Cloud Wars Live with Bob Evans

At Google Cloud Next in Las Vegas, Bob Evans sat down with Karen Dahut, CEO of Google Public Sector, to discuss how AI, security, and open cloud strategies are reshaping government services. Dahut shared how Google Public Sector was built on the belief that government agencies deserve the same advanced commercial technologies as private enterprises, and why that decision is now proving critical in the era of agentic AI.

AI Reinvents Government

The Big Themes:

Commercial Cloud for Government: Karen Dahut explained that when Thomas Kurian became CEO of Google Cloud in 2019, he challenged the outdated assumption that public sector organizations should receive different or lesser technology than private enterprises. Instead of building a separate, restricted GovCloud environment, Google chose to accredit its full commercial cloud for government use. This gave agencies access to the same scalability, resiliency, and innovation cycles as Fortune 100 companies. That decision is especially important now because AI workloads demand enormous scale.

Leadership Makes AI Real: Technology alone does not create transformation — leadership does. Dahut highlighted examples from the FDA, Department of Transportation, and the City of Los Angeles, where visionary leaders are actively driving AI adoption rather than waiting for change to happen. These executives are not simply buying software; they are rethinking how agencies operate, from transportation systems to drug discovery to citizen services. Dahut stressed that real AI success requires courage, education, and enablement alongside strong technology.

Open Cloud Is Responsible Government: Dahut strongly argued that openness is not optional in public sector technology, it is the only responsible approach. Governments operate with decades of legacy systems, massive backlogs of information, and multimodal data spread across many environments. Forcing all of that data into one cloud platform would be expensive, slow, and ultimately harmful. Google’s approach is to leave the data where it already exists and analyze it there, avoiding costly ingress and egress fees and preventing vendor lock-in.

The Big Quote: “AI and agentic AI is truly going to be one of those technologies that we look back on 10, 15 years from now and say that was truly the most transformational piece of technology since the transistor.”

More from Karen Dahut and Google Cloud:

Connect with Karen on LinkedIn or learn more about Google Cloud Public Sector.

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In this special episode of Cloud Wars Live, Bob Evans sits down with Steve Miranda, Executive Vice President of Applications Development at Oracle, from Oracle Park in San Francisco to discuss one of the biggest shifts happening in enterprise technology: agentic AI applications. Miranda explains how Oracle is moving beyond embedded AI and AI agents to fully agentic applications that can act on business objectives rather than just automate transactions. From finance and supply chain to HR and customer service, he shares how this transformation is changing operations, competitiveness, employee roles, and the very mindset organizations need to succeed in the AI Era.

Rise of Agentic Apps

The Big Themes:

From AI Features to Agentic Applications: Steve Miranda explains that Oracle’s AI journey has evolved in three major stages. First, Oracle embedded AI directly into applications to help generate and enhance content, improving the traditional user experience. Next came AI agents — workflow-driven systems capable of handling transaction sequences across ERP, HCM, supply chain, and CX. Now Oracle is introducing agentic applications, which represent a full redesign of enterprise software. These systems allow users to set business objectives rather than manually manage transactions. Instead of handling purchase orders, invoices, or approvals individually, users provide strategic guidance while AI agents execute, monitor, and optimize outcomes.

Competitive Advantage Comes from Speed: Miranda stresses that agentic AI is not only about reducing costs through automation — it is about increasing business speed and adaptability. In competitive markets, companies need to react instantly to supply chain disruptions, shifting cash positions, pricing opportunities, and customer demands. Human-driven workflows create delays, while agentic applications can monitor both internal operations and external market conditions in real time. AI can identify early payment discounts, detect supply chain disruptions, or recommend immediate operational adjustments faster than traditional teams. This responsiveness creates a major competitive edge. Companies that adopt agentic applications can operate faster and more efficiently, while those that delay risk falling behind competitors who are able to move at machine speed

Oracle’s Pricing Philosophy Supports Adoption: Miranda explains that Oracle’s pricing philosophy for AI remains intentionally customer-friendly. Core AI improvements — including embedded AI and standard agentic capabilities — are included within existing application subscriptions. Customers subscribing to financials, HCM, supply chain, or other Fusion applications receive these enhancements as part of the normal service evolution, much like database upgrades. Additional charges apply only when customers extend applications further, such as building custom agents or adding specialized workflows through Agent Studio. Those extensions use token-based pricing, which reflects current industry standards for AI usage. This model gives customers both innovation and flexibility: they benefit from improved core functionality without surprise costs, while paying incrementally only when they choose to expand AI into additional areas of the business.

The Big Quote: “We’re essentially rebuilding our applications from the ground up to make them agentic.”

More from Steve Miranda and Oracle:

Connect with Steve on LinkedIn or learn more about Oracle AI Agent for Fusion Applications.

Visit Cloud Wars for more.

In today's Cloud Wars Minute, I explore how Oracle is redefining enterprise software with AI agentic applications.

Highlights

00:03 — One of the biggest stories of the year, maybe the next few years, is going to be the rise of generative AI, the animating force behind business innovation and unlocking new ways for businesses to work, to run, to see the future, to adapt, and to give people higher-value opportunities as well.

00:29 — Oracle, I think, has been the most articulate and the most active in framing out how agents and applications are going to work together in the future. There has been this false choice brought up that it would be apps or agents, but that is not where things are headed.

01:09 — What we're seeing now is not going to be apps and agents. Oracle is fusing them together, calling them AI agentic applications. Steve Miranda explained in a longer conversation I had with him how these applications are different, what the business benefits are for customers, and how this new AI agentic revolution is changing enterprise software.

02:34 — Oracle is saying these AI agentic applications will trigger a shift of applications being systems of record to systems of actual outcomes. The agents are going to pursue not just task by task, but business outcomes, business goals, and business objectives.

03:51 — Companies that move quickly will be able to reposition their people to do higher-value work instead of drudge work. The risks of waiting are growing scarier as the pace of innovation increases, and leaders need to aggressively and confidently take on these new technologies.

Check out my longer conversation with Steve Miranda here.

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In this episode of the AI Agent & Copilot Podcast, Cloud Wars Founder Bob Evans is joined by Dona Sarkar, Chief Troublemaker of AI Adoption at Microsoft, who shares her perspective on how leaders should approach AI adoption, why fear around AI replacing jobs is misplaced, and how executives can create a culture of experimentation. Speaking from the 2026 AI Agent & Copilot Summit NA in San Diego, Sarkar explains why organizations need AI-first thinking, stronger leadership involvement, and a focus on solving impossible problems rather than simply improving existing workflows.

Key Takeaways

AI Won’t Replace You — But Someone Using AI Might: Sarkar strongly pushes back against the fear-driven narrative around AI replacing workers. She explains that change does not happen overnight and that professionals should focus on becoming AI power users instead of waiting for disruption to happen to them. As she puts it, “We will be relevant, irrelevant. Who’s they? Exactly. You can be they.” She encourages workers to learn AI within their own discipline (legal, finance, sales, or operations) and become the person who understands how to train, guide, and supervise it. The future belongs to those who learn to “harness its power.”

AI Should Solve Impossible Problems, Not Just Existing Ones: Rather than using AI only to optimize familiar work, Sarkar believes organizations should target the problems they have never been able to solve. She says, “Let’s go solve the problems we’ve never been able to solve because we just don’t have the human capital.” This shift moves AI from being a cost-cutting exercise to a growth engine. Leaders should use AI to uncover opportunities, identify market gaps, and rethink what their companies are capable of delivering in the future.

Focus on Team Productivity, Not Personal Productivity: Sarkar argues that many companies are stuck in outdated AI use cases like meeting summaries and individual task optimization. She believes the real opportunity lies in workflow transformation across teams. “You have to get outside the personal productivity experiments.” By identifying full workflows — like sales enablement or content operations — and improving them with AI agents, companies reduce fear and unlock capacity for new work. AI should create room for innovation and experimentation, not simply make individuals feel more replaceable.

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In this episode of the AI Agent & Copilot Podcast, host Giuseppe Ianni speaks with Parmesh Rajan, VP of Technology for HSO US, live from the AI Agent & Copilot Summit NA in San Diego, California.Rajan explains how organizations are moving beyond experimentation and embedding AI directly into business processes, implementation delivery, and workforce productivity. The discussion highlights a shift from standalone copilots toward operational, production-grade AI agents that deliver measurable outcomes.

Key Takeaways

AI Embedded in Core Operations, Not Add-On Tools: Organizations are moving from experimenting with AI to embedding it directly into enterprise systems and workflows. As Parmesh Rajan explains, the goal is to shorten complex ERP implementations and integrate AI into core business processes like finance, operations, and customer engagement rather than treating it as a standalone capability.

Automation Across the Entire Implementation Lifecycle: HSO is applying AI across the full delivery stack—from gap-fit analysis and solution design to coding assistance and data transformation. This is helping reduce manual effort in traditionally lengthy 12–18 month implementations while improving accuracy and accelerating time to value for customers.

Adoption Depends on Workflow Fit, Not Agent Quantity: Industry-specific AI agents are critical for real-world adoption because they align with how users actually work. Examples like automated timesheets and AI-driven expense processing show that success comes from embedding agents into daily workflows, with effectiveness ultimately measured by usage rather than the number of agents deployed.

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