Cloud Wars Live with Bob Evans

In today's Cloud Wars Minute, I explain why the AI revolution isn’t a bubble — it’s backed by unprecedented backlog growth.

Highlights

00:02 — There are some wild numbers being thrown around here early in 2026 as we think about the CapEx investments that the four hyperscalers — Microsoft, AWS, Google Cloud, and Oracle — are making to build up their AI factories, their AI and cloud infrastructure to meet the incredible demand for AI training, inferencing, cloud transformations, business transformations, and more.

01:28 — The money, the huge revenue, is already there, and it’s growing at an incredible pace. That’s why these companies are investing so much, because the market is so enormous, the potential is so huge. This number —$1.63 trillion — that’s the amount of either RPO or backlog combined that those four companies have generated going forward.

02:12 — The RPO backlog figures for each of these companies are: Microsoft, $625 billion, growing at 110%; Oracle, $523 billion, growing at 438%; AWS, $240 billion, up 40%; Google Cloud, $240 billion, growing at 55%. These are very fresh figures from their Q4 earnings results.

03:28 — Microsoft and Google each going to spend about $185 billion in CapEx this fiscal year; AWS, $200 billion; and Oracle, about $75 billion. That totals up to $645 billion dollars in CapEx. The world has never seen anything like this. We’re into unprecedented territory here.

04:39 — That is money that’s chasing this already committed business in RPO and backlog. This is $1.63 trillion. That’s right here, right now — a snapshot of what they already have in backlog. Even if they don’t come anywhere close to those growth rates, they’re still showing extraordinary growth and vitality.

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In this episode of the AI Agent & Copilot Podcast, John Siefert, host and CEO, Dynamic Communities and Cloud Wars, is joined by Jen Harris, CEO of TMC, to explore how AI agents, automation, and mindset shifts are redefining business. Their discussion spans TMC’s acquisition of TMG, leadership in the partner ecosystem, and why reimagining work is critical now, setting the stage for conversations at the 2026 AI Agent & Copilot Summit NA.

Key Takeaways

• AI Requires Commitment, Not Caution: Harris emphasizes that half-measures slow progress more than they reduce risk. Organizations that just try one thing often abandon AI too quickly because early results aren’t perfect. She notes, “You fail first at new things,” adding that true adoption requires patience, leadership backing, and a willingness to accept short-term discomfort for long-term gains.
• Solutions Beat Technology Stacks: Customers no longer want disconnected tools; they want outcomes. Harris explains that clients expect partners to “meet them where they are,” combining Power Platform, Azure, data, and AI into real solutions.
• Mindset Is the Real Bottleneck: While AI is already embedded in daily life, Harris observes resistance when it enters core business roles. “It’s not quite here yet” is often code for fear of job impact. She challenges leaders to reframe AI as a workload reducer, asking, “What if it would make you less busy?”
• Reactive Roles Are Disappearing: Harris highlights a coming shift as agents take over repetitive, reactive work. Professionals who built careers on being indispensable specialists must evolve. People will move toward proactive creation, strategy, and value generation.
• Human Connection Still Matters: Despite rapid automation, Harris stresses that humanity isn’t going away. Reflecting on in-person events, she says, “Look at you — you came out of your offices on a cold day, and we’re talking.” AI may scale intelligence, but trust, inspiration, and shared understanding still comes from people.

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In today's Cloud Wars Minute, I explain why unified security strategies are essential in the GenAI Era.

Highlights

00:08 — One of the cornerstones of AI adoption is security. It’s essential to get it right the first time and not backtrack, because compared to the security risks of the past, AI tools and the vast swathes of sensitive data they leverage are in a league of their own.

00:25 — To mitigate these risks, organizations need to ensure that the pace of their security measures matches that of AI innovation. Now, the 2026 Microsoft Data Security Index report addresses these issues, how to leverage the incredible power of AI while keeping data secure.

01:26 — Ultimately, the report suggests three priorities for organizations to protect their data while maximizing AI adoption. One is a conscious and deliberate move away from fragmented security tools towards a unified data security mechanism.

01:45 — The report found that 47% of organizations surveyed had a GenAI-specific control in place, and this year’s survey found that an astounding 82% of those questioned have already developed plans to incorporate GenAI into their data security ops.

02:43 — When it comes to GenAI, the situation is tricky, because the technology serves both as a gateway for threat actors and as a mechanism for preventing them. When you get this balancing act right, the opportunities for growth are endless.

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In this latest episode of Cloud Wars Live, Bob Evans is joined by Colleen Kapase, Vice President of Channels and Partner Programs at Google Cloud, and Rakesh Sancheti, Chief Growth Officer at Tredence. Together, they explore how agentic AI is transforming enterprises from insight-driven organizations into adaptive, reflexive businesses. The conversation highlights how AI agents, data foundations, and partner ecosystems are reshaping productivity, decision-making, and real-time execution across industries.

The Responsive Enterprise

The Big Themes:

• AI Moves From Insight to Action: Enterprises are transitioning from AI that merely advises to AI systems that actively execute decisions. Agentic AI workflows enable systems to sense changes, analyze signals, and take action without waiting for human intervention. This marks a fundamental shift from dashboards and reports to operational intelligence embedded directly into business processes. The result is faster adaptation, reduced latency in decision-making, and organizations that can respond to market changes in near real time rather than after-the-fact analysis cycles.
• Partners Are the Critical Bridge: Technology platforms alone cannot deliver transformation. Partners play a crucial role in translating AI capabilities into real-world outcomes by combining industry expertise, customer context, and accelerators. They bridge the gap between powerful AI platforms and the specific operational realities of each enterprise. This partnership model accelerates deployment, reduces experimentation cycles, and ensures AI agents are connected to real data and real processes.
• Retail Emerges as a Leading Use Case: Retail provides a vivid example of agentic AI in action. Multi-agent systems personalize experiences, optimize merchandising, adjust media spend, and guide customers in real time. These systems act continuously, responding to shopper behavior, inventory signals, and market conditions instantly. The result is improved customer experience, higher returns, and operations that function more like living systems than static processes.

The Big Quote: “We’re really going to move past the era where data is just sitting in warehouses and being collected and really looking at it independently, and instead take advanced AI and put it in the hands of every single individual.”

More from Tredence and Google Cloud:

Dive into Tredence's exploration of AI agents and Google Cloud's guide for putting AI agents on the marketplace.

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In today's Cloud Wars Minute, I examine why incremental growth matters more than sheer cloud size.

Highlights

00:02 — Made big changes atop the Cloud Wars Top 10 here at the beginning of 2026. Driven by trends in the financial results that the three biggest hyperscalers: Microsoft, Google Cloud, and AWS are reporting. There are changes taking place at the top among those companies, in terms of customer demand and the choices customers are making going forward into the AI Economy.

00:48 — My big point here is that there is a metric, key growth metric, and in Q4 for the first time that I can recall, this key metric, both Google Cloud and AWS beat Microsoft in this. This hasn’t happened that I can recall. The key here isn’t so much about mass accumulated over the years, but about the growth and who customers are spending their money with now.

01:42 — Microsoft Cloud revenue of $51.5 billion, up 26%. AWS, $35.6 billion up 24%. Google Cloud, $17.7 billion up a whopping 48%. Now look at the incremental Q4 over Q3 momentum. AWS up $2.6 billion. Google Cloud up $2.5 billion. Microsoft up $2.4 billion.

03:13 — Google Cloud actually brought in more incremental revenue in Q4 versus Q3 and this is the first time I believe this has ever happened. Google Cloud’s now has $70 billion on an annualized basis, not a little company by any means. In Q4 it grew 48% and it took more new business Q4 versus Q3 than Microsoft did.

04:56 — Google Cloud almost matched what AWS did in incremental growth for Q4, and it beat Microsoft. That validates the position I took when I moved Google Cloud to number one on the Cloud Wars Top 10. These numbers reflect what customers are doing, where they’re spending their money, who they’re choosing, and who they’re going with.

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In today's Cloud Wars Minute, I analyze hyperscaler Q4 numbers and reveal why growth rates matter more than size right now.

Highlights

00:02— We've got the final hyperscaler numbers in now, so we can do some comparisons here. AWS reported a very strong Q4 numbers late last week. I want to talk about that in two contexts. First of all, those numbers themselves and the very nice performance AWS put together.

00:42 — The second one, though, is relative to its big competitors, specifically Google Cloud and Microsoft. AWS, in spite of good numbers itself in Q4, continues to fall behind the pace being set by the leaders, particularly Google Cloud. Its revenue is up 24% to $35.6 billion. I think that's about a $142 billion annualized run rate.

01:44 — Very impressive, excellent growth rate. Each quarter this year, their growth rate has gone up: Q1, 17%; then 17.5%; then 20%; and now 24%. Best quarter in more than three years for them. And their backlog, they said, was up 40% to $244 billion. But at the same time, Google Cloud's explosive Q4 numbers show that they have a 48% growth rate versus AWS's 24%.

02:16 — That's twice as much. So AWS is twice as big as Google Cloud, but Google Cloud is growing twice as fast. The growth rate now — 48% in Q4 for Google Cloud, 26% for Microsoft Cloud, and AWS 24% — that is really an outlier there. One is in incremental quarter-over-quarter revenue. So the revenue in Q3, then look at the revenue in Q4.

03:02 — AWS is in the lead: $2.6 billion incremental revenue in Q4 versus Q3. Google Cloud, $2.5 billion. Microsoft Cloud, $2.4 billion. AWS is twice as big as Google Cloud, but Google Cloud matched them on this incremental new growth. Microsoft is three times bigger than Google Cloud, but Google Cloud actually exceeded, by a little bit, what Microsoft did in Q4 over Q3.

04:27 — Those numbers in any other industry would absolutely be astonishing, unprecedented. In the Cloud Wars, though, as good as those AWS numbers are, it's only third-best. Oracle is expected to grow 40% to 44% in numbers that will come out in about a month, when it reports its most recent quarter. Microsoft is bigger than AWS, and it's growing faster.

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In today's Cloud Wars Minute, I explain why agent sprawl may become one of the biggest hidden risks of the AI Era.

Highlights

00:03 — The massive increase in the adoption of agentic AI technology will have significant consequences for businesses. There’ll be increased productivity, the ability to reskill employees who have more time to focus on other areas of the business, and opportunities to explore new business ideas and avenues.

00:32 — And something else — a surge in the number of AI agents, millions, millions, and millions of them. All of these agents lead to a phenomenon called agent sprawl. So if data sprawl is diesel-driven, think of agent sprawl as running on jet fuel. Without proper governance and visibility, this can lead to shadow AI, which, in the wrong hands, could effectively bring down a business.

01:04 — To avoid this, Salesforce has added automated discovery for AI agents and tools to MuleSoft Agent Fabric. Andrew Comstock, SVP and GM of MuleSoft at Salesforce, said "The expanded capabilities give you the freedom to innovate across any platform while maintaining the unified visibility and control needed to scale."

01:32 — At the core of these enhancements are agent scanners, which automatically detect and catalog AI agents across Salesforce Agentforce, Amazon Bedrock, Google Cloud’s Vertex AI, and other authorized AI platforms. Additionally, for MCP services and other bespoke agents, MuleSoft Agent Fabric facilitates easy integration across a company’s entire agent ecosystem.

02:01 — The recent updates replace manual oversight with automation, enhance security by providing instant visibility into multi-cloud agents, highlight internal tools that may otherwise be overlooked, and offer a unified agent map to identify areas for optimizing AI investments.

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Highlights

00:02 — A month ago, I moved Google Cloud up to the #1 spot on the Cloud Wars Top 10, moved Microsoft down to #3. That was predicated in large part on the tremendous job Google Cloud has done in building sort of the twin pillars: AI and cloud, the way its customers are building for the future, not just perfecting what they've done in the past.

00:27 — And also the company's impressive growth rates, showing that more and more, in spite of the size differential between Microsoft and Google Cloud, Google Cloud was winning a disproportionate share of new business, showing it is becoming, back then, the favored cloud and AI vendor.

00:47 — Well, the Q4 numbers for Google Cloud came out yesterday, and there's no doubt that that was the right call To make. Google Cloud's Q4 revenue jumped 48% to $17.7 billion and they beat Microsoft for the first time ever in a very key metric, it's the really the big thing I want to talk about here today.

01:50 — Microsoft's last three quarters, it grew 27% 26, 26. For Google Cloud, it's 32, 34, 48. Google Cloud is on a massive acceleration run here. So, in spite of the fact that the numbers here, the revenue figures, are different, what we see is Google Cloud accelerating wildly. Well, Microsoft has leveled off again.

02:23 — The key point here, this key metric I talked about up above, if you look at the incremental revenue gains each company made, looking at what calendar Q3 ended, September 30 to calendar Q4 December 31, those are the periods we're looking at. Google Cloud's revenue Q3 to Q4 went up $2.5 billion from just over $15 to $17.7, Microsoft's went up $2.4 billion $49.1 to $51.5.

03:30 — While the heart of this discussion is around Google Cloud, Microsoft has been doing an extraordinary job in this very competitive market, but that's why I call it the greatest growth market the world has ever known. We're seeing companies perform in this market unlike any other industry at any time in human history.

04:47 — The big thing about it here is you've got these smaller, disruptive cloud and AI players, Google Cloud at #1, Oracle #2, Microsoft down at #3. I moved AWS down to #7. It's doing some really good things in a lot of ways, but as far as the company setting the agenda in line with their customers for the future for the AI economy, it's Google #1, Oracle #2, Microsoft #3.

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In this episode of the AI Agent & Copilot Podcast, John Siefert, CEO of Dynamic Communities and Cloud Wars, sits down with Dona Sarkar, Chief Troublemaker, Enterprise AI Advocacy at Microsoft, to explore what it really takes to move AI agents and copilots from experimentation into production. Their conversation previews Sarkar’s keynote at the 2026 AI Agent & Copilot Summit NA and dives into practical adoption, human-centered AI, and lessons learned from real-world enterprise deployments.

Key Takeaways

• Enterprise advocacy bridges the gap: Sarkar explains that enterprise cloud advocacy exists to translate Microsoft product capabilities into practical, real-world business solutions. Rather than selling tools, her team focuses on enablement — creating demos, workshops, and labs that show how AI agents, Copilot Studio, Azure, and Power Platform can actually be deployed inside organizations.
• Production is harder than experimentation: Building an AI agent is easy; deploying it responsibly is not. Enterprises struggle with permissions, ownership, data readiness, and governance once agents move into production. These challenges reveal why successful AI adoption requires cross-functional collaboration between IT, business units, and governance teams.
• Not all work should be automated: Sarkar cautions against replacing meaningful human interactions with automation simply because it’s possible. Instead, organizations should focus AI on prioritization, analysis, and repetitive tasks — freeing humans to spend more time on creativity, judgment, and relationship-building. “We really need to go draw a big old line in the sand and say, these should be uniquely human to human activities," she says. "These should be uniquely AI to human activities. These should be uniquely AI to AI activities.”
• Human connection matters more than ever: Despite fears that AI would reduce in-person interaction, both speakers observe the opposite trend. Conferences and professional gatherings are thriving because people crave perspective, not just information. While AI can surface data instantly, point of view comes from lived experience.
• Failure is part of responsible AI adoption: Sarkar openly shares that "The number of agents I’ve had to take down is probably like 50% of the agents I built.” These failures weren’t wasted effort; they informed better tooling, clearer governance, and improved workflows. Microsoft’s rapid release of new AI tools reflects lessons learned internally before being shared with customers.

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In today’s Cloud Wars Minute, I look at how Microsoft is helping developers build and scale AI agents safely inside Visual Studio Code.

Highlights

00:10 — The Microsoft Copilot Studio extension for Visual Studio Code is now generally available, providing developers with the ability to build and manage Copilot Studio agents directly within the IDE. This extension is designed for developers and integrates seamlessly into their workflows.

00:28 — It includes standard Git integration, request-based pull reviews, auditability, and is tailored to the VS Code UX. The new extension reflects the growing complexity of agents and equips developers with the same best practices they use for app development, including, as Microsoft puts it, source control, pull requests, change history, and repeatable deployments.

01:02 — This extension really benefits developers when they need to manage complex agents, collaborate with multiple stakeholders, and ensure that any changes made are done so safely. It’s ideal for developers who prefer to build within their IDE while also having an AI assistant available to help them iterate more quickly and productively.

01:30 — The extension introduces important structural support for the development of AI agents. By integrating Copilot Studio directly into VS Code, Microsoft is empowering developers to build more efficiently, without compromising control, access to collaborators, or safety. This is a critical combination as AI agents become increasingly more powerful and complex.

02:00 — As these agents continue to evolve, they require the same stringent checks and balances as traditional software. Microsoft’s Copilot Studio extension addresses this by giving developers the tools they need to scale agents responsibly while maintaining performance.

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