Cloud Wars Live with Bob Evans

By Bob EvansBusiness News Technology

Cloud Wars Live with Bob Evans episodes

May 01AI Agent & Copilot Podcast: Inside Microsoft’s Vision for AI Agents and the Future of Work
In this episode of the AI Agent & Copilot Podcast, Cloud Wars Founder Bob Evans, is joined by James Lennox, Director of Product, Microsoft, who shares his perspective on AI transformation, enterprise adoption, and the evolving human-AI relationship. Recorded live at the 2026 AI Agent & Copilot Summit NA, Lennox explores how tools like Copilot and Work IQ are reshaping productivity, governance, and innovation across industries.
Key Takeaways
Delegation is the New Productivity Model: Lennox underscores a fundamental shift: “I can delegate those long-running tasks to AI.” This evolution allows humans to move away from repetitive execution and focus on strategic, creative, and decision-driven work. With platforms like Work IQ acting as the “brain behind Copilot,” organizations gain end-to-end visibility into business processes. This changes not just efficiency, but the very nature of work — humans become orchestrators rather than operators, dramatically increasing output and impact across roles.

Governance is the Gateway to Scale: One of the biggest blockers to AI adoption isn’t capability, it’s control. Lennox notes organizations ask: “How do I have the governance and oversight to roll this out at scale?” Tools like Microsoft Agent 365 aim to solve this with “full observability, full control, full security.” Without trust frameworks, AI remains experimental. With them, it becomes operational. This highlights that enterprise AI success depends as much on infrastructure and policy as it does on innovation.

AI is Universally Applicable Across Industries: Lennox observed leaders from diverse sectors, manufacturing, healthcare, and food services, all exploring AI adoption. “There is so much broad applicability…to real business process automation.” This reinforces that AI is not industry-specific but function-specific. Whether it’s document processing or supply chain optimization, AI can integrate into virtually any workflow, making it a universal transformation layer rather than a niche tool.
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10 min
May 01 Google Cloud Blowout Q1 Proves Why It's #1, AWS #7
In today’s Cloud Wars Minute, I analyze the shifting balance of power between Google Cloud and AWS.
Highlights
00:03 — Last week, we had three of the four hyperscalers report their Q1 numbers. It’s been fascinating to look at those. While everybody did very, very well, Google Cloud just had an utterly exceptional, spectacular Q1, and I think the evidence of what we see in these comparative numbers shows why Google Cloud has risen to number one.
00:51 — If we compare side by side, Google Cloud and AWS in Q1 on the growth rate, their revenue, their backlog growth, and the backlog numbers — the growth: 63% to 28%. Now we will certainly hear from a lot of the AWS fanboys that that’s just because there’s a discrepancy in size. That’s true, but it does not cover this discrepancy in growth rate.
01:35 — For Google Cloud, the backlog grew 93% to $462 billion. For AWS, the backlog grew 49% to $364 billion. Really impressive numbers here from AWS, but they play in a market with some other pretty good companies as well. Google Cloud shows 93% backlog growth versus 49%, and $100 billion bigger in backlog total versus AWS.
02:31 — AWS in Q1 had 85% more revenue than Google Cloud. Then how do you explain this backlog discrepancy? It shows that going forward, which is what the backlog shows us, future trends of business, Google Cloud is winning much more business in the future. Google Cloud is winning more new business, and that’s where the game is being played.
03:25 — So clearly, the whole AI boom had a huge impact on these numbers. We saw Microsoft, just to toss this in, Microsoft's growth rate was 29% in Q1, its fiscal Q3, and its RPO, which is its version of backlog, was up, it said, 99% to$ 627 billion. Oracle, its RPO was up 325% to over $550 billion. So, it's just an incredible market here right now.
04:05 — For a long time, AWS has conditioned the market to say AWS is the king of the cloud and it will be forever. That’s just not true anymore. Google Cloud, through innovation and jumping into the AI game early and aggressively, is booming right now, and its core cloud business is doing very well.
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6 min
April 30Why Google Public Sector Built Commercial Cloud for Government Agencies | Cloud Wars Live
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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18 min
April 30Oracle Fusing Apps + Agents: Steve Miranda on Biz Outcomes
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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6 min
April 30Steve Miranda Explains Oracle’s Vision for Agentic Applications
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.
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12 min
April 29AI Agent & Copilot Podcast: Dona Sarkar of Microsoft on Why AI Won’t Replace You—But AI Power Users Will
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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17 min
April 29AI Agent & Copilot Podcast: How HSO Is Embedding AI Agents into Core Business Operations
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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9 min
April 29 Stellantis and Microsoft Scale Enterprise AI with 100+ Transformation Initiatives
In today’s Cloud Wars Minute, I explore how Stellantis and Microsoft are launching one of the most ambitious enterprise AI collaborations yet, spanning engineering, cybersecurity, and large-scale operational transformation.
Highlights
00:09 — Stellantis, the automaker responsible for well-known brands such as Dodge, Jeep, Peugeot, and Ram Trucks, has partnered with Microsoft in a five-year strategic collaboration.
00:19 — The goal of the partnership is to accelerate the company’s digital transformation through advanced AI systems, enhanced cybersecurity measures, and next-generation engineering capabilities. Stellantis has already been an early adopter of AI, embedding the technology directly into its vehicles.
00:38 — Now, by collaborating with Microsoft, the company plans to accelerate this AI momentum across the enterprise. Judson Althoff, EVP and Chief Commercial Officer at Microsoft, explained that combining Stellantis’ global scale and engineering expertise with Microsoft’s trusted cloud, AI, and security platforms will deliver real value for millions of drivers worldwide.
01:03 — In total, the partnership will lead to more than 100 AI initiatives designed to enhance customer care, product development, and operations. This includes AI-powered product development and validation, predictive maintenance and testing, and faster deployment of new digital features and services.
01:48 — This is an incredibly ambitious project — one of the most significant I’ve seen not only in the automotive sector but across AI transformation initiatives overall. I’ll continue following developments closely and sharing updates.
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3 min
April 28Tirthankar Lahiri on Why Agentic AI Must Live Inside the Database | Cloud Wars Live
In this episode of Cloud Wars Live, Bob Evans sits down with Tirthankar Lahiri, Senior Vice President for Mission-Critical Data and AI Engines. Lahiri explains how agentic AI is transforming enterprise applications from simple question-answer systems into action-driven platforms that can reason, remember, and securely execute tasks. He details Oracle’s strategy around unified agent memory, private agent factories, deep data security, and open development standards, all designed to help customers build scalable, secure, and flexible AI systems without added cost.
AI Built Securely
The Big Themes:
Agentic AI Becomes Action-Oriented: Tirthankar Lahiri explains that agentic AI represents the next major step beyond generative AI. While generative AI focused largely on answering questions and producing content, agentic AI is designed to take action. It allows businesses to build systems that can reason, decide, and execute tasks autonomously. Oracle sees this as the future of application development, where AI becomes embedded into workflows rather than functioning as a standalone tool.

Oracle Builds AI Directly Into the Database: Rather than forcing customers to move data across multiple isolated systems, Oracle’s approach is to bring AI directly to the data. Lahiri argues that data is the “ground truth” and moving it creates technical debt, silos, inefficiency, and security vulnerabilities. Oracle’s converged database architecture supports multiple data types, including relational, graph, spatial, and vector, inside one unified environment. This eliminates the need for separate repositories and allows AI agents to access all relevant context without fragmentation.

Deep Data Security Protects Against AI Risks: Lahiri strongly emphasizes that traditional application-layer security is no longer enough in the age of AI. Since AI can generate SQL and potentially bypass interface restrictions through prompt injection, businesses must secure data directly at the source. Oracle calls this “deep data security.” He uses the analogy of protecting valuables in a safe bolted to the floor rather than simply locking the front gate. Even if someone gets inside the house, the valuables remain protected. Similarly, Oracle enforces security policies at the database level, ensuring agents can only access data users are authorized to see.
The Big Quote: "You need to secure data. Need to lock your valuables into the safe deep inside the house."
More from Tirthankar Lahiri and Oracle:
Connect with Lahiri on LinkedIn or learn more about Oracle AI Database.
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22 min
April 28 Google Cloud Bets $750M: Will Microsoft, AWS Match?
In today’s Cloud Wars Minute, I break down Google Cloud’s $750M partner ecosystem investment and its aggressive push to lead the agentic AI transformation race against Microsoft, AWS, and Oracle.
Highlights
00:03 — Last week in Las Vegas, we saw Google Cloud roll out an incredibly broad, deep set of agentic AI technologies and solutions. They’re making a massive push on this. Google Cloud is the number one player in the Cloud Wars Top 10, and they’re looking to really take the big lead in agentic AI transformations for their customers.
00:24 — Now, in parallel with that, we also saw Google Cloud — in addition to all what they’re doing on the tech track — on the go-to-market side. They have put together what they’re calling a $750 million fund for their ecosystem and partners to help them drive AI transformations for customers, right — to help them get better training, to be more technically proficient, to help deploy engineers, and more.
00:53 — So I’m wondering now, in light of this, both the tech splash that Google Cloud made at Next but also now with this push for their partner ecosystem, will Microsoft and AWS match this massive, I would say unprecedented, investment in the ecosystem?
02:26 — You’ve got, not so long ago, I think you could look at what we called broadly the hyperscalers, and it was a little bit hard to differentiate, right? They were just sort of known as this one blob. I think the companies Microsoft, AWS, and Oracle are differentiating themselves now to a vast degree.
02:47 — I think what Google Cloud is trying to do here is say, “Hey, we’re going to do all the stuff we did for you before, but we are going to focus more intensely than any company on Earth on the agentic AI revolution, to provide not just the technology, but the skills that you need from the partner ecosystem."
03:37 — And then it's putting the money behind this to ensure that those partners have the capabilities to do it — and to do it very quickly — because this is a race to see who is going to get that first-mover status. So far, I believe Google Cloud is in that for agentic AI transformations for customers across the globe and across industries.
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5 min

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Cloud Wars analyzes the major cloud vendors from the perspective of business customers. In Cloud Wars Live, Bob Evans talks with both sides about these profoundly transformative technologies, and with…