Key Takeaways

• Summit expectations: With so many people dipping their toes into the AI, Copilot, and agentic capabilities of Microsoft, Nancie expects the AI Agent & Copilot Summit to be filled with exciting stories about the outcomes and how people are leveraging and benefiting from it. She also anticipates seeing more exploratory customer case studies demonstrating the shift from conversational Copilot side to the agentic side. "I'm expecting to see much more of that understanding, how to use the full capability of the agentic feature."
• Selecting speakers: As part of the AI Agent & Copilot Summit Programming Committee Board, Nancie has been involved with selecting sessions for the event. She considers criteria for sessions, such as applying real-world use cases, demonstrating outcomes, and providing clarity on how organizations are benefiting. "It's less about the fear of 'How do I use this?' We should be able to see a good balance between business and technical perspectives," and how to launch safely, she shares.
• Moving forward in confidence: Those who attend the AI Agent & Copilot Summit will be able to move forward in adopting the technology in confidence and understanding the path to success. It's important to look at the holistic process so the end customers understand all the features available to update business processes as well as be able to work in a co-creation, collaborative way.
• AI impact: Attendees can gain guidance at the event on applying AI within their own careers, as it can add a competitive edge not only to businesses but also at the career level. Individuals can reflect on how AI will impact professional roles and leadership. The event provides a space to consider what career paths look like in the age of AI. "I see this event as an opportunity for people not just to attend sessions but to collaborate and talk with others who are attending so that they can learn from each other and network with each other, and just build their careers."

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In today's Cloud Wars Minute, I cover Oracle's Q2 results.

Highlights

00:19 — One of the hottest Cloud Wars Top 10 companies right now is Oracle. And I want to talk today a little bit about Oracle's Q2 results from last week. I think there's been a little bit of the fog of war, the fog of AI war specifically here, that has obscured the impact behind what's really going on with Oracle's numbers.

01:06 — Let's look at Oracle's RPO (remaining performance obligation) results from Q2. RPO rose 433% to $523 billion. Far bigger than any RPO any other company has in the last three months, due in large part to deals with NVIDIA, Meta, and others not named. These are hard and fast numbers about where Oracle's business is headed in the future

02:36 — What's going on elsewhere? The biggest cloud vendor in the world, Microsoft, its most recent RPO numbers went up 51% to $392 billion. Those are remarkable numbers. Looking forward, customers around AI and cloud are giving far more of their contracted future business to Oracle than to Microsoft.

04:06 — Oracle's OCI cloud business is bigger than its applications business. Its Autonomous Database revenue rose 40%, and its multi-cloud business is up 817%. That number is a little misleading, because the business is relatively new, but I don't know anybody out there who would not want to have businesses growing at 817%.

04:45 — I've been focusing a lot on RPOs for the last two and a half years or so. It's a great indicator of where customers are committing their money for the future. These big contracts that have signed are going into the past. Nothing wrong with that, but that reflects where the money in the past has gone. RPO is showing the future.

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In today's Cloud Wars Agent & Copilot Minute, I explore Microsoft's addition of Mistral Large 3 to its Foundry platform and why it's a major win for developers seeking open, enterprise-ready AI models.

Highlights

00:11 —Microsoft Foundry is a platform from Microsoft, designed for building, customizing, and deploying GenAI applications and agents. It allows users to access over 11,000 models. Recently, Microsoft added a new model to its offerings, Mistral Large 3. Microsoft claims it to be one of the strongest open-weight, Apache-licensed frontier models available on the Microsoft cloud.

00:53 — An open-weight model is similar to an open-source model, but with some differences. In an open-weight AI model, the parameters used to train the model are publicly available, not just for use or viewing, but also for downloading and modifying. More developers are turning to these models because they offer flexibility.

01:40 — Mistral Large 3 is one of the world's leading open models optimized for enterprise applications. It excels in instruction following, long-context comprehension and retention, multimodal reasoning, predictable performance, and applied reasoning. Unlike its closest competitors, Mistral Large 3 is fully open, with Apache 2.0 licensing.

02:08 — Each new model is carefully selected. It's not just a free-for-all. With Foundry, Microsoft is demonstrating its expertise in the space by keenly understanding what developers want—in this case, an open model with real-world enterprise applications. The pace of AI development is such that even incremental changes and improvements dramatically impact how businesses operate.

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Sales, and Matt Hobbs, Cloud Engineering and Data Analytics Platform Leader and Partner at PwC US. Together, they explore how companies can stop overpaying for cloud and instead fund AI innovation by shifting spend from legacy and suboptimal cloud deployments into modern architectures, multi-cloud strategies, and enterprise-grade AI capabilities that actually move the needle on growth, margin, and new business models.

Smarter Cloud, Bigger AI

The Big Themes:

• Built to Cost Less: Oracle entered the cloud market later and designed OCI from the “bare metal up” with off-box virtualization, a low-latency non-blocking network, and significantly lower egress pricing. That means Oracle’s own cost to deliver infrastructure is structurally lower, so they don’t need to “race to zero” with margin-crushing discounts. When customers compare OCI run-rates to first-generation hyperscalers, it’s common to see 40–70% savings at list-to-net, not just in special deals.
• Turning Technical Debt Into Innovation Budget: Hobbs notes that roughly 40% of internal tech budgets are often tied up in technical debt rather than innovation. PwC sees executives searching for ways to unlock capital for AI and growth initiatives, not just trim expenses. Its “Fit for Growth” program looks at where money is tied up in non-differentiating costs (cloud infrastructure being one of the biggest line items) and reallocates that spend into value-creating initiatives. When PwC runs side-by-side economics, they’ve seen OCI’s promised 40–70% savings show up in real deals.
• OCI + PwC: budget creation meets execution: The Oracle–PwC collaboration stands out, the guests argue, because both sides are relentlessly focused on the client outcome rather than maximizing any one platform. PwC validates OCI’s economics and brings the talent to design and execute migrations, process re-invention, and agentic AI programs; Oracle brings a cost-efficient, multi-cloud-friendly infrastructure designed for price-performance and portability.

The Big Quote: “You can burn a lot of money chasing ghosts in this game if you really don't have a very specific use case."

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Bob Evans sits down with Will Grannis, Chief Technology Officer at Google Cloud, to unpack how AI is reshaping both technology stacks and corporate culture. They explore Google Cloud’s Gemini Enterprise platform, the newly upgraded Gemini 3 models, and the rise of agentic AI. Along the way, Will shares customer stories from industries like finance, healthcare, retail, and travel, and even talks about how his own team had to change its habits to benefit from AI.

Inside Google Cloud’s Agentic AI

The Big Themes:

• Models vs. Platforms in the AI Stack: Grannis draws a sharp distinction between AI models like Gemini and the broader platforms that operationalize them. Models determine how intelligent and capable AI workflows are “out of the box,” across tasks like reasoning, multimodal understanding, and conversation. Platforms, by contrast, are how a business injects its own data, processes, and rules to build differentiated IP, brand experiences, and competitive moats. In practice, that means thinking beyond a single chatbot to agentic workflows composed of models, data, tools, and multiple agents working together.
• Culture and Discipline: Grannis describes how even his own team initially struggled to build an internal ops agent to automate sprint reviews, status updates, and reminders. It was only after leadership pushed them to be an exemplar that the agent became reliable and valuable. Things as simple as putting status information in the same place on every slide suddenly mattered. The lesson: AI exposes hidden process chaos. To get leverage from agents, organizations must tighten their operating discipline and be willing to change how they work, not just bolt AI onto old habits.
• Rethinking ROI and Metrics: Traditional, siloed ROI metrics can kill transformational AI efforts before they start. Grannis cites research about AI projects dying at proof-of-concept stage and contrasts that with companies like Verizon, which used AI in the contact center to simultaneously lift revenue, reduce cost, and improve customer satisfaction by turning support calls into sales moments. Instead of chasing a single metric in isolation, he advocates for “bundles” of outcomes anchored in customer experience.

The Big Quote: “We had to be more disciplined about how we conducted our own work. And once we did that, AI’s effectiveness went way up, and then we got the leverage.”

More from Will Grannis and Google Cloud:

Connect with Will Grannis on LinkedIn or learn about Gemini Enterprise.

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Welcome to the Cloud Wars Minute — your daily cloud news and commentary show. Each episode provides insights and perspectives around the “reimagination machine” that is the cloud.

In today’s Cloud Wars Minute, I discuss why culture, mindset, and leadership matter just as much as technology in driving AI transformation, based off my conversation with Will Grannis, CTO, Google Cloud.

Highlights

00:30 — Will has been the Chief Technology Officer at Google Cloud, one of the world’s most advanced technology companies, for almost a decade. So Will’s perspectives on things are pretty powerful, especially in this notion of how corporations unlock the power of AI to drive great outcomes for those companies and their customers or their patients or their stakeholders.

01:10 — One of the first things that Will talked about is the big AI unlock. He said you’ve got to start with thinking about putting the customer at the center of everything, and then build back, build out from there. So reverse-engineer what has to change inside the organization to ensure that the customer outcomes, the customer experience, the customer value, are at the center.

AI Agent & Copilot Summit is an AI-first event to define opportunities, impact, and outcomes with Microsoft Copilot and agents. Building on its 2025 success, the 2026 event takes place March 17-19 in San Diego. Get more details.

02:27 — He talked a lot about the mindset. One customer example was recently BNY Mellon. BNY Mellon has added Gemini Enterprise for its Eliza AI platform, and that is being used now. The Chief Data and AI Officer at BNY Mellon said our AI strategy in the company is simple. He said it’s AI for everyone, AI everywhere, and AI for everything.

03:19 — He said this is something that’s enabled them now to do more things for their customers. It allows their internal people to be much more productive, be more expansive in their analysis, so that they can provide greater value to their customers. Will said it’s been a huge change at the company.

04:06 — So again, I hope you have a chance to check out the whole interview with Will Grannis, the Chief Technology Officer at Google Cloud. You can see it in the links here. Will’s a terrific guy. One of the things you’ll see here is he offers some pretty honest and candid assessments about challenges he himself has faced as the CTO at Google Cloud, and very candidly explains how he got around those.

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Key Takeaways

• Mullican expresses the value of the event, and given that AI and Copilot have matured, the sessions at the 2025 AI Agent & Copilot Summit NA will shift from a focus on experimentation to practical applications that deliver real impact.
• As a returning Programming Committee Board member, Mullican highlights the "unprecedented number of submissions this time around,” making it tough to choose sessions for 2025. The event will offer a mix of visionary talks, practical use cases, and deep dives to serve both tech and business audiences.
• Mullican shares how business leaders can use the event to "adapt to a new reality," as it aims to “cut through the hype” around AI and focus on practical realities. Even though AI offers transformative potential, most businesses will adopt it gradually, using tools like copilots to improve efficiency rather than undergoing radical overnight changes. "I expect that there's going to be a lot of discussion about. It's just these different layers, these different levels of AI hype and truth."

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In today’s Cloud Wars Minute, I look at how IBM and Cisco are teaming up to pioneer long-distance quantum networks.

Highlights

00:03 — Although not the only company invested in the development of quantum computing, IBM is certainly considered the most active. The company has the highest number of patents, a clear road map for fault tolerant quantum systems, and the most prestigious track record across quantum hardware, software and the commercialization of these tools.

00:28 — Now, IBM and Cisco Systems have revealed plans to link a network of quantum computers over long distances — and the result, perhaps the introduction of the quantum internet. Before I get carried away on this, leaders from both IBM and Cisco have confirmed that the technology to power these networks doesn't yet exist, but they are working on it.

00:59 — The bottleneck is getting qubits, the unit of information used by quantum computers, to travel along fiber optic cables between Cisco switches. IBM and Cisco hope to have the first proof-of-concept ready within five years, a network that connects individual, large scale, fault-tolerant quantum computers with the power to run computations over 10s to hundreds of 1000s of qubits.

01:49 — So, why do we need the quantum internet? Well, beyond the massive enhancement in computational power, which is the primary driver for companies to enter this space, if quantum computing itself becomes widespread, we'll need quantum structures in the Internet to protect ourselves from our very own creation.

02:28 — Technology is advancing at an unfathomable speed, and just like in the AI space, we need to ensure it's contained. In fact, researchers at IBM co-developed three of the four quantum resistant algorithms that the U.S. National Institute of Standards and Technology, or NIST, have earmarked for future standardization.

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Highlights

00:24 — I think we’re seeing some very interesting competitive battling between Palantir and ServiceNow, head to head, emerging over two categories. One, this AI platform position that they’re both talking about relentlessly as sort of the core of their strategic value. And secondly, they’re both on this kick now about who is the defining software company of the 21st century, of the generation.

01:57 — Both are talking up the power of the AI platform as the foundation for what companies need to succeed in this new AI-centric future. Which one has the right approach? How are they trying to position their companies, their capabilities, their ecosystems, to be able to take advantage of that? These are some of the things that I get into in detail in a later article.

02:19 — We’ve also got both claiming that their results are just the greatest thing ever relative to the Rule of 40, which is for high-growth companies. You want to have a combination of 20% growth or more for revenue and 20% growth or more for margins, to have those equal 40 or more. Both exceed that number.

03:26 — Who’s got the momentum? Who’s positioning themselves right in this sweet spot for businesses moving into this AI future, right? Who’s going to be able to put together the tools that control the agents, that let all the data that’s needed for IE come through? How are they able to build applications easily on top of this?

04:05 — But right now, I think ServiceNow and Palantir are the ones that have the most focus on this AI platform vision. And it was fun to sort of look at this. In the article, we look at some of the comments from the Q3 earnings call from ServiceNow CEO Bill McDermott, and also from Palantir’s Chief Revenue Officer, Ryan Taylor.

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Key Takeaways

• Agents take center stage: Bensch says last year’s event was focused on Copilot basics and early-stage AI adoption, but 2025 is the year of agents. Organizations are asking how to make agents work securely, how to tap into data through offerings like Work IQ and MCP servers, and how to build governance that actually holds up. Attendees can expect deep dives into security, data extraction, Dataverse, Finance & Operations, and all the new features unveiled at Microsoft Ignite. “Everyone’s hearing agents, agents, agents,” he notes. “So, how do I get them to work?”
• Sessions designed for real adoption—not marketing fluff: This year’s call for speakers exploded from ~160 last year to over 500 submissions, giving planners a far stronger pool of practical, hands-on sessions. The programming committee prioritizes real-world implementations, lessons learned, and “the good, the bad, and the ugly” of AI projects. He stresses that this event is not a product-pitch environment. Instead, sessions will help attendees understand how to build, deploy, and scale agents across modern work, business apps, and development workflows. “We’re looking for empowering people,” Bensch says.
• Where strategy meets execution: Bensch explains that most attendees will fall somewhere between the starting line of AI adoption and mid-stage Copilot integration—but everyone is looking to connect the dots between strategy and execution. From governance to Dataverse to legacy-system integration via computer-use capabilities, sessions will show how companies can extend agent intelligence far beyond Q&A. The setting, including intimate sessions, world-class speakers, and networking events like golf and pickleball at Torrey Pines, creates space for candid, high-impact conversations attendees won’t find at massive trade shows.

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