Cloud Wars Live with Bob Evans

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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