Cloud Wars Live with Bob Evans

In this episode of the AI Agent & Copilot Podcast, Tom Smith is joined by Kieron Allen, an industry analyst and AI observer, who shares insights from the 2026 AI Agent & Copilot Summit NA in San Diego. Together, they unpack major themes from the event, including agent orchestration, workforce reskilling, MCP’s enterprise impact, and the evolving human-AI partnership.

Key Takeaways

Human + AI Orchestration Is the New Core Skill: Allen underscores that orchestration is not just about technology—it’s about people managing AI systems effectively. Humans have to view agents as part of the workforce. This means employees must develop skills to coordinate, supervise, and optimize AI agents, treating them as collaborators rather than tools. The ability to orchestrate multiple agents will become a defining competency in modern organizations.

Reskilling Must Address Culture and Collaboration One of Allen's strongest points is that reskilling goes beyond technical training. “We need to understand the AI… not just the tools, but also the cultural elements.” Organizations must prepare employees to work alongside AI, interpret outputs, and adapt workflows. This includes fostering trust in AI systems, redefining job roles, and building a culture that embraces continuous learning and collaboration with intelligent agents.

MCP is Unlocking Massive Enterprise Efficiency: Smith highlights MCP as a breakthrough, describing it as a “USB-type connector” between AI and enterprise systems. With up to “650,000 actions” now automatable in Dynamics 365, MCP dramatically reduces manual effort. This standard simplifies integration across platforms, accelerates deployment, and enables scalable automation—making it a cornerstone for organizations looking to operationalize AI at scale.

Customer-Centric AI Learning is Accelerating Adoption: Allen observes that many professionals are attending the conference not just for internal use, but because “they’re attending this conference… for their customers.” This reflects a shift where AI literacy is becoming essential for delivering value externally. Businesses are recognizing that understanding AI enables them to better anticipate client needs, create new offerings, and remain competitive.

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In today’s Cloud Wars Minute, I question whether OpenAI’s $140 billion enterprise revenue target is a realistic strategy or a speculative leap.

Highlights

00:03 — It was announced recently, or revealed recently, that OpenAI expects that its revenue will hit about $280 billion by the year 2030, half of that enterprise, half of it consumer. So that would mean that by 2030, OpenAI, according to this CNBC report citing anonymous, confidential sources, will have its enterprise revenue be about $140 billion in five years, or less than five years now.

00:48 — As Larry Ellison said, “The baby could talk.” There has been a huge amount of interest around OpenAI. It has also stirred up considerable head-scratching with its agreements to purchase $300 billion of AI training and inferencing from Oracle, and about the same amount, maybe even a little more, from Microsoft. Now, all of this has people wondering, who is this company? What's it going to do?

01:47 — They said it's confidential, but they've seen information about OpenAI’s plans, so maybe we need to take this with a grain of salt. And I typically regard anonymous sourcing reports with about the same passion and love that I have for skin rashes. But I think because of the implications here for OpenAI and what it might mean, I thought this was at least worth mentioning.

02:26 — But they also said that, seeing that OpenAI has now changed its projections for how much compute or AI infrastructure spending it needs to do, Sam Altman had recently said it's going to be $1.4 trillion. Well now, according to the CNBC report, he's pulled that back to about $600 billion. That's a cut of $800 billion, or about 57% of the projections.

03:36 — So the more compute spending we do, the more revenue OpenAI is able to get—that is her premise. Now, if they are indeed cutting their compute and AI infrastructure spending by $800 billion, how then does that equate to this explosive revenue growth? And was that premise—that compute growth equals revenue growth—not true?

04:29 — Now, what about if key suppliers such as Oracle and Microsoft, perhaps Google Cloud, perhaps AWS, are also in this expansive scheme by OpenAI to reach $140 billion in enterprise revenue in four and a half years? What if they become competitors? How do they feel about continuing to be the suppliers of this engine of revenue growth?

05:26 — I don't mean in raising these questions to diminish the impact or the potential that OpenAI has. I think, like any fast-growing category creator as OpenAI has been, there's no roadmap, nobody's done this before, there's no playbook, and they've got to make this up as they go along.

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Microsoft is redefining enterprise productivity by positioning Copilot, agents, and unified AI platforms as the operational backbone of next-generation “frontier firms.” Visit Cloud Wars for more.

In this episode of the AI Agent & Copilot Podcast, host Tom Smith speaks with Vaishali Vinay, Data Scientist at Microsoft, and Raghav Bhatta, Data Scientist at Microsoft, about their upcoming masterclass at the 2026 AI Agent & Copilot Summit NA in San Diego. They discuss how AI can serve as a threat research partner for cybersecurity teams, augmenting human expertise in threat hunting and detection engineering while helping organizations proactively defend against increasingly sophisticated cyber attacks.

Key Takeaways

AI as a Threat Research Partner: Vinay explains that traditional threat hunting and detection engineering have historically been highly manual processes requiring significant time and expertise. AI can now assist by analyzing attacker behavior and identifying detection opportunities faster. As Vinay notes, the goal is to augment our human experts and accelerate this threat research process much faster.

Scaling Cyber Defense in an AI-Powered Threat Landscape: Bhatta highlights that as AI adoption grows across industries, the volume of data and potential attack vectors increases rapidly. Organizations must therefore adapt AI for defensive purposes as well. “The amount of data which is produced… is increasing at a nonlinear scale,” Bhatta explains. AI copilots help defenders process this scale by assisting with detection engineering, threat hunting, and proactive defense strategies that protect infrastructure and customers from evolving cyber threats.

Capturing and Sharing ‘Tribal Knowledge’ Through AI: Cybersecurity often depends on the deep experience of veteran researchers who understand attacker behavior patterns. Bhatta suggests AI copilots can help scale that expertise across teams. He explains that copilots can serve as a “source of tribal knowledge,” enabling newer analysts and teams to leverage insights that historically lived only in the heads of experienced researchers. This dramatically increases productivity and knowledge transfer within security organizations.

AI Attackers vs. AI Defenders: The session also acknowledges that cyber attackers are increasingly leveraging AI themselves. That makes defensive innovation essential. Vinay and Bhatta emphasize the importance of building AI systems that analyze attack techniques and automatically recommend detection rules. This dynamic defense model enables security teams to react faster to emerging threats and reduces the manual workload traditionally required to understand complex attack patterns.

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In today's Cloud Wars Minute, I look at why the AI economy is fueling unprecedented demand for cloud services and pushing the world’s top vendors into hypergrowth again.

Highlights

00:03 — Things are off to a hot start here in early 2026 with the growth rates for the world's top cloud and AI vendors within the Cloud Wars Top 10 growing nicely across the board here because of the demand from customers for AI and cloud services. In fact, we're seeing the return of hypergrowth, 40% or higher growth rates.

00:27 — Hadn't seen that for a while, and this installment of the Cloud Wars Growth Chart we've got three vendors in that category: Palantir at 70%, Google Cloud at 48%, Oracle at 44%. Behind this all is massive customer demand for cloud and AI services, data, agents, and insights as companies prepare themselves for the rapidly approaching AI economy.

01:47 — Palantir, as I said, was number one, 70%, just over $1.4 billion in revenue last quarter. Google Cloud: 48% to $17.7 billion. Oracle: 44%, $8.9 billion in cloud revenue in its most recent quarter. Microsoft: 26% growth rate on $51.5 billion — by far the largest cloud and AI services vendor.

02:41 — And then SAP in a tie with Microsoft here for fourth place: 26% growth, $6.6 billion in revenue. Across the board for all of the Top 10 companies, we saw an increase in the growth rate from the last time I did the Cloud Wars Growth Chart, which was in mid-December.

03:47 — Businesses are expressing and showing enormous demand for these AI and cloud services. And I think in that context it's important to remember we're just at the beginning of this. As customers see what can be done with AI and advanced cloud services, there's going to be more demand.

04:19 — Because of the incredible competitive dynamics among the Cloud Wars Top 10 companies, the pace of innovation from the vendors is rising. We can expect continued remarkable demand feeding into the Cloud Wars Top 10 — what may be the greatest growth market the world has ever known.

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