surged into the number two spot at 63%. Visit Cloud Wars for more.

In this Cloud Wars special report, Bob Evans speaks with Chad Wahlquist, Architect at Palantir, about the company’s explosive Q1 performance and the deeper forces driving enterprise AI adoption. Wahlquist explains how Palantir’s model goes far beyond traditional software, combining forward deployed engineering, ontology, agentic AI, and enterprise infrastructure to accelerate customer outcomes. AI Infrastructure Rising The Big Themes: AI Building AI: One of the most striking themes is the shift from companies building AI products to building AI products with AI. Wahlquist describes a major evolution in enterprise delivery models, where Palantir has moved from “boot camps” to “agent camps,” using AI agents to help rapidly construct customer solutions. This dramatically compresses timelines from projects expected to take months down to days. The deeper implication is that AI is no longer just the product layer; it is becoming the production mechanism itself. SAP Migration Gets Reinvented: The SAP partnership emerges as one of the most strategically significant parts of the discussion. Wahlquist describes Palantir helping customers accelerate complex ERP migrations, including ECC-to-S/4 transformations, acquired-company integrations, and even mainframe modernization. Traditionally, these efforts consume years and hundreds of millions of dollars. Palantir’s approach uses ontology plus agentic frameworks to interpret structured and unstructured enterprise information, identify mismatches, and automate execution paths. He claims 50%+ time compression in migration work. Efficiency As Corporate Proof Point: One fascinating element is Palantir’s operating model itself. Evans references Alex Karp’s claim that a company of Palantir’s scale would traditionally employ thousands of salespeople, while Palantir operates with a dramatically leaner commercial organization. Wahlquist argues that product effectiveness changes the equation: engineers demonstrating working systems on customer data become the real sales force. He also notes Palantir internally runs on its own software, using Foundry-based systems for CRM, ticketing, finance, and operations. This creates both operational efficiency and credibility. The Big Quote: “What I’m seeing here is really the difference between, hey, I’m building AI products to I’m building AI products with AI.” More from Chad Wahlquist: Connect with Chad on LinkedIn, or learn about Palantir Foundry. Visit Cloud Wars for more.