Cloud Wars Live with Bob Evans

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. Visit Cloud Wars for more.

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. Visit Cloud Wars for more.

Key Takeaways Agent transactions: With models like the Universal Commerce Protocol, Google aims to control global agent transactions, relying on Mastercard’s verifiable financial infrastructure to make it viable. Filling voids: Similar to how MCP secures agent access to internal systems, verifiable intent enables agents to securely transact on behalf of humans by closing three gaps in the purchase flow; it secures transactions by validating agent identity, ensures strict adherence to user instructions, and confirms the transaction occurred. Big picture: Google and Mastercard are racing to lay the foundation for agentic commerce, but if no single standard wins, fragmented protocols could recreate the same consumer confusion seen in past payment wars—all hinging on the assumption that agents will define the future of commerce. Visit Cloud Wars for more.

In today’s Cloud Wars Minute, I explore how Oracle is embedding more than 1,000 AI agents into its applications to transform entire industry ecosystems. Highlights 01:18 — I think what we're seeing now here at the cusp of the agentic AI boom is the opportunity for modern technology to transform not just individual companies but entire industries and ecosystems. Oracle said it's now got more than 1,000 agents embedded within and working inside Oracle's applications. 02:21 — This is a big effort that goes beyond just what a specific company is doing, and to do that in an industry-specific, targeted way, thus slashing the time to value for customers. This is the sort of automation, insight, transparency, and visibility that many businesses are eager to have. 03:01 — CEO Mike Sicilia said, we've got a few hundred agents up and operating. The customers have been very eager to use this. They're not buying the whole “SaaSpocalypse” nonsense, and instead they've been eager to say, we're currently using some Oracle apps and we'd like to use more, especially the ones that have the agents in there driving new capabilities. 04:02 — They're seeing what he called a halo effect from this, allowing customers to take on more aggressive and ambitious transformations. Innovation, growth, and acceleration are the key things that are happening across these industry layers. 04:48 — What used to be the enterprise apps business is now apps plus agents plus AI plus data. And Oracle says it wants to use this combination of agent-powered applications so that it and its customers can be the disruptors rather than becoming the disrupted. Visit Cloud Wars for more.

Key Takeaways Shift in AI focus: As Director of AI at Armanino, Montgomery explains that organizations are shifting from last year’s AI experimentation and demos toward defining real business use cases and operationalizing AI; embedding it into processes, insights, governance, and workforce interactions to transform how the business runs. Session overview: One of her sessions, "From Insight to Intuition: Designing Copilot Experiences that Understand People," will provide “a practical blueprint for designing Copilot and agent experiences that people can trust and use,” addressing the gap between building AI systems and thoughtfully designing how employees interact with them. Learning objectives: Turning on Copilot often leads to early experimentation but a dip in trust as users encounter vague outputs, prompt fatigue, and unclear accountability because the experience wasn’t intentionally designed. Montgomery's masterclass introduces an “agent experience” framework called CARE — context, awareness, relationships, and empathy — to help organizations design AI systems that are trustworthy, accountable, and effective in business workflows. Event relevance: The event, explains Montgomery, comes at “an inflection point with AI adoption across businesses,” bringing together technical and business leaders to help organizations move from exploring AI’s possibilities to deploying it responsibly and at scale across their operations. Visit Cloud Wars for more.

Key Takeaways Smart friction: AI prioritizes speed and efficiency, but in retail experiences where shoppers value engagement, intentional friction can enhance customer satisfaction and ultimately drive better returns, giving rise to the idea of "smart friction." Use case: Trader Joe’s, for example, deliberately avoids self-checkout to create smart friction, using wait time to immerse customers in design, promote product discovery, and foster interactions with staff that enhance the overall brand experience. By preserving the elements that make its brand special rather than blindly automating for speed, the grocery retailer has been able to stay competitive despite having fewer locations than many rivals. Don't over-automate: While many AI solutions will benefit enterprises, organizations should be careful not to automate away the core elements that define and differentiate their brand. Visit Cloud Wars for more.

In this episode of the AI Agent & Copilot Podcast, Giuseppe Ianni, host of the show, is joined by Andrea Pinillos, Senior Technical Program Manager at Microsoft, to discuss practical strategies for enterprise adoption of AI agents and copilots. Pinillos shares insights from her work leading internal Microsoft tooling and previews her upcoming session at the 2026 AI Agent & Copilot Summit NA. Key Takeaways Democratizing AI with Simple Tools: Pinillos emphasizes that organizations don’t need complex infrastructure to begin using AI agents. By combining tools like Excel and Copilot Studio, teams can quickly prototype useful solutions such as employee directories. Her goal is to lower barriers to adoption so more teams can experiment safely. Governance Must Come First: One of Pinillos’ strongest recommendations is to establish governance before deploying AI agents at scale. Organizations often rush into building tools without clear rules about ownership, permissions, or oversight. According to Pinillos, responsible adoption starts with planning. She stresses the importance of “making sure that your organization is making [this] an important factor." Real-World Demonstrations Accelerate Adoption: Pinillos’ summit session focuses heavily on practical learning through demonstration. Rather than discussing theory, she will show attendees exactly how to connect Copilot Studio to an Excel data source, build actions, and enable conversational interaction with data. She believes hands-on demonstrations help organizations move from curiosity to implementation. Visit Cloud Wars for more.

In today's Cloud Wars Minute, I explore how Microsoft is using Copilot Studio and multi-agent orchestration to dramatically improve customer support performance. Highlights 00:09 — Now, one of the best ways to assess the impact of Microsoft Copilot is to examine case studies of the technology in action. Microsoft has announced details of a recent project delivered through Copilot Studio, aimed at enhancing the customer support experience on microsoft.com, building on the Ask Microsoft web agent created using Microsoft Copilot Studio. 00:51 — This new approach resulted in a 61% reduction in latency and up to 70% fewer human escalations. The Microsoft team tested and refined the original web assistant, getting it live within just a few weeks using Copilot Studio tools. 01:11 — However, it was the facilities multi-agent orchestration feature that truly enhanced this project, enabling the team to connect the main agent to sub-agents with domain-specific knowledge in areas such as Azure or Microsoft 365 . 01:34 — Firstly, Microsoft is presenting a very tangible use case for Copilot Studio here. Secondly, it highlights the speed at which Copilot Studio can be used to rapidly deploy and easily edit agentic workflows. And finally, it serves as a really good advertisement for multi-agent architecture and orchestration, which I believe unlocks the most capable AI performance. Visit Cloud Wars for more.

Key Takeaways Session overview: AI is a transformative technology where security is lagging dangerously behind. Polino's session, "A Guide to Security Roles in AI Transformation (Implementation)," will explore why it's critical for organizations to reassess current roles, controls, and systems and proactively design security strategies specifically for an AI-driven environment. Guardrails: AI systems can be easily manipulated through indirect prompts or parameter framing, making it essential to enforce extremely strict guidelines and access controls to prevent unintended exposure of sensitive data. Exploring security with leaders: Organizations must proactively define security policies and controls for AI now to prevent users from going rogue or turning to shadow IT, because inaction will only amplify risk as sensitive data inevitably leaks into unsecured public AI tools. Event takeaways: Polino notes the importance of events like this because they bridge the knowledge gap between AI leaders and everyday business users by equipping them to understand AI early and effectively transfer that knowledge across their organizations. "AI is coming, whether you want it or not. The goal here is to figure out how to use it appropriately, how to make it as safe as you possibly can, and mitigate those risks inside your organization." Visit Cloud Wars for more.