Cloud Wars Live with Bob Evans

As enterprise AI rapidly evolves from isolated assistants to autonomous systems capable of executing complex business processes, organizations are looking for practical ways to turn AI into measurable business outcomes. In this episode of Cloud Wars Live, Bob Evans speaks with Chris Leone, Executive Vice President of Oracle Applications and AI, Oracle about Oracle's latest innovations in Fusion Agentic Applications, the new Fusion Builder Experience, and AI Studio Skill. Leone explains how Oracle is combining enterprise applications with AI agents to automate work, empower both business users and developers, and help organizations accelerate AI adoption while maintaining enterprise-grade security and governance.

AI That Delivers Outcomes

The Big Themes:

Outcome-Driven AI Changes Everything: Oracle's vision for agentic AI begins with a simple premise: enterprise software should no longer focus primarily on completing tasks — it should focus on delivering business outcomes. Leone explains that Oracle has intentionally designed Fusion Agentic Applications around measurable objectives rather than individual transactions. Instead of asking users to manually coordinate dozens of activities, organizations define a goal, such as reducing supplier spending or shortening inventory lead times, and the application orchestrates the work required to achieve it. Teams of AI agents collaborate, monitor progress, recommend next steps, and increasingly automate execution while keeping humans involved whenever appropriate.

Autonomous Work Is Gradual: Oracle isn't advocating for immediate, fully autonomous enterprises. Instead, Leone introduces the idea of an "autonomy dial" that organizations can gradually increase as confidence grows. Initially, AI agents recommend actions while employees remain responsible for approvals and execution. Over time, companies can allow the system to automatically perform more routine work while humans supervise exceptions and strategic decisions. Leone illustrates this using Oracle's Sourcing Command Center, where customers establish objectives like lowering supplier costs or reducing lead times. The application identifies shortages, creates RFQs, manages supplier auctions, recommends winners, and continuously guides employees throughout the process. As organizations become more comfortable, more of these steps can execute automatically. This phased approach helps customers balance productivity gains with governance, compliance, and trust while steadily reducing repetitive work and allowing employees to concentrate on higher-value business decisions.

Customers Are Moving Fast: Leone describes Oracle's customer base as spanning the full spectrum of AI adoption. Some organizations are already experimenting aggressively with Oracle's newest Builder Experience, posting demonstrations almost immediately after release. Others have successfully deployed Oracle AI capabilities into production, with more than 7,000 customers already using Oracle AI services. Still, others remain cautious, focusing primarily on traditional transactional systems while gradually evaluating AI opportunities. Despite these varying adoption rates, Leone believes Oracle must continue innovating at the leading edge because tomorrow's competition may come from AI-first startups rather than traditional enterprise software vendors.

The Big Quote: "We're truly moving from this system of record that we've been delivering for many years to truly delivering outcomes for our customers."

More from Chris Leone:

Follow Chris Leone on LinkedIn or send a message via Oracle AI for Fusion Applications.

 

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In today's Cloud Wars Minute, I compare Microsoft's and AWS's dramatically different branding strategies for AI deployment services.

Highlights

00:01 — We see here, in the unfolding AI Deployment Wars, some interesting naming conventions from Microsoft and AWS. And if you look at the comparison of these two, I wonder what they were hoping to achieve by this. I mean, I'm sure they wanted to have these names resonate clearly with people, but they picked wildly different names.

00:48 — AWS calls it Forward Deployed Engineering. Now, that is wildly unimaginative, but it's very clear. This is what you're going to get: forward-deployed engineers. That's the heart of it. It'll be both AWS's own FDEs and also some partners. They have three different tiers of services that customers can tap into.

01:22 — Microsoft is calling its company Microsoft Frontier Company, and I think, in a way, that's a little bit of a cross between Star Trek and Little House on the Prairie. Microsoft is sort of positioning this like companies really want to be the first in their field, out on the frontier.

03:13 — I think what business leaders are looking for isn't so much about frontier. What they want is: let's make this stuff work. Let's make it work clearly. Let's show quantifiable results. Let's get our culture right. Let's get our processes optimized. Let's get not only costs taken out of the company, but let's get new revenue streams building here.

04:07 — So I guess, of the two, if I had to pick one that I think was better, I'd have to give the nod to AWS. They're not going to try to impress anybody. They're not going to try to confuse anybody. You want this? This is what it is. So we'll see how this all plays out. But wild times are coming along here.

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As artificial intelligence accelerates both innovation and cyber risk, organizations are facing unprecedented pressure to secure sensitive data while deploying AI at scale. In this episode of Cloud Wars Live, Bob Evans speaks with Vipin Samar, SVP, Software Engineering, Database Security, Oracle, about Oracle's expanded AI security strategy and how the company is helping customers defend against increasingly sophisticated AI-powered attacks. Samar explains Oracle's three-part security philosophy and why removing barriers to rapid patching and risk assessment has become essential in the emerging era of agentic AI.

Winning the AI Security Race

The Big Themes:

AI Has Fundamentally Changed the Cybersecurity Landscape: Vipin Samar argues that artificial intelligence has dramatically shifted the balance between defenders and attackers. While organizations are rapidly adopting agentic AI to improve productivity and automate business processes, the same advances are empowering cybercriminals. Modern large language models can now write software, analyze applications, identify vulnerabilities, and even recommend methods for exploiting those weaknesses. Tasks that once required highly trained hackers and weeks of effort can now be completed in hours by individuals with far less technical expertise.

Speed Has Become a Critical Security Requirement: One of the interview's strongest themes is that cybersecurity now operates on AI timelines rather than human timelines. Samar explains that attackers no longer wait weeks or months to exploit newly discovered vulnerabilities. AI allows them to identify weaknesses, analyze patches, and develop exploits almost immediately after updates become available. That makes rapid patch deployment essential. Oracle is responding by simplifying and accelerating the entire patching lifecycle through automation, database lifecycle management tools, application testing capabilities, and deployment technologies that reduce operational complexity.

Oracle Is Removing Adoption Barriers: Oracle's strategy extends beyond developing new security technology. Samar explains that many organizations delay implementing security improvements because of procurement hurdles, lengthy approval processes, limited budgets, or concerns about operational disruption. Oracle is attempting to eliminate those obstacles by making several enterprise-grade security products available free for a limited time, including Oracle Data Safe, Database Security Assessment capabilities, Database Lifecycle Management Pack, and Exadata Management Pack.

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In today's Cloud Wars Minute, I compare Google's ecosystem-first AI strategy with the hybrid deployment models of Microsoft and AWS.Highlights

00:03 — A crazy new trend here in 2026 has been AI deployment, or agent deployment, agentic transformation. The connection is this remarkable technology that all these AI companies have been pumping out with the desired business goals that business leaders are demanding. You see a couple of different approaches emerging here.

00:26 — The five big AI companies leading the way on this are Google Cloud, Microsoft, AWS, OpenAI, and Anthropic. The only one of those that is going with an exclusively partner ecosystem-led approach for these AI deployments is Google Cloud. I think the big thing is it's going 100% with its ecosystem partners for these AI deployments, for what Google Cloud calls agentic transformation.

01:51 — President, Global Partner Ecosystem, Kevin Ichhpurani has been a very successful in his efforts. He's also been a staunch supporter of this [approach], he says: "We're a technology company. We're really good at doing the technology, and we want to surround ourselves with force multiplying partners who are really good at the deployment. And Google Cloud will be connected with them in some ways."

03:16 — Partner-driven revenue was up 80%. Bookings driven by partners were up 100%, so they doubled. And sales of partner-created solutions on the Google Cloud Marketplace were up 90%. As high-growth as Google Cloud was in 2025, they're moving and growing, expanding at an even more blistering pace here in 2026.

04:36 — Google Cloud has said, "Hey, what we've been doing so far has been working really well. We're going to double down on that with lots of training and incentives for our partners," whereas AWS and Microsoft say, "You know what? We're going to keep working with partners. In some ways, we need to build our own capabilities and expertise."

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Key Takeaways

Solgari's leading innovations: Grant explains that Solgari provides a customer engagement platform built on Azure that extends Microsoft Teams and Dynamics 365 (as well as other CRMs) to capture customer conversations and centralize that data for better engagement. Customers are adopting it to quickly solve specific engagement challenges, gain fast ROI, and apply it to AI strategies to drive more intelligent business outcomes.

AI's role in customer engagement: Companies that centralize customer conversations into a single data platform gain an advantage because AI is only as effective as the data it can access. Grant says customer engagement is "ground zero for AI" as it enables capabilities like automation, sentiment analysis, and sales or service intelligence that improve customer satisfaction, reduce costs, and deliver measurable ROI.

Use case: Grant shares details on Solgari's involvement with AMB Sports & Entertainment, who own the Atlanta Falcons. Solgari helped them unify fan engagement across voice, SMS, email, and WhatsApp within Microsoft Teams and Dynamics 365, creating a repository of fan conversations in Dataverse. By consolidating this data, AMB Sports & Entertainment is now well positioned to "create momentum around their AI strategy."

Final thoughts: In closing, Grant shares why Solgari has shifted its customer and partner conversations away from product demos and toward business outcomes, showing how customer engagement data can evolve into valuable AI use cases over time.

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