Cloud Wars Live with Bob Evans

In today's Cloud Wars Agent and Copilot Minute, I explore how Microsoft's new AI-powered phishing detection in Teams could transform cybersecurity while raising important questions about user privacy. Highlights 00:10 — Microsoft is introducing a new AI feature to Teams that will detect phishing attempts and scams by analyzing conversations. Now, rather than relying solely on traditional methods of detecting malicious links and files, it uses behavior-based detection to identify suspicious activity in messages. 00:28 — The feature will initially run silently in the background, with warnings potentially appearing when phishing is detected. It will also prioritize conversations with new contacts, as the risk here is generally higher. This is a great use of AI. It shows how companies can use the technology to approach problems differently. In this case, by analyzing behavior at scale to strengthen a company's cybersecurity defenses. 01:03 — Microsoft says message content won't be retained for AI training or other secondary uses, and it says the feature will only be used for security purposes. Now, the rollout is due to begin in November 2026, with general availability expected in the first half of December this year. Crucially, it will be enabled automatically, without requiring IT administrators to configure it. 01:31 — And that's where, for me, things get interesting, complicated. Think back to Microsoft Recall. That's that controversial AI feature that took screenshots of users' screens and was initially planned to be enabled by default. Now, following some pretty significant privacy and security concerns, Microsoft went back to the drawing board and made saving screenshots on Microsoft Recall an opt-in feature. 01:51 — So, introducing another automatically enabled AI feature that analyzes, again, conversations raises an obvious question: Has Microsoft learned from its past mistakes, or is it repeating them? Visit Cloud Wars for more.

In this special episode of Cloud Wars Live from Workday Rising 2026, Bob Evans speaks with Rupesh Ahluwalia, Vice President of HR Information Systems at Concentrix, about how artificial intelligence and enterprise technology are transforming human resources. With more than 430,000 employees across over 80 countries, Concentrix is reimagining how HR supports its global workforce while expanding its technology-driven business. Ahluwalia discusses the company's decade-long relationship with Workday, the growing importance of workforce adaptability , and why meaningful AI transformation must go beyond automation to deliver more intuitive, people-centered employee experiences. Workday Powers HR Transformation The Big Themes HR Becomes a Strategic Driver : At Concentrix, HR is far more than a traditional back-office function. With more than 430,000 employees across over 80 countries, the company recognizes that its people are its greatest asset. Ahluwalia explains that HR has consistently held a prominent role in organizational decision-making, particularly as Concentrix has expanded through mergers and acquisitions. Rather than separating HR from technological innovation, the company actively integrates its approximately 3,000 HR professionals into technology adoption and business transformation. Adaptability Becomes the Essential Skill : Hiring more than 200,000 people annually creates significant workforce planning challenges, especially as emerging technologies introduce roles and skills that barely existed a year earlier. Ahluwalia highlights an unusual recruitment dilemma: How does a company interview candidates for positions when the necessary expertise does not yet exist internally? His answer emphasizes adaptability over mastery of any particular programming language or technical function. AI Transformation Must Go Beyond Automation: For Ahluwalia, the greatest opportunity presented by AI is not simply making existing workflows faster. While automating manual tasks and improving efficiency remain valuable, he argues that organizations must question whether certain processes need to exist at all. Concentrix is exploring how AI can fundamentally redesign work rather than merely optimize established procedures. This distinction becomes particularly important at scale, where approximately 50,000 managers still perform activities such as employee performance reviews. Instead of focusing exclusively on simplifying those tasks, Ahluwalia challenges his team to envision a future in which technology completes some activities on employees' behalf. Big Quote : "We are not looking at saying, okay, can we automate this workflow and reduce 5% of the headcount? We are looking at can we automate that workflow, which reduces the friction in the process and people use the systems better." Learn More About Concentrix and Workday: Check out this information on Workday AI and learn more about Concentrix . Visit Cloud Wars for more.

In today's Cloud Wars Minute, I challenge Oracle's skeptics and explain why its aggressive AI infrastructure investments could position the company for extraordinary growth. Highlights 00:03 — Oracle made a significant announcement last week. It had nothing to do, really, with its technology or partnerships, although those have been remarkable. It had to do with what I have called the monkey on its back, the negative cash flow monkey on its back. And in light of that announcement, I'm recommending to all the Oracle skeptics out there: just breathe. 01:06 — Oracle's already got the incredible demand in the form of contracted business, almost as much as Microsoft has built up in this cloud and AI backlog. No other company ever in the tech industry, in any other industry, has ever assembled a backlog as big as the one Oracle has. 01:47 — In the next three years, that backlog will convert to $332 billion of revenue. So, this is a company with a huge business, customers lined up, demand is there. It's building out the capacity to meet that. To do that buildout, it had to borrow some money, but the big thing is the demand is there. 03:29 — Its RPO is already, like I said, $664 billion. The only company with a bigger RPO backlog is Microsoft, which is $677 billion. So, you know, Oracle's almost on pace with them, bigger than AWS, bigger than Google Cloud. So, at AI World, they had this ambitious product blitz and also partnerships at AI World that are showing that Oracle's not sitting back. 04:00 — Its whole huge portfolio is now 100% oriented around AI. The partnerships are going to push them into new areas, new capabilities. It's partnering with Google to use Google TPUs. It had Sam Altman from OpenAI there. It's infusing OpenAI's technologies throughout all of Oracle's software suite. Its database business is picking up, especially with the Oracle AI Database coming out now. 04:29 — I think that you know I understand why some people say, "Huh, nobody's done this before. What if it doesn't work?" But, Oracle's way of doing things is always say, "Hey, nobody's done this before. We will make it work", and I've got a link in this article to a great presentation at the Oracle Investor Day by the president of Oracle Cloud Infrastructure , Mahesh Tiagarajan, in which he explains how they're doing that to scale the build out of these data centers. Visit Cloud Wars for more.

In today’s Cloud Wars Minute, I break down the growth rates of the hyperscalers and the remarkable comeback AWS is making with its latest growth rates. Highlights 00:03 — AWS reported strong earnings. While its Q3 growth rate was 39%, up to $46 billion, Amazon CEO Andy Jassy said that AWS will hit hypergrowth of 40% or higher throughout all of 2027 and 2028. This is the sixth straight quarter in which AWS has had accelerating growth. This is a remarkable comeback to its growth rates a few years ago. 01:17 — To put it in perspective, that is 39% growth for AWS, 30% growth for Microsoft, and 103% growth for Google Cloud. With the size of AWS, it rolls up to getting closed to an annualized run rate of $200 billion. Microsoft is at about a $250 billion annualized run rate. Google Cloud is at about a $125 billion run rate. Across these three hyperscalers, there's very strong growth overall. 02:44 — Bedrock inference service is undergoing surging growth. Token volume is up 17 times over a year ago and the spending from Fortune 500 is up by seven times. Looking back a few months, AWS's chip business has hit greater than a $25 billion run rate. The AI business, as of three months ago, was at $25 billion. 04:05 — Each of these hyperscaler companies had the opportunity, over the last few years, to go into or develop any products and services they wanted that would best meet the needs of enterprise companies. The ones that are innovating the most directly, effectively, and rapidly along the lines of what customers want will be the winners. Visit Cloud Wars for more.

At Oracle AI World in Las Vegas, Cloud Wars host Bob Evans sits down with Bonnie Tinder, founder and CEO of Raven Intelligence, to explore what enterprise customers are actually experiencing as they implement artificial intelligence. Drawing on conversations with seven Oracle customers across industries, including Heathrow Airport, Baylor University, and Northwell Health, Tinder identifies the critical factors shaping successful AI adoption. Oracle AI Gets Real The Big Themes: Clean Data Drives AI Success: Clean, reliable data emerged as the most important foundation for successful enterprise AI adoption across all seven customer conversations Bonnie Tinder conducted at Oracle AI World. Organizations emphasized that their systems of record needed to be established and optimized before AI could deliver meaningful value. Baylor University, which implemented Oracle applications in 2020, spent several years strengthening its data foundation before expanding AI-enabled workflows. Employee Trust Determines AI Adoption: Trust emerged as a recurring theme. Organizations recognize that employees need confidence in AI-generated information before they will consistently embrace new workflows or recommendations. Introducing unreliable systems or poorly designed processes can damage that confidence and undermine subsequent technology initiatives. Consequently, customers emphasized careful implementation, credible outputs, and practical applications that improve employees' daily experiences. Enterprise AI Must Enable Action : The conversation ultimately centered on the transition from systems that record information to systems that help organizations take action. Evans observed that AI is becoming increasingly effective at identifying previously hidden problems, including potential employee turnover, security vulnerabilities , maintenance requirements, and fraud risks. However, uncovering these challenges creates additional responsibilities for business leaders. Tinder argued that organizations must use predictive insights to prevent problems from escalating rather than simply accumulating more information about potential risks. The Big Quote: "I mean, you could look at the problems that it surfaces and get depressed about it, or you can like actually do something to ensure that those problems don't escalate and snowball." More from Bonnie Tinder: Connect with Bonnie on LinkedIn and learn more about Oracle's latest advances . Visit Cloud Wars for more.

In today's Cloud Wars Minute, I analyze the extraordinary growth of Google Cloud, Microsoft's impressive performance, and the changing competitive dynamics of the AI revolution. Highlights 00:02 — Earlier this week, we got Q3 results from both Google Cloud and Microsoft, and I think the big news for me about both those, while both companies performed very, very well and the growth is really eye-popping, Google Cloud, for the three months ended September 30, is growing three and a half times faster than Microsoft Cloud. 00:36 — Microsoft Cloud revenue grew 30% to $63.9 billion. So, I'm not in any way trying to criticize what Microsoft did here. I mean it's the equivalent of a $250 billion business growing at 30%. That's just unprecedented, unheard of. 01:43 — This isn't a flash in the pan or a one-time thing. Let's look at the growth rates for Google Cloud and Microsoft Cloud over the last seven quarters. Taking nothing away from Microsoft, but the comparison here is striking. And in a detailed article later this morning, I got a couple of bar charts on there that show quite graphically the differences in the growth trajectories of these two stellar companies. 02:38 — And it really is striking, the difference between Google Cloud going like this and Microsoft just barely better than flat. So, I want to again say kudos to Microsoft. It's got a company now, with its growth over the next few quarters on an annualized basis, it's somewhere between a $250 billion and $300 billion company, and the last quarter growing at 30%. 04:18 — Google Cloud added an incremental $5.9 billion in Q3 versus Q2. Microsoft added an incremental $4.6 billion. So, while Microsoft's overall number is bigger, and it deserves full credit for that, Google Cloud is winning more new business quarter to quarter, right here, right now, than Microsoft is, and that is stunning. Visit Cloud Wars for more.

In today's Cloud Wars Minute, I examine how Larry Ellison, Mike Sicilia, and Clay Magouyrk are positioning Oracle for its next phase of AI-driven growth. Highlights 00:03 —We're here at Oracle AI World in Las Vegas, and really, the last couple days, were an AI innovation blitz across technologies, partnerships , go-to-market plans, across the whole breadth of Oracle's portfolio, and some striking new technology vendors that some might consider potentially competitors of Oracle's now coming in with partnerships. 01:24 — Oracle is accelerating, and what I like to point out to anybody who talks about the debt issues: yes, that's real. It's not an ideal thing, but there's a time sequence that's going on here. And what the great news is for Oracle is, with $664 billion in backlog , or RPO, it's got plenty of money in line that's going to be converted to revenue. 02:13 — Google, a few months ago, said it was going to start to offer its TPU chips on the market to others. Oracle is now the first hyperscaler to deploy those. Snowflake and Oracle have created a native AI data service that's going to make it easier for enterprises to access and act upon all of their data. 03:32 — But, I thought the highlight at the end of the day, Larry Ellison came out on stage. There had been some question, you know, was he going to appear here? He no longer participates in the earnings calls, and he came out. It was really quite a moving discussion. He talked by himself for a little bit about the Oracle healthcare applications, the full suite they've put together, the impact AI is going to have on that. 04:33 — He said he believes that, with the help of AI, that all cancers are going to be eradicated in the next five to 10 years. He said it'll certainly be 10 years. Said it might be as soon as five, and he said, imagine if you can project into other industries the benefits and the achievements that AI can help deliver there. 05:00 — The CEOs, Mike Sicilia and Clay Magouyrk, both gave impressive keynotes. They both showed that they're not just in the position of CEO, but they're in control of the company and steering its future direction. And then you've got the extraordinary, you know, once-in-a-lifetime visionary Larry Ellison helping to guide things along from the chairman's point of view. Visit Cloud Wars for more.

In today's Cloud Wars Minute, I explore the growing security threats facing AI agents and why Microsoft is investing in protecting organizations from emerging attacks. Highlights 00:25 — All these different breaches [are] happening in the space of agents ... because there's an opportunity here for people to be able to consume and utilize tokens from other providers. It's going to be a situation where we've got to keep an eye on this now. 00:44 — One of the most recent intrusions was a CERT India firm, and they didn't see any of the actual issues come in from the breach that they recently had. And this is very interesting because who then reported it? How do we know that there was a breach? The answer is that the actual providers of the different platforms are actually seeing these breaches, not the actual people being breached. 01:33 — So. what we are seeing is companies like Microsoft, with their Defender, can now pick up 60 different agent types that might be doing something nefarious within organizations. So, what we're going to see is a general view across this that we need a way to be able to secure and make sure that people are not actually getting access to information they shouldn't through agent-based technology. 02:00 — Now, even the Microsoft security chief had said that frontier models cannot be trusted. Now, does this mean that we can't trust the AI model to do something or not to do something? It's more along the lines that these models will want to solve a problem, so they will go and they will try to figure out a way to solve the problem. 03:26 — Two goals: one is make sure that we don't see any breaches happening, and number two is that we also want to make sure that we don't see people attacking for denial-of-service attacks or trying to take on and use AI credits from another organization. And I will leave you with this: Satya Nadella himself said, "We simply can't outsource responsibility for what intelligence does on our behalf," and that's very true. Visit Cloud Wars for more.

In today’s Cloud Wars Minute, I analyze Microsoft’s ambitious Maia 300 rollout and how owning its own AI chips could give the company greater control over its AI infrastructure, improve efficiency, and reduce its reliance on NVIDIA. Highlights 00:10 — Microsoft has announced Maia 300 , the company's latest custom AI chip. It's also revealed plans to expand its Azure Maia systems to multi-gigawatt deployments starting in 2027, and with this rollout, Maia will become the primary AI inference system for Microsoft products and services. 01:02 — Microsoft expects Maia 300 to deliver 40% more tokens per megawatt than leading GPU-based systems. In other words, Microsoft expects to deliver more AI output for the same amount of power. That's crucial as demand for AI services continues to skyrocket. Now, Microsoft also says that in a full configuration, Maia 300 systems are expected to deliver up to seven times the rack-scale token throughput of Maia 200. 01:41 — Bear in mind that Maia 200 is already a very capable system, and Maia 300 really builds on those foundations — I'm going to quote Microsoft here: "To enable more coding with GitHub, more flexible AI model deployment through Microsoft Foundry, and faster interactions with Copilot, Teams, and Dragon Copilot." Now, back to that incredibly important point I made at the start. 02:05 — Maia is set to become the primary AI inference system for Microsoft products and services. Now, back in August, I talked about what this could mean for NVIDIA. My conclusion was that Microsoft's own chips could help level the playing field and give the company more options. 02:33 — Could Microsoft chips potentially challenge NVIDIA in the market? I think that remains to be seen. Microsoft's announcement certainly seems to suggest that it will have more control over its AI infrastructure , but it doesn't necessarily mean that NVIDIA is being pushed out of the picture altogether. What is clear, though, is that Microsoft is moving towards a much more full-circle AI business with its own chips, cloud infrastructure, models, and applications. Visit Cloud Wars for more.

In today’s Cloud Wars AI Minute, I break down Nscale’s rapid shift from Bitcoin mining to AI data centers and why its enormous contracted backlog raises important questions about the risks and realities of scaling AI infrastructure. Highlights 0:05 — So, one of the things that I wanted to bring up, because as I was doing my research, I ran across Nscale. Now, Nscale is probably the biggest company that none of you even know who they are, and it's basically a data center hyperscaler. 1:48 — So, this company that literally has $103.4 billion in the ability for them to go and contract is only making $140.6 million as of H1 2026 revenue. So, that means they're way off of their revenue targets against what they're actually having to invest. If you take like 85% of what this company is funded by, it's funded by Anthropic, which is about $44.6 billion, and Microsoft at $43.88 billion, and that's primarily the workloads that they have, and that's why their H1 net loss is about $1.02 billion. 3:03 — And they've got these hardware contracts to be able to go do it. But those contracts need hardware, and so it's really interesting to see all the movement in this space. Because is this company overleveraged? We're not quite sure. 3:21 — In the last 24 hours, we saw Microsoft walk away from a contract, and then Anthropic doubling down on a contract with this particular vendor. So, it's going to become very interesting to see what happens as we watch this market expand, as the demand for data center capacity continues to grow, and companies like Nscale have the ability to sign these really big deals and these big contracts. Visit Cloud Wars for more.

In today's Cloud Wars Minute, I discuss why Oracle must continue delivering innovation and financial growth while reassuring investors about its debt and Larry Ellison's leadership presence. Highlights 00:15 — On the one hand, Oracle has got this incredible momentum in its cloud and AI business, and a staggering volume of RPO backlog, but at the same time, there's lingering and ongoing concern about the level of debt that Oracle has had to take on in order to fund the buildout of these AI data centers across the country and around the world. 00:49 — It's got to continue its innovation blitz across all the things it's doing in OCI, with its AI database, its Fusion Agentic applications, and across the full Oracle product lineup. And we'll see that this week at AI World. Now, also, the momentum it's got from its Q1, which ended August 31st: it had OCI revenue up 121% to $7.4 billion, and the guidance for that is very strong going forward. 01:51 — That's not revenue yet, so that's one of the largest backlogs any company's ever had. Microsoft's right now is $678 billion, so just slightly larger than Oracle's. But very few companies have ever had to face a backlog like this and the responsibility to build that out. 02:42 — What Oracle has to do is continue to show product innovation and financial growth. It'll be having a financial analyst meeting later this week at AI World, so we'll see what comes out of that. Now, the other big point here with AI World is: Will Larry Ellison be there? And if so, in what capacity, and what level of visibility will he have? 03:09 —In early September, for the first time ever, Ellison was not present at all on the [earnings] call. He didn't make any statement. He didn't answer any questions. Oracle went public in 1986, and until recently, Ellison was not only on, but he was the heart of those earnings calls, those engagements with the public. He used those to give Oracle's vision of the future and where Oracle was headed, where the technology was headed. Visit Cloud Wars for more.

In today's Cloud Wars Minute, I examine how SAP's AI-first strategy helped drive 26% cloud revenue growth and why Christian Klein believes the momentum is accelerating. Highlights 00:01 — We had some interesting numbers from SAP last week that I talked about: Q3 cloud revenue up 26% to seven and a half billion, and its cloud backlog up 28% to $27 billion. I wanted to chat a little bit today about Christian Klein, the SAP CEO. He said there are three reasons why AI has been so important in helping to generate these sorts of numbers. 00:37 — Here's what he said: There's certainly better technology capable now with AI to help accelerate these migrations, but the big thing, he said, is getting better business outcomes and being able to focus on those. The second thing he said: AI and the enhancements there make the suite, the SAP Business Suite, relative to best-of-breed. He said it makes it much more attractive. 01:12 — And he said the Business AI platform overall has been a huge driver for customers, and especially in this area now around the Business Data Cloud. He said that is the thorny issue that's going to unleash the potential for AI to come in and really help drive these better business outcomes. 02:28 — One of the reasons, I think, is because SAP has been not only going all in on AI for the last few years, but in addition to that, I think Klein has always kept uppermost in his mind: What are the outcomes that are most important for our customers? The business outcomes most important for them, and are we putting the right amount of emphasis on helping deliver those? 03:04 — The important thing here about that is that the Business Data Cloud is unifying all this stuff that SAP has been putting together over the last five decades. How companies work, where their data is, what their processes are like, the industry-specific nature of what they have, and I think this Business Data Cloud, with the various ideas that Klein put forward, I think that's going to be the most important. Visit Cloud Wars for more.

In today's Cloud Wars AI Minute, I examine how GitHub Copilot squads and Claude Code agent teams are changing the way AI agents communicate, collaborate, and solve complex problems. Highlights 00:12 — And today, we want to talk about AI coding squads. We're seeing this change about how we're seeing agents being able to go and work on different, really complex projects. And we used to have this one assistant that would go out and everything else, but now we're starting to see teams of agents going and doing things, and we see different configurations of this. 00:54 — So you could have a front-end developer, a back-end developer, an auditor, all of these different things, and they're just basically different personas. And then the beauty of this is where we talk about something like Claude Code subagents, which has been out for a while. This is more the concept of a task agent, where you have a parent that is going to spin off subagents underneath it. 01:34 — Well, when we get into GitHub Copilot squads, we actually see this changing, where what we're having is that each of these different personas are created as members of a team, and the teams work together to be able to come with, like, a common shared team memory and allow them to be able to communicate back and forth, to be able to assign tasks and collaborate and communicate with one another. 02:02 — And this makes it where you end up with a more robust way of actually solving problems, where you're not having to orchestrate it all through a single, a single agent that's supposed to make the decisions on everything. Now you have different personas that can weigh in their opinions and play their role. You can kind of think of it just the same way you would have a human team. 03:15 — But we're going to start seeing more and more of the different AI creators or the different providers of agents starting to take this tack, where they're going to have more of a squad or a team of agents versus having a parent-child relationship, like we've seen in the past. So, something to keep your eye on and pay attention to as you continue to move forward in your AI journey itself. Visit Cloud Wars for more.

In this episode of Cloud Wars Live, Bob Evans speaks with G2 Krishnamoorthy, Vice President of AWS Databases, about how agentic AI is reshaping enterprise data strategies and accelerating business innovation. Krishnamoorthy explains why AI-ready data foundations, knowledge graphs, and purpose-built databases are critical to unlocking the potential of intelligent agents. The conversation explores how AWS customers are dramatically reducing processing times, why forward deployed engineering is transforming technology partnerships, and how security, interoperability , and infrastructure economics will influence the next generation of enterprise AI applications and database innovation. AWS's AI Data Strategy The Big Themes: AI-Ready Data Foundations Drive Innovation : As enterprises embrace agentic AI, establishing a strong data foundation is becoming essential to unlocking sustainable business value. G2 Krishnamoorthy compares agentic AI to a powerful car and the data foundation to the road it needs to travel. Regardless of how sophisticated AI becomes, organizations must ensure their data is accessible, well-structured, and ready to support innovation. Importantly, these investments extend beyond AI applications. Forward Deployed Engineers Accelerate Transformation : AWS is investing in forward deployed engineering (FDE) to help customers translate emerging technologies into production-ready business solutions. Rather than simply providing database products and technical guidance, AWS engineers work directly within customer environments to understand specific challenges, demonstrate solutions, and support implementation. Krishnamoorthy explains that this approach can span cloud migration, data integration, cataloging, contextual knowledge development, and AI-enabled process redesign. Agentic AI Requires Stronger Security Governance : As AI agents gain the ability to perform actions on behalf of users, security and governance become increasingly critical. Krishnamoorthy identifies two major priorities for AWS: ensuring trusted agentic operations and strengthening defenses against emerging vulnerabilities . AI agents must operate within appropriate authorization, authentication, and auditing controls while maintaining the identity and permissions of the users they represent. AWS is working with Amazon Bedrock and AgentCore capabilities to establish guardrails around agentic experiences. The Big Quote: “You need to have the elasticity. You really need to actually be able be truly effortless in terms of managing capacity. You really want to reduce the cost of operations dramatically." More from G2 Krishnamoorthy: Follow G2 Krishnamoorthy on LinkedIn or learn about knowledge graphs and AgentCore Identity . Visit Cloud Wars for more.

In this episode of Cloud Wars Live, Bob Evans speaks with Gary Miller, Oracle Customer Success Officer and Executive Vice President of Oracle Customer Success Services, about how AI is reshaping enterprise operations and customer expectations. Miller explains why businesses are shifting from AI experimentation to measurable outcomes. He also discusses how Oracle is evolving its customer success strategy to help organizations accelerate adoption while managing costs and security. Looking ahead to Oracle AI World, Miller previews Fusion Claw, AI Success Navigator, and new capabilities designed to speed implementation and deliver business value. Industrializing AI for Business The Big Themes AI Becomes a Business Imperative: Gary Miller explains that enterprise AI conversations have changed dramatically over the past year. Rather than simply exploring AI assistants or experimenting with emerging technologies, organizations are prioritizing measurable business outcomes. Competitive pressure is pushing companies to adopt agentic AI faster, rethink workflows, and demonstrate returns on their investments. Miller describes this transition as moving from the democratization of AI to its industrialization, emphasizing repeatability, efficiency, and disciplined implementation. Industrializing AI Requires Coordination : Miller says that industrializing AI involves much more than providing employees with access to intelligent tools. Organizations need structured processes for discovering, deploying, and reusing existing AI capabilities across departments. Without coordination, companies risk duplicating development efforts, increasing expenses, and undermining their expected returns. For large enterprises, the challenge becomes especially significant when thousands of employees can independently create agents. AI Governance Enables Faster Innovation : As companies accelerate AI adoption, security, governance, and cost management become increasingly important. Miller argues that organizations should establish governance structures before deploying agents extensively. These frameworks must define which data agents can access, what processes they can execute, and when human involvement is required. Oracle's embedded governance capabilities within Fusion provide identity management, access restrictions, and operational boundaries that organizations can use as a foundation for broader AI policies. Big Quote : "Do a pilot, get it into production. Many many initiatives fail between pilot and production, and then scale it and learn from that in continuous innovation. So it's building. I call it building the muscle for ongoing innovation." More from Gary Miller and Oracle: Follow Gary on LinkedIn or learn more about Oracle AI Success Navigator , Fusion Claw , and Oracle AI for Fusion Applications . Visit Cloud Wars for more.

In today's Cloud Wars Minute, I discuss how Christian Klein is transforming SAP from an enterprise applications leader into an AI-powered cloud powerhouse. Highlights 00:01 — We got some big numbers yesterday from SAP for Q3, and one of the highlights of this, I would say, we see acceleration in its cloud revenue growth, acceleration in its current cloud backlog growth, and also in its cloud ERP suite numbers. So, a powerful quarter for SAP across Q3, and you can really see the evidence here of SAP's ambitious AI strategy starting to kick in. 00:36 — Cloud revenue for Q3 is up 26% to $7.5 billion. Last quarter, I think it was 24% growth. Cloud backlog, 28% to $27 billion. Last quarter, it was 27% growth. Cloud ERP suite up 29% to $6.61 billion. Cloud ERP Suite is a subset of their overall cloud revenue. And the company's total revenue, I thought this was interesting, up 13% to $11.5 billion. 01:08 — Now, certainly its traditional license business is going down. We see the rapid cloud growth pulling the whole company upward. Very, very impressive number there, 13%. Also, SAP announced that its full-year cloud guidance is going to hit what it said will be toward the upper end of the range that the company gave earlier this year. 02:19 — The Autonomous Enterprise, the big new brand promise that SAP announced at Sapphire this year. He said it's gaining customers' confidence. It's trying it in parts. It's feeling more and more comfortable with it. And Klein believes that the Autonomous Enterprise is really starting to kick in with the momentum here. 03:40 — So, as the company gets bigger, its growth rate is increasing — a very difficult thing to do. The growth rates that SAP has been putting up for the last several quarters are much higher than its primary competitors in this category. No other big enterprise — I used to call them apps company, but now we have to call them enterprise apps, agents, data, and platform company — is growing nearly as fast as SAP is. Visit Cloud Wars for more.

In today's Cloud Wars Minute, I discuss how Google Cloud's $3 million in computing credits could help European researchers tackle some of science's most persistent challenges. Highlights 00:03 — Google Cloud, alongside Google DeepMind, are planning to give up to 200 leading European scientific researchers direct access to Google's frontier models , as well as $3 million in Google Cloud computing credits. The credits are essentially there to ensure researchers have the computing capacity that they need for their research. 00:27 — So, beyond the models, researchers will also have access to some incredibly powerful tools like AlphaFold 3, a well-known tool that helps predict molecular structures, WeatherNext, a weather forecasting tool, and AlphaGenome, which helps researchers study DNA. This is part of a European initiative supporting the EU's AI for Science initiative called RAISE, the Resource for AI Science in Europe. 01:08 — So, there are the obvious geopolitical impacts here. This is certainly going to give the EU's science and technology sector a boost. But for me, this is actually a lot more significant than those potential economic gains. I see this as a really outstanding demonstration of how we can pivot AI towards solving some of the problems that we've been unable to solve without this model infrastructure. 01:34 — Now, I think we've all been promised a great deal in terms of the potential social impact of AI, targeting those really difficult problems, but I think the onus has been on the developers of this technology, the companies, to make those discoveries. For me, this is a much more targeted and scalable approach. 01:54 — Google's committing resources to the RAISE initiative, but the EU is putting the wider framework in place. This, I think, is how we get to the root of some of our most persistent challenges using AI: by not only developing the technology, but also building the structures that enable it to be put to work where it's needed most, and not making it the sole responsibility of the model developers. Visit Cloud Wars for more.

In today's Cloud Wars Minute, I explore why Google Cloud could achieve an astonishing 90% to 100% revenue growth rate in Q3. Highlights 00:03 — We got some big numbers coming out later this week from SAP for Q3, and then next week we've got Google Cloud, Microsoft, ServiceNow, all on October 28 and October 29. Palantir will release its Q3 numbers the first week of November, but let's take a look here at Google Cloud's Q3. 00:25 — I think there's a very good chance the revenue growth for Q3 could be anywhere from 90% to 95%, even 100%. Let me show you the numbers that drive this thought for me. And again, Alphabet will report its results October 28. If we look over the last four quarters at Google Cloud's growth, its revenue, and its quarter-to-quarter incremental growth, which is becoming for me an extremely important metric, here's what we get. 02:00 — To hit 90% growth for Q3, Google Cloud would have revenue of $28.9 billion, and that would require it to grow in Q3 versus Q2 by $4.1 billion. That's a huge stretch, but look what it did in Q2, $4.8 billion. So even if it brings in less incremental revenue this quarter, they could still grow 90%. 02:48 — Now, to hit this 100% number, its revenue would have to be $30.4 billion. That would require an incremental growth, Q3 versus Q2, of $5.6 billion. It's a big stretch, big number, but if you look at the trajectory here of what they've been doing the past few quarters, it is a big stretch, but it is by no means unreasonable, unfeasible. 04:56 — Say Google Cloud grows only 90%. That is still just phenomenal. Twice as fast, at least, as AWS. About three times faster than Microsoft is growing. 95%, 100% — these are astonishing figures for a business as big as Google Cloud's. It shows just how well the number one company on the Cloud Wars Top 10 is doing here. Visit Cloud Wars for more.

00:10 —Microsoft has launched MAI Transcribe to Streaming, a real-time speech-to-text model and Microsoft's first model in the streaming transcription category. The new model has already proven to be incredibly powerful. 00:31 — It operates in 60 languages with continuous automatic language detection, and according to Microsoft's testing, the new model ranks number one for accuracy in both final and partial transcripts. The new model can handle partial text as the speech is arriving, which means reasoning can begin even before a speaker finishes talking, and this is particularly useful for voice agents . 00:59 — Microsoft is also launching two new voice models, MAI Voice 2.1 and MAI Voice 2.1 Flash. Microsoft has positioned this new Flash model alongside MAI Transcribe to Streaming, and I'm just going to read a line from Microsoft AI on that: "Together, they give users the fast and fluid building blocks to create conversational experiences with no compromise on accuracy or voice quality." 01:26 — Ultimately, Microsoft has set the stage here for a complete solution for voice agents. And I'll quote again from a recent Microsoft AI release: "Pairing MAI Transcribe to Streaming with MAI Voice 2.1 Flash buys time back on both ends. The time saved gives your agent more room to reason, use tools, and check its answer, all while keeping the conversation moving at a human conversational speed." 01:53 — The breadth of AI use cases is so massive that we're seeing more and more of this specificity, even from companies like Microsoft that have massive generalized AI toolkits. But to win in the AI era, it's going to take this kind of mastery of specific use cases, not just delivering a catch-all solution. Thank you for watching. Visit Cloud Wars for more.

Bob Evans welcomes Christopher Lochhead, Head Buccaneer at Category Pirates , to Cloud Wars Live, exploring the extraordinary opportunities and challenges emerging from artificial intelligence. Drawing on decades of experience in technology, entrepreneurship, and category design, Lochhead examines the rise of personal AI, the disruption of digital commerce, California's proposed billionaire tax, and growing concerns about AI regulation and corporate accountability. Trust, Technology, and Entrepreneurship The Big Themes Personal AI Emerges as the Next Frontier : Lochhead argues that artificial intelligence is entering a new phase, moving beyond productivity tools toward personal AI assistants capable of managing everyday activities. While early generative AI applications focused on developers, writers, and content creators, the next major opportunity involves systems that understand users' calendars, communications, relationships, finances, and personal preferences. Lochhead identifies Meta 's Muse as an early example of this emerging category, potentially positioning the company ahead of Apple and Google. AI Shopping Threatens Traditional Commerce Models : The rise of AI-powered shopping assistants could fundamentally transform how consumers discover, evaluate, and purchase products. Lochhead explains that personal AI systems can already recommend purchases based on individual requirements, compare alternatives, and increasingly complete transactions. This development presents a strategic dilemma for major commerce platforms. He contrasts Amazon's reported decision to restrict Muse's shopping capabilities with Spotify's more open approach to AI-driven transactions. AI Regulation Raises Questions About Corporate Motives : Lochhead delivers a forceful critique of Anthropic and broader AI industry narratives surrounding existential risk, sentience, and government regulation. He argues that warnings about catastrophic AI outcomes deserve scrutiny when the same companies continue developing and commercializing increasingly powerful systems. In his view, calls for strict regulation could also serve commercial objectives by restricting open-source competition and limiting corporate liability. More about Christopher Lochhead and the topics discussed in this podcaast: Connect with Christopher Lochhead on LinkedIn and learn about Anthropic's vision of Claude's character and California's billionaire tax debate . Visit Cloud Wars for more.