Cloud Wars Live with Bob Evans

In today's Cloud Wars Minute, I examine three signs that ServiceNow is positioning itself to become a cybersecurity powerhouse. Highlights 00:02 — We've recently seen ServiceNow position itself as a security powerhouse, and I wonder if that is ultimately the grand plan, the grand vision of CEO Bill McDermott. We've heard and seen ServiceNow sort of evolve its overall position. It's tinkered around with the Control Tower platform and so on. We've seen it now centered on this AI Control Tower for business reinvention. 00:50 — So, on July 22, it had its Q2 earnings call, and McDermott's opening remarks were heavily, heavily focused on their fast-growing security business. He said it's the fastest-growing major security vendor in the world. He said it's now the eighth largest. He talked about how quickly that part of ServiceNow's business is growing, and he used some very colorful examples of why this is so important. 01:34 — A couple weeks after that, on August 3, ServiceNow named a new chief marketing officer. That chief marketing officer held the same position, CMO, at Armis, a cybersecurity company that ServiceNow has just acquired. So, of all the people, you know, who might be more involved in platform reinvention, McDermott chose as the company's new CMO somebody who was specializing, at the time of the acquisition, in cybersecurity. 03:41 — This AI Control Tower for business reinvention is very nice, and I think it sounds good. I think it's temporary. I think the cybersecurity place is where they're going to go to. And again, I just track that right back to the July 22 Q2 earnings call. Of all the things in the world Bill McDermott could have chosen to talk about, he could have gone into great detail about the AI Control Tower. 04:39 — I would expect that ServiceNow is going to try to straddle those two areas, AI Control Tower and cybersecurity, saying they're really two sides of the same coin. But I think for customers, it's going to provide a lot of clarity about where the company is headed, where they're going, and how they'll be able to build out unique capabilities across industries. Visit Cloud Wars for more.

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Highlights 00:02 — Workday last week reported its Q2 results. They came in pretty strong, and I think if we look at the tenor of some of the comments that co-founder and CEO Aneel Bhusri made on the Q2 earnings call last week, we'll see that he's generally pretty low-key. But he's quite bullish now about what's going on with the early momentum Workday is gaining from its AI products. 00:49 — First, quick overview of some key Q2 numbers. Subscription revenue was up 13.9% to $2.47 billion. Its current RPO was up 14.2% to just over $9 billion. And for all of fiscal '27, which will end January 31, its guidance now says that the company expects to grow 13% to about $9.945 billion. 01:54 — AI tools drove more than $100 million in annual contract value in Q2. Workday is very excited about that and believes that that shows good evidence of the uptake from customers and the rising demand for these AI solutions. Also, the AI run rate for AI SKUs, as Workday calls it, across the company is now almost $600 million, and it said that's up 200%. 02:55 — And then what I'm calling the power of enterprise context. Bhusri said said, "We're an enterprise context company." And he said that context — who reports to whom, who pays the bills, where different people are organized, and so on — all those little sort of unstructured things that go on within corporations. Workday has it. 03:35 — So, it has been six months now since Aneel Bhusri returned to Workday as CEO. He felt that with the rise of AI, the AI revolution, that it was time Workday needed to have a deep technologist in the CEO spot, leading the company through this tumultuous change. So, he's increased the pace of technology innovation. He has got the growth rate moving back upward. Visit Cloud Wars for more.

In today's Cloud Wars Minute, I break down Microsoft's evolving AI consumption strategy and how it compares with Salesforce, UiPath, and other major industry players. Highlights 00:19 — Microsoft just announced the GitHub Copilot harness for Copilot Studio — a really cool new capability that enables an agentic reasoning loop. 00:33 — As part of this release, it said that on September 1, it's going to start charging for consumption on the GitHub Copilot harness specifically. This is an interesting move for Microsoft because 90% of Fortune 500 organizations have actually given developers a way to be able to explore their curiosity and consume this technology 01:12 — To compare and contrast in this space, Microsoft on the GitHub Copilot harness is giving $0, if you use the Copilot Studio standard harness, there's actually free allocation for developers to go play with this. Now, if we compare this to other players in the industry, such as Salesforce, which Agentforce provides 200,000 Flex Credits to be able to come in. 02:05 — What I would tell you is that I'm expecting that this is going to not necessarily be something that will be able to continue in a market where there's a lot of demand. Just to give you perspective, when GitHub Copilot was doing this before, it took about seven weeks for them to realize that there was a problem with this, and they corrected it. 02:50 — This is lining up to Satya Nadella back on July 29th, saying that it's evolving its business model to go beyond per-seat licenses and are leaning into consumption. So, we will continue to see these types of things, and I expect to see other growing pains like this for all vendors as consumption starts to become the new metric. Visit Cloud Wars for more.

In today's Cloud Wars Minute, I look at how Google Cloud is expanding the Gemini ecosystem into the automotive world through its partnership with Mahindra. Highlights 00:03 — Google Cloud is partnering with the Indian automobile manufacturer Mahindra to get Gemini Enterprise installed directly into its vehicles. That's another interesting example that we're seeing here of AI leaping out of the digital space and becoming something much more physical. 00:23 — In this new development, the automotive agent in Gemini Enterprise is being integrated into MAIA, Mahindra's Artificial Intelligence Architecture platform. Beyond being a voice assistant, Gemini can understand natural language requests and actually interact with a car and its functions. 00:41 — Sashi Sreedharan, Managing Director of Google Cloud India, explained that "by enhancing its in-vehicle assistant with an automotive agent built on Gemini Enterprise, Mahindra is creating personalized and helpful conversational interactions for navigation, search, media communication, and other vehicle controls that will help drivers navigate and explore rich features in a more natural and helpful way." 01:13 — What we're seeing here is pretty significant: AI operating at the edge, with this idea of the digital and physical working together, and the car becoming the AI endpoint. This is also a really important way for Google Cloud to expand the Gemini ecosystem beyond smartphones, PCs, and enterprise software. 01:37 — The real opportunity that I see here isn't necessarily about Gemini as an AI assistant, but where the tech is embedded; it's those all-important endpoints. Visit Cloud Wars for more.

In today's Cloud Wars Minute, I look at how AI monetization is moving beyond execution and into creation as agentic development becomes more costly and valuable. Highlights 00:15 — One of the things that I want to talk about today is the meter moving upstream. A lot of this has to do with the fact that what we're starting to see is that the cost that is associated with the actual build process is starting to get really high. And the reason behind that is the concept of an agentic reasoning loop and the cost that's associated with the build process. 01:35 — And what you're starting to see is that the build is actually costing a lot more because of the fact that we're using these different AI models in an agentic reasoning loop to be able to go do the build process. An example of this would be Microsoft starting to charge for the creation of agents inside of Copilot Studio. 02:03 — This is not something that's new in the industry because of the fact that we see other vendors that have tried this across the board. An example is that is exactly what you see in GitHub Copilot and Claude Code. These are definitely going to be tools that are building and being able to execute, and we're seeing a massive amount of adoption in this space to be able to allow builders to be able to build. 02:49 — We definitely are going to see some movement in this space. We're probably going to see each of these different vendors want to compete on who can give the best experience and do it in a cost-effective way. It's going to be very interesting to see how this starts to play in the concept of discoverability of different products and of different vendors. Visit Cloud Wars for more.

In today's Cloud Wars Minute, I analyze Salesforce's latest results and why Dreamforce could be critical for proving its AI opportunity is here now. Highlights 00:03 — Salesforce yesterday released its Q2 results, and I'd say that while there's some very good things in there, it's a little bit of a mixed bag relative to what some other companies in its category are doing. But let's take a look at this because I think the big, the big news here, aside from the numbers, is Salesforce announced a huge new partnership with Anthropic. 00:41 — Customers will be able to tap into the power of Anthropic reasoning with their Salesforce applications and agents and data. So I think that offers a lot of potential for the future. But some of the key numbers here: we saw Salesforce revenue go up 11% for Q2, ended July 31. That's $11.3 billion relative to Q1. 01:30 — Its AI and data products—starting to break those out—said they now have an annualized revenue run rate of about $3.85 billion, almost $3.9 billion. It said that's up 210%, and then for Agentforce, annualized run rate of almost $1.5 billion, it said that's up 240%, and this, that. 02:43 — Combine that with the incredible presence of Salesforce applications and agents all over the world, all sorts of businesses. Bring those together. I'm sure for Anthropic, this is great too, as they aspire to become an enterprise powerhouse. The Salesforce partnership and connection here gives them entrée to some huge customers and huge opportunities. 04:21 — It's got to step up the urgency on that, and I think the deal with Anthropic is going to be just the medicine that's needed here for Salesforce. Got a detailed article that'll go into this on CloudWars.com, and we'll be following up more next week with the analysis of what Marc Benioff and others talked about on the earnings call. Visit Cloud Wars for more.

In today's Cloud Wars AI Minute, I explore why falling token prices aren't necessarily making AI transactions cheaper. Highlights 00:01 — So, one of the things that I want to talk about today is going to be the token economy. And what we're actually seeing is that tokens are about 12 times cheaper than they've been before. 01:30 — But what we're seeing is the average cost of a transaction is actually going up, and that is because of the fact that while token prices are coming down, the amount of tokens it takes to process something is actually going up. We're actually seeing a 520 percent increase in the amount of tokens that you're going to need to have per unit of work. 01:56 — And the reason behind this has been this agentic reasoning loop and the reasoning models that are starting to go and process. As a matter of fact, you're actually seeing that most recently, we've even seen that chat-based things and chat conversations that have happened between humans and agents have actually now, for the first time, started to fall off. 02:30 — So, if this industry trend continues, what you're going to see is that we're going to continue to see this drop. But what we want to see is we want to start also seeing some sort of normalization and drop happening on the average amount of tokens spent on a per-transaction basis. Visit Cloud Wars for more.

In today's Cloud Wars Minute, I explain why Workday believes AI security is becoming an ecosystem problem that no single vendor can solve independently. Highlights 00:06 — Workday has become the latest organization to join the Open Secure AI Alliance. It's a well-supported initiative that aims to improve the security of AI systems through open-source tools, research, and knowledge sharing. Workday's joining this alliance, and it's in very good company alongside companies like NVIDIA, Cloudflare, Microsoft, and IBM. 00:31 — I want to read a short passage from Workday's joining announcement to give you a sense of why the company chose to join the alliance. So, from Workday: “Delivering safe, trusted enterprise AI requires multiple layers of protection across the entire application stack, from identity management and access permissions to continuous guardrails, monitoring, and governance.” 00:53 — “Our commitment to continuously build our internal security engineering programs to meet these high standards is why Workday is joining the Open Secure AI Alliance.” Enterprise AI is shifting quickly towards more open stacks and more ambitious agents. Initiatives like the Open Secure AI Alliance are incredibly important. 01:22 — Workday and the other members of the alliance recognize that AI security is quickly becoming an ecosystem problem, not just something that one vendor can solve independently. And that's why, for example, Workday specifically said that it has historically worked on security internally for its own platform, but now is sharing what it's learned with the wider community. 01:50 — As AI becomes more open, distributed, and agentic, securing models isn't going to be enough. The challenge now, and that's one that Workday and the other members of the alliance are trying to address, is securing everything around these models. Visit Cloud Wars for more.

In today's Cloud Wars Minute, I examine why the emerging Google Cloud and Oracle alliance could reshape how enterprises accelerate their AI transformations. Highlights 00:01 — Interesting to see some new and different combinations of partners moving forward here in the AI Revolution, because the pace at which customers have to move, their escalating business, competitive pressures, their new technology requirements, and just the urgency they're all feeling to innovate, move into their AI transformations as quickly as possible, is leading to some unexpected combinations of companies and new sorts of enhanced partnerships. 00:33 — So, I think a real power pair that is emerging are the number one and number two companies on the Cloud Wars Top 10, Google Cloud and Oracle, and I think they're coming together. Each has sort of put forward into the mix, not some peripheral products they have, but really, in each case, sort of the crown jewels for what's happening right now. 01:26 — Google Cloud for Q2 had revenue of almost $25 billion, up a remarkable 82%. Meanwhile, its backlog soared 390% to $514 billion. Oracle, for the quarter ended May 31 — and it'll have its new numbers out in a couple of weeks — but for the quarter ended May 31, its fiscal Q4, its cloud revenue was almost $10 billion, up 47%. 02:50 — So, really, each company has put forward the very best it has to offer in this new and extended partnership. And again, I think we're going to see more and more of these sorts of groundbreaking, unprecedented, or certainly unexpected partnerships going forward, because what customers want and need now is changing so rapidly. 03:47 — So, this is a great, great new step forward for customers. And again, I think we're seeing lots of different combinations among the Cloud Wars Top 10 companies. So, these partnerships, alliances, whatever you want to call them, they're more important than ever before. Visit Cloud Wars for more.

00:03 — According to recent reports, Microsoft is set to reveal its Maia 300 AI accelerator as early as September this year. For context, Microsoft launched Maia 200 back in January with the direct aim of reducing the cost of AI inference. 00:27 — The Maia 300 is expected to support both AI training and inference, but the key story here is the scale of ambition behind it. Now, Microsoft is once again partnering with TSMC, Taiwan Semiconductor Manufacturing Company, who delivered the first iteration of Maia chips. However, this time, the scale is much larger. increasing from tens of thousands of Maia 200 accelerator units. 00:54 — It's increasing from tens of thousands of Maia 200 accelerator units to potentially hundreds of thousands, or even over a million Maia 300 chips. For me, this initiative is really about Azure. By investing in these chips, Microsoft isn't necessarily trying to compete with NVIDIA. Rather, it aims to ensure that Azure doesn't rely entirely on NVIDIA infrastructure. 01:14 — This move will give Microsoft greater control over the cost, supply, and performance of the AI infrastructure running on Azure. And beyond that, Microsoft CEO Satya Nadella has stated that building the company's own silicon to work alongside NVIDIA and AMD chips is a priority. 01:35 — The successful launch of Maia 200 demonstrated that Microsoft's custom silicon strategy can work, albeit on a relatively small scale. The hope now is that Maia 300 will enable Microsoft to scale this strategy into a genuine competitive advantage for Azure. Visit Cloud Wars for more.

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Bob Evans speaks with Chad Wahlquist, an Architect at Palantir, about what is driving the company's extraordinary growth and, more importantly, what customers are getting from its technology. Wahlquist argues that Palantir's momentum comes from helping enterprises solve difficult operational problems rather than simply deploying AI or chasing model benchmarks. Their conversation explores AI sovereignty, business outcomes, Palantir's Ontology, LLM complexity, customer operating leverage, and the importance of retaining control over enterprise decision-making. Outcomes Over AI Hype   The Big Themes: Outcomes Drive Palantir's Growth: Wahlquist connects Palantir's growth to the tangible returns customers see after adopting its technology. Rather than treating AI as a standalone investment or another piece of enterprise software, customers increasingly expand their Palantir relationships because successful initial projects create opportunities for broader deployment. He points to strong net dollar retention as evidence that existing customers are spending more after experiencing ROI. The underlying philosophy is straightforward: when an investment generates meaningful business value, executives are willing to repeat and expand it. Production LLMs Create New Problems: Getting an LLM working is only the beginning. Wahlquist discusses the stochastic and probabilistic nature of models, changing provider guardrails, security requirements, model deprecations, and unpredictable behavior across edge cases. Technically switching from one model to another might appear simple, but ensuring that a replacement works reliably across production workflows is significantly harder. This creates a fundamental enterprise question: how do businesses build durable operations on technology whose behavior and availability can change? Protect the Enterprise Decision Loop: One of the conversation's most important ideas is that a business can be understood as a collection of decisions. Companies continually observe data, apply logic, take actions, measure outcomes, and adjust future decisions. Wahlquist calls that feedback loop a source of business “alpha” — the proprietary knowledge that helps one organization outperform another. As AI agents become participants in enterprise decision-making, ownership of that loop becomes increasingly important. Companies should understand who controls the data, logic, actions, outcomes, and learning generated through those processes. The Big Quote: “LLMs don't just magically fix everything. They also create new problems that you have to go solve.” Visit Cloud Wars for more.

00:03 — We've had a lot of big numbers come out for Q2 reports. Google Cloud is at 82 percent. AWS growth jumped up to 37 percent. But I have to take a little more time here to dig into what I'm calling the Palantir phenomenon. Here's a company that, over the last three quarters, has seen its growth rate go from 71 percent to 85 percent to 93 percent. 01:12 — What are customers asking Palantir right now to do for them? That may seem like a goofy, simple question. But if you grow at 93%, you have to be doing something special. What is it that customers are asking for, and that Palantir is delivering, that drove this 93% growth? Chad goes into a lot of detail about that and offers some unique insights there. 02:34 — I think that that's still valid, but the bigger issue now around sovereignty is who controls your data, and not only the data, but how that data is being used to drive AI output. Palantir is making the case that the large language model companies are incorporating the data and everything that goes with it into their own models. 03:27 — Finally, we had a fun conversation considering this company that has grown 93%. It is predicting that the U.S. commercial business, for the next year, will grow 134 percent, but Palantir doesn't have prices for its software. 04:00 — They go in. They talk about what the customer wants to do. They say, "Okay, given that, if we drive the value you're looking for, you pay us this." And then, as that seems to be working quite well, the customer often comes back and says, "Hey, that was terrific. Let's do this, this, and this in addition." Visit Cloud Wars for more.

  00:03 — In a big coup for Salesforce, the Pentagon has approved the use of its Missionforce national security platform to launch AI agents on the most sensitive unclassified missions, and that's because it's been granted Impact Level Five, or IL5 , authorization. 00:21 — The first major user will be Army Human Resources Command, which will use the technology to help with soldier and family support and everyday admin tasks. Later, there will be other use cases, including recruiting, personnel management, and logistics. The big thing here is that Salesforce AI can now take actions and automate workflows. 00:47 — Handling routine tasks while human specialists can stay in the background and remain responsible for sensitive decisions. For the Pentagon, this is quite a jump, moving from AI that, beforehand, solely advised to AI that can actually execute tasks autonomously in military operations. That's no small thing, and I think the fact that Salesforce has won this contract is a massive reflection. 01:14 — On the level of security and governance that the company has in place around its agentic infrastructure, and that will certainly be an attractive proposition for customers. Government contracts always help to boost the credentials of a company, but here, in the age of AI, to have a government department okay the use of agents in an autonomous capacity is a very big win indeed. Visit Cloud Wars for more.

In this special episode of Cloud Wars, Bob Evans speaks with Garrett Lord, co-founder and CEO of Handshake, about one of the biggest challenges facing enterprises today: turning the extraordinary promise of AI into measurable business outcomes. Lord explains why AI agents have delivered dramatic productivity gains in software engineering but have yet to achieve comparable results across many other knowledge-work domains. Making AI Agents Work AI's ROI Gap Persists: Enterprises are enthusiastic about AI and are spending heavily on tokens, but Lord says meaningful returns remain uneven. Software engineering has emerged as the standout, with AI agents producing what he describes as two- to threefold productivity improvements and increasingly executing lengthy assignments autonomously. The challenge is translating that success into disciplines such as finance, manufacturing, retail, oil and gas, and insurance. In these areas, agents can generate presentations, emails, and briefing documents, but they aren't yet consistently transforming complex, long-running workflows. Evaluations Define What 'Good' Means: Lord repeatedly returns to evaluations as the foundation for enterprise AI. Because models are nondeterministic, companies can't assume an agent will reliably produce the desired result simply because it performed well once. Instead, businesses need to codify what successful performance actually looks like across their specific workflows. Lord compares an evaluation to a product requirements document: it creates a measurable baseline against which an agent can continuously improve. Once organizations can evaluate performance, they can improve their agents and harnesses, decide which models are appropriate for particular jobs. Long-Horizon Work Is the Frontier: Generating an email or presentation is fundamentally different from completing a 20-hour investment-banking assignment. Lord describes knowledge work as a complex trajectory involving data rooms, Outlook, Slack, Excel, Bloomberg, FactSet, colleagues, and potentially hundreds of individual actions. Humans continuously manage context while navigating those systems, but today's AI agents still struggle to execute these long-horizon workflows reliably outside software engineering. That distinction helps explain why impressive AI demonstrations haven't always translated into enterprise transformation. The Big Quote: “The point that most enterprises are at right now is they want to bring agents into production beyond software engineering.” Visit Cloud Wars for more.

In today's Cloud Wars AI Minute, I break down the rise of agentic reasoning loops and why their impact on AI token consumption and costs could be significant. Highlights 00:12 — Today's topic is going to be agentic reasoning loops. Everyone's moving to this concept where we can have a planning, act, observe, and reflect type of process, which allows us to be able to get much deeper analysis and much more resilient implementations across AI, across the world. 01:03 — Now, the other thing is with this, we're seeing that about 33% of enterprise software will run on this kind of approach by 2028. Also, the other part of this is that because these different loops are taking place, we're actually seeing that tokens are going to get more and more consumption happening off the back end. 01:38 — So one of the driving factors of this is going to be the increase that we're seeing, and just to give you perspective of what we're starting to see, it's about a 17x on a single chapter that we're starting to see happen as a result of this. So what it used to do when we just did simple RAG patterns. 02:01 — Now we're seeing about 17 times the amount of tokens being consumed, and when we start seeing that level of token consumption, we're going to see that while we're getting better answers, there's also going to be a higher cost that's associated to it. 02:28 — But it doesn't matter that the tokens are necessarily coming down in cost because of the fact that what we used to see is that an average transaction would be about three cents, and now we're seeing it move to about 15 cents across the board, and so this is going to be one of those things that we really need to be thinking about as you start to build out your solutions. Visit Cloud Wars for more.

In today's Cloud Wars Minute, I look at why Palantir's approach to AI sovereignty, sales, and customer value deserves the software industry's attention. Highlights 00:02 — I wanted to talk a little bit more today about Palantir, and I know I've been mentioning the company, digging into what they did in Q2 and their discussions about customer developments, the huge advances some customers are making as they use Palantir. 00:18 — And the reason I want to do this is because when a company almost doubles its growth rate against some very intense competition, that deserves extra scrutiny. What's going on there? Why is this happening? So, today I wanted to take a look at the CEO of Palantir, Alex Karp, as the company posted recently its Q2 numbers. 01:31 — Just to recap, Q2 Palantir's revenues soared 93% to 1.9 billion dollars. Their U.S. commercial business grew 149 percent and is now almost bigger than their government business, and their net revenue retention was up 157 percent, which shows that once customers start to work with Palantir, they quickly accelerate the investments they're making with Palantir. 02:26 — His first point, he said, there is a revolution underway for independence and for AI sovereignty. He said this is well underway. It's taking place. Businesses are going to demand that they be in control of their data and all the metadata surrounding that, the processes, the related workflows, that give the great value to that data as it's used for AI outcomes. 03:10 — His second big point, he said, we are accomplishing this stunning industry-best growth, while he said we have a minuscule and shrinking sales headcount. So, while Palantir has been undergoing this incredible growth rate, they've been reducing the size of their sales organization. 04:21 — The third point, he said, we've always aspired to be paid as a derivative of value creation for customers. So, they don't have a price list. He's saying, we set up an agreement up front with customers that said if, in working with us at Palantir, you achieve the business outcomes you want and we're a significant contributor to that, then we will extract our fees, our payment, our revenue as a derivative of that value that's being created for the customer. Visit Cloud Wars for more.

In today's Cloud Wars Minute, I look at why Oracle is rejecting a single-model AI strategy and embracing a flexible, multi-model future. Highlights 00:03 — Oracle has announced that it's extending its partnership with Google Cloud and will be making Google's Gemini models available across its enterprise AI portfolio. This includes Oracle Fusion Cloud Applications, NetSuite, Oracle AI Agent Studio, and Oracle Cloud Infrastructure, or OCI. 00:22 — In true Oracle style, the company will embed Gemini into business applications and AI agents, allowing customers the flexibility to use Google's models within their existing workflows. At the same time, customers will have the freedom to switch between the various models offered in Oracle's suite. Now, what this is doing is giving customers more choice when they build Fusion-native agents and agentic apps. 00:53 — Oracle and Google Cloud already have a strong relationship, but the broader story here is how Oracle is positioning itself as an AI control plane that delivers outstanding infrastructure without the need to roll out a host of foundation models itself. Now, the company is really embedding itself in this area, and I think it's working out incredibly well for it. 01:17 — The company has really pushed the idea of flexibility, interoperability, and choice. Now, Oracle, from very early on, has really avoided that single-model strategy, saying that's a strategy that's aging quickly, and instead, Oracle's building a platform that can adapt as the AI landscape continues to evolve. 01:40 — I think this really ties in with the ambitions of those enterprises that want to take advantage of rapid AI developments while still controlling their data, applications, and workflows. And that's where Oracle stands out in its ability to bring together infrastructure, applications, and multiple AI models while seamlessly enabling companies to maximize the benefits of the latest AI developments. Visit Cloud Wars for more.

In today's Cloud Wars AI Minute, I break down the rapid rise of forward deployment engineering and why getting AI into production is becoming the next competitive advantage. Highlights 00:10 — Today, the topic is going to be why we're seeing AI move to forward deployment engineering type of scenarios, and this industry trend has actually increased in just year-over-year growth of forward deployment engineering job postings in just the first half of 2026, increasing by 1,000%. 01:29 — You actually have to get to deployment, and the big problem there is that between 88 to 95% of all AI pilots that are being built today are actually never actually getting to production. So we have a whole lot of interest in the market and a lot of stuff that's being really cool and is being done, but we're not actually seeing it get to production. Hence the need for FDE, or forward deployment engineers. 02:04 — Two, you actually have embedded engineers to go help a client to be able to get up and get going. And just to give you guys a typical situation here, now we're starting to see a lot of the pay for these type of roles. They're getting very, very valuable in this market space. 03:04 — So this is a major, major shift in what we're seeing, and it's also why even in DCI and our training offering, I'm looking at building out how to be able to move toward an FDE-type approach engagement, specifically for partners, because you're gonna really have to think about how you move to AI being able to get about 99% code coverage in order to be able to play in this space and be able to have fixed-fee, high-quality implementations that actually drive into production implementations. Visit Cloud Wars for more.

In today's Cloud Wars Minute, I explain why ServiceNow's fast-growing security business is becoming central to Bill McDermott's AI strategy. Highlights 00:01 — I wanted to chat a little bit about ServiceNow's Q2 performance, but mostly what CEO Bill McDermott disclosed on the Q2 earnings call. Very strong performance across the board. They beat on all their numbers, doing very nicely. And what McDermott did, what he used the Q2 earnings call for in his opening remarks, was to lay out what I think is a significant new direction. 01:15 — Now, on top of that, we see a lot of anxiety from businesses now about — while they see the huge potential of AI, they also see that it raises security to levels that it hasn't been at before. So McDermott is sort of pairing those things up: the fully integrated Control Tower plus security plus governance. 02:14 — He said, “We're going to be able to handle all that simply and easily for customers.” He said that whichever chip wins, whichever lab wins, whichever price-per-token regime wins, he said, ServiceNow is going to be able to handle that. You're not — any of the customers aren't going to be, you know, going down a dead end or a dead-end alley if they choose to work with ServiceNow. 03:23 — He said CEOs have been losing sleep over this idea of risk at scale, and we're going to help those CEOs sleep well at night. So it's a big promise. It's a big adaptation for ServiceNow, but I think it's one that's consistent with some of the steps that McDermott has been making in the past, and it's very timely now to bring these two forces together. 03:59 — Now, one of the things that has made McDermott so successful over his seven years at ServiceNow, and before that at SAP, is his ability to use these earnings calls as almost like a come-to-Jesus discussion of where we as a company are, where the external market is with customers, and how aligned we are not just with where customers are now, but where they're heading. Visit Cloud Wars for more.

In this special episode of Cloud Wars Live, Bob Evans speaks with Manish Sood, founder and CEO of Reltio, about the rapidly changing relationship among enterprise data, AI, and business strategy following SAP's acquisition of Reltio. Sood explains why trusted, interoperable data is becoming increasingly important as enterprises embrace agentic AI and autonomous business processes. He also discusses why AI models themselves may increasingly become commoditized, how organizations can bridge legacy and next-generation technology, and the ideas behind his new book, Agentic Intelligence: Strategy at the Speed of Data. Data Powers Agentic AI Data Becomes the Differentiator: Sood argues that enterprises should stop viewing data simply as another asset and instead recognize it as an interoperable asset that becomes more valuable as it is put to work across the organization. This distinction becomes particularly important as AI capabilities spread. If businesses eventually gain access to broadly comparable AI models, competitive differentiation will increasingly come from proprietary enterprise knowledge: decades of customer information, operational history, relationships, and business context. AI Creates Unavoidable Urgency: Enterprise transformation once proceeded at what Sood describes as a relatively organic pace. AI has fundamentally changed that dynamic by creating an enormous pull on organizations to move more quickly. Executives might still feel uncertainty about AI, but another fear has become even stronger: getting left behind. That competitive pressure is creating urgency around experimentation, investment, and execution. Sood sees this as potentially healthy because it forces organizations to reconsider technology and processes that previously seemed difficult to change. Strategy Still Beats Shiny Objects: AI's extraordinary pace doesn't eliminate the fundamentals of good business strategy. Sood notes that every major technology cycle produces a new "shiny object" that organizations race to adopt, sometimes before determining the architecture, strategy, and business value required to make it useful. AI shouldn't become another example. Enterprises absolutely need to embrace the technology, but Sood argues that they cannot sacrifice disciplined thinking about what they are trying to accomplish. That idea sits at the center of Agentic Intelligence. The Big Quote: "Our thesis has always been that data is not just an asset. Data is the interoperable asset that needs to be used.” More from Manish Sood and Reltio: Follow Manish on LinkedIn and learn more about Reltio and SAP at the following links: Reltio: Agentic AI Readiness Research, SAP Business Data Cloud, and Reltio: Building a Foundation for Agentic AI Visit Cloud Wars for more.

In today's Cloud Wars Minute, I explore Oracle's major $7 billion Pentagon contract and what it means for the company's government and enterprise ambitions. Highlights 00:03 —The Pentagon has awarded Oracle a major 10-year contract worth up to $7 billion, sending the company's shares around 3% higher in extended trading. On the news, investors are clearly happy to see another major government win here for Oracle. 00:22 — The agreement will see Oracle's software deployed across on-prem data centers used by the U.S. military, intelligence agencies, and Coast Guard. But the contract covers far more than just software licenses. It also includes long-term maintenance, technical support, and consulting services, which will ultimately provide Oracle with a steady stream of recurring revenue over the next decade. 00:50 — This deal is also pretty significant in the wider Cloud Wars and shows how Oracle's ongoing investment in its OCI platform is helping it win these really high-profile enterprise and government contracts. 01:05 — And also for customers, really its enterprise customers, this contract is a really important endorsement of Oracle's technology and its ability to support some of the world's most challenging and sensitive IT environments, and crucially, at a massive scale. Visit Cloud Wars for more.

In today's Cloud Wars Minute, I analyze the extraordinary RPO growth at Microsoft, Oracle, Google Cloud, and AWS and what it signals about AI demand. Highlights 00:03 — We've got another example here where, in the greatest growth market the world has ever known, we are working with some big numbers that put the law of big numbers to the test here. So, if you look at the four hyperscalers, and I go in order of the size of their backlog or RPO, you've got Microsoft, Oracle, Google Cloud, and AWS. 00:29 — So this is fully committed business. It's fully contracted and not yet recognized as revenue. So this is what's coming down the road, to look into the pipeline, in the future, these companies have — this isn't some guesstimate of what they hope they'll get. This is signed, contracted business. So this is one of the factors, probably the key factor, behind why you see these CapEx numbers approaching or exceeding $200 billion. 01:09 — Now that has led to a couple of these companies entering into the debt markets to try to fund this data center expansion and all that enormous CapEx outlay that they've got to go through. In turn, a couple of these companies for a quarter or two had negative cash flows, and that's got some people on Wall Street unable to comprehend it. The world's coming to an end. What are we going to do? 01:46 — I think the perspective is being switched here, right? Traditionally, the idea is bad. You don't want to have negative cash flow. Okay, that's pretty basic. I think we got that. The difference is there have never been a market with a size, a total addressable market , anything like this, growing at the rate this is. Look at these latest numbers for the four hyperscalers. 02:23 — Oracle, off a much smaller revenue base, has this huge future business coming in: $638 billion in RPO, growing at 363%. Google Cloud had a huge jump this past Q2, $514 billion in backlog, up 390%, and a resurgent AWS posted its biggest backlog number ever, $496 billion, and I believe that growth rate of 154% for its backlog is much higher than any they've reported over the last five or six quarters. 04:07 — So I think it's significant, but I also think it's being vastly overblown. I just want to say one more time: $2.3 trillion. Now, that's not like a TAM figure. Somebody's saying, "Oh, we think the market for new scooters is going to be $2.3 trillion." These are four companies, just four , not the whole tech industry, and these are their signed, contracted, committed figures for what they've got in their backlog or RPO. Visit Cloud Wars for more.

In today's Cloud Wars Minute, I compare Google Cloud, Microsoft, and AWS to reveal which hyperscaler is winning the most new business. Highlights 00:15 — While all of them had terrific quarters, I'd have to rate it this way: Google Cloud was far and away the best. AWS had a terrific quarter, especially for the way it had been performing before that. Microsoft, at its phenomenal size, had a very good quarter. It's just not growing as quickly, not winning as much new types of business in that way, as the other two. 01:44 — So we had Microsoft go from $54.5 billion to $59.3 billion. So it added $4.8 billion in new revenue in Q2. For Google Cloud, $20 billion to $24.8 billion; it also added $4.8 billion. AWS, $37.6 billion to $42.2 billion. It added $4.6 billion. 02:32 — Yet Google Cloud gained as much new revenue last quarter as Microsoft did, and Google Cloud gained more new revenue than AWS did. So we find that the mix of products and services, the fit to what businesses need right now, Google Cloud is matching what Microsoft's doing, matching or exceeding what AWS is doing. So the size differential is becoming less significant now. 03:27 — What we see with this analysis of the numbers is that Microsoft is not continuing to extend that size differential. The others are chopping into that, and particularly for Google Cloud, at this size and with its growth rate, we see that happening. So, you know, how is this possible? And I think it all comes down to this notion of, you know, the customers have a terrific set of choices here. 05:02 — But in terms of — you look right here, right now — the new business that Google Cloud is winning, they are matching or beating their competitors here, and I think we're going to see that continue with the momentum that Google Cloud has. Visit Cloud Wars for more.

In today's Cloud Wars AI Minute, I explain how Microsoft's AI agent momentum could transform business applications at scale. Highlights 00:00 — So we're now hearing, according to Microsoft, that it has 40 million agents deployed now in the Microsoft ecosystem. Now compare that to the 30 million seats that it actually has sold for the M365 Copilot, and that really starts to show us that AI agent creation and things of this nature are starting to take off when we're starting to see more than one-to-one ratios here. 00:33 — So this is a really big situation for Microsoft. It's actually a really good signal that custom agents and agents that are being built are starting to get more value off the backside. Now we can't necessarily completely get to this level because what you'll see is a lot of these agents are probably really simple right now. 00:54 — But with some of the new applications coming out and the focus that Microsoft also came out and announced — that they are looking at going through and producing a Super App Copilot — and this was something that Satya Nadella just talked about in the news just last week. 01:13 — So when we think about this and we start thinking about how is it that Microsoft's going to start combining all of its different Copilot assets or its AI agent assets, it really opens up a door where we might start seeing a much bigger multiplier effect happening on the number of agents created. 01:32 — Due to the fact that they're going to make it not so confusing to be able to determine where to get started and be able to help you get this all down. So this is really exciting news, and it's really a good thing for why you should start looking and understanding these agents because they're really starting to take off as business applications themselves. Visit Cloud Wars for more.

In today's Cloud Wars Minute, I break down Microsoft's push to protect open-weight AI models and why the debate over openness could shape the future of the AI ecosystem. Highlights 00:09 — Microsoft is among more than 20 tech companies, including NVIDIA, Meta, and Palantir, that have issued an open letter urging U.S. lawmakers to slow down in placing restrictions on open-weight AI models. These are models that users can modify and run on their own infrastructure. 00:38 — The backlash from the companies comes in light of discussions within the U.S. government about potentially restricting access to Chinese open-weight AI models in the U.S. The administration's floated the idea of potential restrictions or sanctions involving Chinese open-weight models around concerns about copying other AI models, intellectual property theft, and national security. 01:06 — The tech companies that signed the letter argue that open-weight models strengthen competition, and with technology benefits broadly shared instead of being concentrated into a few hands, and that, in fact, relying entirely on closed models is not inherently safe because they can be breached, misused, or fail in ways that outsiders can't detect. 01:30 — They say that keeping AI advancements in a small circle of companies just compounds that risk. Sharing the letter on his personal X account, Microsoft CEO Satya Nadella said, "Open-weight models are essential to a healthy AI ecosystem. Together with others across our industry, we are outlining a path for open-weight models to strengthen American competitiveness and expand economic opportunity while protecting national security." 02:14 — This is yet another example of how the democratization of AI is being promoted by tech companies. In my opinion, the idea of collaboration and openness has made it much easier for the public to trust AI. Not only does this strengthen the position of the companies themselves, but it also means that more people will benefit safely and securely from the potential of AI technologies. Visit Cloud Wars for more.

In today's Cloud Wars Minute, I look at why Palantir's AI strategy is resonating with customers and disrupting the software industry's established order. Highlights 00:03 — Well, we had a fascinating earnings report and earnings call with Palantir recently. A couple of things happened. Its growth rate soared. It almost doubled its growth in Q2, up 93% to over $1.8 billion. 00:19 — But intriguingly, the story behind this growth now is one that CEO Alex Karp is doubling down on, and that is to cut directly against the grain of how traditionally the software industry has worked. He feels that there's too much power being consolidated among the tech vendors, particularly now the AI labs and the AI model companies. 00:55 — Now, is there a direct correlation between the 93% growth rate and this refreshing, new, different customer-oriented approach from Palantir? I think there is. Whether you think Karp's antagonism toward the entrenched order is overblown or not, you've got to look at the financial results. Palantir is outperforming every major tech vendor on Earth. 02:36 — What Karp is promising, he said, what Palantir is offering, is a new, better way that allows customers to keep control of that data, keep the benefits of that data, keep what he calls the alpha, and let them control their own outcomes instead of turning over their data to model companies. 04:36 — I just find myself throughout the call listening and watching Karp, who always wears a white T-shirt. He is just completely unabashed in not holding back and stating his opinions. I think we need more of that in this business, especially at these very critical times when businesses are betting their futures on what's going to happen here. Visit Cloud Wars for more.

In today's Cloud Wars Minute, I break down OpenAI's decision to make GPT-5.6 the preferred model for Microsoft 365 Copilot and why AI efficiency is becoming an increasingly important competitive advantage. Highlights 00:09 — It's fair to say that OpenAI has had a changeable relationship with Microsoft over the past few years. However, ties between the two companies have always remained strong. To that end, OpenAI has announced that GPT-5.6 has become the preferred model in Microsoft 365 Copilot, which includes Word, Excel, PowerPoint, Copilot Chat, Teams. 00:33 — Now, for context, this is OpenAI's latest flagship model, which the company claims delivers higher quality outputs and stronger performance per dollar spent, and this efficiency is increasingly important as more work shifts to AI models. 00:58 — For Excel, there'll be deeper data analysis and faster insights in PowerPoint. Copilot will be able to create more polished presentations with less manual effort. Meanwhile, Copilot Chat benefits from GPT-5.6's improved reasoning and productivity capabilities for everyday tasks. 01:28 — For me, though, the biggest benefit is this idea of improved efficiency — the notion of getting the most out of every token and gaining more value from the tools you're using. I think this will become a new battleground moving forward, not just for model developers who balance power and budget friendliness, but also for providers of AI tools like Microsoft, who need to show their customers that they're making the best choices in how these products are powered. Visit Cloud Wars for more.

In today's Cloud Wars Minute, I break down the reshuffled hyperscaler rankings and what AWS's comeback means for the AI economy. Highlights 00:03 — The third hyperscaler reported its numbers late last week. That was Amazon's AWS unit. Fantastic quarter for AWS. Best in four or five years. It had what I called an awesome Q2, and in doing so, we've seen a complete reshuffling of the growth standings among the hyperscalers. 01:18 — Microsoft, for the same period, its fiscal Q4 grew 27% to $59.3 billion, and Google Cloud was up an incredible 82% to almost $25 billion. We see Google Cloud and now AWS on a very nice continuous upswing, while Microsoft has leveled off. 03:05— Inside AWS, the backlog soared, up 154% to almost $500 billion. Andy Jassy said Amazon will spend in 2026 $220 billion on CapEx, almost all of which will go toward building the data centers necessary to fund this expansion in cloud and AI. 04:19 — The smallest backlog number of the four hyperscalers is AWS at $496 billion. Microsoft is around $675 billion, Google Cloud is $514 billion, and Oracle is about $636 billion. Together they represent well over $2 trillion in backlog. 05:12 — I think it's great seeing AWS back in high-growth mode. It makes the competition better, and it certainly is a great thing for customers, who now have choices of fantastic suppliers across the four hyperscalers: AWS, Google Cloud, Microsoft, and Oracle. Visit Cloud Wars for more.

In today's Cloud Wars Minute, I examine why SAP's biggest competitive challenge may soon come from OpenAI and Anthropic rather than traditional enterprise software rivals. Highlights 00:00 — SAP released its Q2 numbers last week, and a couple of interesting things happened there. First of all, strong Q2 cloud revenue growth, 24%. But even higher than that was its backlog growth, which went up 26%. CEO Christian Klein tied that specifically to the company's transformation, started about two years ago, to shift more and more of the sales effort from the direct channel to the indirect channel. 00:56 — It had resellers whose big concern a number of years ago was, "Well, what margin am I going to get? What discount do I get?" Today, the focus, through the efforts of Chief Partner Officer Karl Fahrbach and Klein, has shifted very, very much toward, "How do we get successful outcomes? How do we ensure these AI deployments happen smoothly, rapidly, and effectively at the customer site?" 01:29 — It's about $7.2 billion. Within that, the Cloud ERP Suite was up 27% to $6.4 billion, and the current cloud backlog, that 26% jump, pushed it to $26.3 billion. It said growth for full-year 2026 will be somewhere between 23% and 25%. I've penciled it in here as 24%, and that will come in right at about $30 billion. 02:28 — Klein said, "The growth for our indirect channel in Q2 again significantly outpaced our direct channel growth," and this reflects, he said, a successful go-to-market transformation. He has revised the company's leadership, its product portfolio, the impression the market has about ERP and what SAP Cloud ERP means, and how the whole notion at the highest level of the autonomous enterprise sinks in. 04:20 — Now there's enterprise applications, agents, AI, and data vendors, and this growth streak it's had in the mid-20s has been very impressive. So the biggest challenge SAP has going forward will come, in some form that's unclear right now, from OpenAI and Anthropic, and exactly how those they are going to parlay their early focus on models into the whole agentic AI movement in the agents and workflow space. Visit Cloud Wars for more.

In today's Cloud Wars Minute, I explore OpenAI's bold move into AI-powered consumer hardware and what it reveals about the future of trust in artificial intelligence.   Highlights 00:03 — OpenAI is adding yet another string to its bow as it becomes increasingly recognized as more than just its flagship ChatGPT product. Now, the company is reportedly developing its first consumer hardware device: a human-like AI companion that lives in the home. 00:21 — The report suggests that OpenAI is creating a portable, screenless AI smart speaker, not the AI phone that many people are expecting. As you might expect, the device will integrate with ChatGPT and handle questions, send messages, play media, and enable smart home controls. 00:38 — All pretty comparable to the existing smart speakers on the market, like Amazon's Echo. However, OpenAI's device is also expected to include cameras and sensors to get a better understanding of where it is and the context. While mechanical moving elements will give it more presence. Over time, the AI will learn about its owner and become increasingly personalized. 01:01 — Now, beyond the obvious—and by that I mean OpenAI's potential foray into consumer electronics and all the potential battles that might start between the leaders in that space—there's something really interesting about the ambition here and what it says about where we are today. Not long ago, the discussion was all about trust. 01:21 — Could we get consumers to trust AI enough to get the most from it? Looking at this investment, I think the answer is yes. This is an AI that not only observes and listens to its owner, but actively changes to adapt to their likes, dislikes, and personalities, passively and without waiting for requests. This is a big jump. Visit Cloud Wars for more.

In today's Cloud Wars Minute, I compare Microsoft's latest cloud results with Google Cloud's accelerating momentum.   Highlights 00:09 — Microsoft Cloud revenue was almost $60 billion for the quarter, up 27%. The RPO, as I said, was up 84%. It's now the biggest RPO total, slightly ahead of Oracle. Microsoft Cloud: $678 billion for that. It said that Azure revenue was up 43% and that its revenue for the fiscal year ended June 30 exceeded $100 billion for Azure. 01:46 — So if we look at the last five quarters from Microsoft, the growth rate: 27%. Starting in Q2, the present, going back five quarters: 27%, 29%, 26%, 26%, 27%. So relatively flat over that period of time. The 29% jumped up a little, but the others, all 27s and 26s. 02:14 — Over those same five quarters, Google Cloud's growth rate has absolutely soared, and the trajectory, the arc of its growth, representing customer demand in the marketplace, has been remarkable. So again, starting from the just-finished quarter and going backward in time: 82%, 63%, 48%, 34%, and 32% growth rates. 02:49 — What we're talking about here is the arc of the growth. Google Cloud is getting a much bigger share of what's happening here. It's winning more business. It's taking deals away from Microsoft, AWS, and perhaps Oracle as well, and they're winning a lot of new business. 04:40 — So we'll get AWS numbers later today. I'll be following up next week with some insights into that and give the head-to-head comparison. It is an extraordinary time, but the ultimate truth is coming from the customers and where they are deciding to make their investments as they move into the AI Economy. Visit Cloud Wars for more.

In today's Cloud Wars Minute, I look at Microsoft's strategy for balancing AI innovation with local governance, culture, and national control. Highlights 00:04 — I want to start today with a quote from Natasha Crampton, Microsoft's Chief Responsible AI Officer. "AI sovereignty doesn't mean doing it alone." This quote stands out from an interview she recently gave on the sidelines of the UN AI for Good Summit in Geneva. 00:48 — Ultimately, Crampton, echoing Microsoft's stance, stated that nations should leverage the best global AI technologies while ensuring they're adapted to local laws, languages, cultures, and values. Crampton explains that AI sovereignty is about control, not isolation. It's about cross-border coordination whilst making sure that countries retain control over how AI is deployed, governed, and used. 01:18 — One of the main problems that Crampton highlights regarding AI sovereignty is how AI is widening the gap between developed and developing economies. She says we cannot let the digital divide become an even greater AI divide. She emphasized the importance of making these technologies more accessible to the Global South. 01:43 — She says that AI sovereignty is about making sure that local impact, local cultures, values, and norms are prioritized within AI systems while taking advantage of global technology. AI becomes far more valuable when it understands local languages and cultures rather than simply translating from English. 02:15 — Overall, Crampton laid out a clear and, I'd say, pretty unique vision for what AI sovereignty can be. It's also a clever position for Microsoft to take, saying to governments that choosing Microsoft doesn't mean giving up sovereignty because they can control the data, the governance, and the policies on Microsoft's global platforms. Visit Cloud Wars for more.

In today's Cloud Wars Minute, I examine why Google Cloud's explosive growth is redefining the competitive landscape ahead of Microsoft and AWS earnings. Highlights 00:03 —We have earnings results coming up later this week from both Microsoft and AWS. Microsoft on July 29, and AWS on July 30. So, that'll give us some nice comparisons to the stunning Q2 that Google Cloud reported last week. Google Cloud will be outgrowing AWS by somewhere between two and a half times at the high end, and at least two times on the low end. 01:02 — Over the last several quarters, Jassy has alluded to Google Cloud, not by name on earnings calls, but he said, "We've got some companies throwing up these fancy high growth rates." What we see with these growth rates is the customers expressing their vote. They are the ultimate arbiters in this decision about who's the hottest company. That's expressed in growth rates. 02:23 — I'm comparing Q2 here for Google Cloud versus Q1 for AWS because, right now, the Q2 numbers aren't out yet. AWS grew at 28%. Google Cloud grew 82%. Say AWS reports this massive acceleration to 40%. They would still be outgrown by Google Cloud by 2X. My guess is AWS's growth rate will come in somewhere around 30% or 31%. 03:22 — It is becoming a little tiresome for these bigger companies to say, "We're bigger than them. Of course, they have a higher growth rate." The customers are voting here. These growth rate disparities are so important because they tell us how the different vendors are doing in the marketplace through the eyes and wallets of customers. 04:01 — In the Cloud Wars, the customers are always, always the big winners. Microsoft and AWS are growing their cloud businesses in the range of 30%, which is astonishing. But Google Cloud posted 82% revenue growth and backlog growth of almost 400% to over $500 billion. By the numbers, Google Cloud is the king of the hill right now. Visit Cloud Wars for more.

In today's Cloud Wars Minute, I look at why playing to win — not playing it safe — is becoming the defining strategy for AI and cloud leaders. Highlights 00:01 — Last week, we talked about Google Cloud's extraordinary Q2, with revenue up 82% to almost $25 billion, backlog up almost 400% to $514 billion. I wanted to talk today a little bit about a challenge that Google Cloud and the other hyperscalers are facing, because this extraordinary growth requires very aggressive investments in CapEx to build out data center capacity. 00:58 — Will these companies continue to have the courage to play to win, as opposed to trying to appease rattled investors? Right after Alphabet reported these numbers, Alphabet also had to say that its CapEx budget for 2026 is going to go up slightly to about $200 billion, while Q2 cash flow was negative $5.9 billion. 01:49 — But it's not a long-term trend here. The market reaction was they hammered Alphabet stock, and its market cap went down $250 billion after Google Cloud reported this. My point is, you've got to keep a clear head in these crazy sorts of times, and I think Alphabet is doing exactly that. Sundar Pichai cited immense opportunities during the Q2 earnings call and talked about the complete AI stack. 02:56 — They believe these investments they're making now are going to pay off with significantly more data center capacity next year. In the short term, Google Cloud is going to tap into some third-party data center capacity, Pichai said, as one of the ways to take care of customers. They're willing to trade that very short-term pain for enormous contracts down the line. 04:09 — It's a wild time here, but definitely, as I've said many times, this is the greatest growth market the world has ever known. These big hyperscaler companies are now faced with challenges that no company has ever had to face before. I applaud the Alphabet leadership for playing to win rather than playing not to lose. That's just not going to cut it in the Cloud Wars. Visit Cloud Wars for more.

In today's Cloud Wars Minute, I explain how Salesforce's latest MCP announcement advances Marc Benioff's vision for AI-first enterprise collaboration. Highlights 00:03 — Salesforce has announced the introduction of new MCP servers that connect Slack to Salesforce CRM, Tableau, Data 360, and third-party AI tools. Now, these new servers have enhanced Slackbot, which is Slack's personal AI agent, enabling it to serve as a conversational interface for tasks across the Salesforce ecosystem. 00:29 — The headline for the press release about this announcement really summarizes it very well: "Slackbot can now do anything Salesforce can — just ask." Salesforce users can now view and update Salesforce records, run automations, access custom data without leaving Slack, and just using natural language. Users can query Tableau dashboards and analytics. 00:55 — Data 360 integration now enables Slackbot to access customer data for better responses and context-aware responses. Slackbot can now orchestrate work across multiple AI agents and enterprise apps, including partners like Anthropic, Atlassian, DocuSign, and Zapier. And the whole thing can be centrally managed by admins with built-in authentication and security. 01:22 — These Salesforce-hosted MCP servers are now generally available for all Enterprise Edition organizations and above. So what's the vision here? Well, Kris Billmaier, EVP and GM of Sales Cloud, explained, "Salesforce Sales Cloud in Slack is the future of how revenue teams work," he said. 01:55 — "AI is changing what it means to sell, and putting Salesforce intelligence and data inside Slack, where sellers already live, means teams stop chasing context and start driving growth. That shift is happening now, and we're right at the center of it." Ultimately, Salesforce is now positioning Slack as the primary workspace for AI-powered collaboration. Visit Cloud Wars for more.

In today's Cloud Wars Minute, I show why Google Cloud is setting the pace in the AI economy despite Microsoft's and AWS's larger scale. Highlights 00:03 — Well, we thought we had seen some big numbers in the Cloud Wars over the last few quarters, but Google Cloud for Q2 absolutely blew the numbers away. Astonishing: revenue up 82% to almost $25 billion, and its backlog up 390% to $514 billion. 01:39 — From Q1 to Q2, Google Cloud's revenue jumped $4.8 billion. That's far larger, not only than what Google Cloud has done quarter to quarter, but Microsoft and AWS. I believe, looking pretty closely over a long period of time, for any of those companies to have a $3 billion increase quarter to quarter has been remarkable. 02:16 — I've got an article offering some highlights from this, and also side-by-side-by-side comparisons of the growth that Google Cloud, Microsoft Cloud, and AWS have each posted over the past five quarters. What makes Google Cloud stand out is the arc of its acceleration. It is much, much steeper, much higher. 03:18 — Q4, Google Cloud really broke away from the pack: 48% growth in Q4, 63% growth in Q1, and here now for Q2, 82%. Just absolutely remarkable, and I think we see that among the hyperscalers, and perhaps others as well, Google Cloud is clearly the AI leader. 04:32 — While Microsoft Cloud and AWS have bigger revenue numbers, Google Cloud is the one setting the pace, winning more customers, winning new business, and setting the pace with technology, go-to-market innovation, and the confidence, in large part delivered by the remarkable security business it's built, that it can handle everything that customers need as they move into the AI economy. Visit Cloud Wars for more.

In today's Cloud Wars Minute, I look at how Microsoft is helping schools move from AI experimentation to effective deployment. Highlights 00:08 — There isn't a sector that AI hasn't impacted, and with the proliferation of these technologies, it's important to examine individual sectors and analyze the effect of AI on them, both positive and negative. 00:23 — To understand where things are working and where they aren't. And that's what Microsoft has done with its 2026 "AI in Education" report. I want to share some of the key findings from that report with you today. Ultimately, AI has become mainstream in education, with 92% of students and education leaders, and 88% of educators, having used AI for school-related purposes. 00:60 — Adoption is increasing. In fact, 58% of education leaders report that their institutions are already implementing or scaling AI initiatives. According to the report, the biggest gap identified is the need for training, with both educators and students requesting more structured support. In fact, 66% of educators want AI training on a monthly or quarterly basis. 01:15 — While 52% of students are also seeking regular AI training. The priority highlighted in the report is responsible AI use, with 41% of students and 42% of educators citing academic integrity as a leading concern. Now, in response, Microsoft has announced new AI capabilities across Microsoft 365 Education and its broad education platform. 01:40 — These include AI-assisted unit planning for teachers, student AI guidelines, learning groups, enhanced classroom experiences in the Learning Zone, Copilot Notebooks, and a Study and Learn agent in Copilot Chat. The overall message from this research is that the focus in education is shifting from access to AI to its responsible deployment, with improvements needed in training, governance, and classroom-ready tools. Visit Cloud Wars for more.

In today's Cloud Wars Minute, I examine why Google Cloud and Palantir have become the fastest-growing companies in enterprise AI. Highlights 00:01 — Now that we are more than halfway through the year, we've got Q2 earnings season coming up, and a couple that I'm looking for in particular are Google Cloud and Palantir because their growth rates have been so much above the norm. I think what we see in those growth rates and in the numbers behind those is a reflection of what customers really want from AI and the cloud here in the AI revolution. 00:52 — Let's look at numbers for Google Cloud, the number one company on the Cloud Wars Top 10. Palantir is number five. For Google Cloud, in the quarter ended a few months ago, March 31, its growth rate was 63%. Its revenue was $20 billion. Q4: 48%, $17.7 billion. Going back to Q3: 34%, Q2: 32%, and Q1: 28%. So we see, for the last five quarters, Google Cloud has soared over the last couple of quarters 01:57 — Now let's look at Palantir with those same five quarters, going back to Q1 of 2025, and up through Q1 of this year. So, most recently, 85% growth rate with over $1.6 billion in revenue, 70% before that, 63% before that, 48%, 39%. So in both cases, we see the company, even as its revenue base gets bigger, growing much, much faster moving forward. 03:22 — Palantir is 24 years old. This is not a startup company, although it's just sort of burst onto the scene. I wonder if, in some ways, Palantir's technology was out ahead of where the market was. But now that the AI boom has swept the world, Palantir's technologies are now suitable for  companies of any size to help take what they have and use that as a foundation to build into the future. 04:37 — Innovation in going to market, as well as in technology, means  some new approaches to things. I think particularly Google Cloud here has been an extraordinary example of this. And I refer in this article to their recent disclosure that while OpenAI and Anthropic, AWS, and Microsoft are all launching deployment units to pull off these big AI projects, Google Cloud is relying 100% on its ecosystem. 05:11 — I'll be eager to see how these companies do in Q2, and we'll follow up with those and the other Cloud Wars Top 10 companies on how they've done in calendar Q2. But I really take my hat off to Google Cloud and Palantir because, in this very intense time, with an enormous market and everybody going after it, their growth rates are soaring. Visit Cloud Wars for more.

In today's Cloud Wars Minute, I preview the coming wave of Q2 earnings while highlighting the extraordinary growth reshaping cloud computing. Highlights 00:03 — We're on the verge of having a lot of calendar Q2 financial results released, so just in advance of that, I wanted to offer a snapshot of where things stand now regarding the world's hottest cloud and AI vendors. Right now, we've got Palantir in the number one spot, Google Cloud number two, Oracle number three. 00:42 — I've also got a chart in there showing backlog, or RPO, which is future booked business that's fully contracted, fully committed, among the four hyperscalers that now totals over $2 trillion. But in the here and now, here's where it stands for the Cloud Wars Top 10 companies. Palantir is in the number one spot for Q1. 01:56 — We've got Microsoft with an enormous performance here: 29% growth and $54.5 billion in quarterly cloud revenue. AWS had a very strong quarter: 28% growth and $37.6 billion in revenue. Salesforce is in the number nine spot with 13% growth, while OpenAI remains an estimate because it is not yet publicly traded. 03:05 — You know, you see some of these numbers, and as I referred to a moment ago about the backlog numbers, which are truly just mind-bending, we become immune to being amazed by the size and the volume here. I do not throw around the phrase "the greatest growth market the world has ever known" lightly. 03:55 — The former applications companies are now racing to become agentic companies and data companies. Huge change and transformation within the Cloud Wars Top 10 is helping customers participate in, succeed in, and potentially thrive in the AI economy. I don't expect any massive changes in this lineup, but the growth numbers will be very interesting over the next few weeks. Visit Cloud Wars for more.

In this episode of the AI Agent & Copilot Podcast, John Siefert, Founder and CEO of Cloud Wars, is joined by Cedric Wells, IT leader and former Senior Manager of Infrastructure and Operations at Gorilla Glue. Together, they explore how AI is reshaping IT leadership, software development, governance, and enterprise transformation. Wells shares why continuous learning, balancing strategic vision with execution, and maintaining strong security and data governance will define successful organizations in the AI Era. Their conversation also reflects many of the leadership themes that attendees explored at the 2026 AI Agent & Copilot Summit NA. Key Takeaways Growth mindset is becoming the most valuable IT skill. Wells believes technical expertise alone is no longer enough. The speed of AI innovation requires professionals at every level to continuously refresh their knowledge and remain adaptable. He explains that technologies evolve so rapidly that learning has become a permanent responsibility rather than a periodic exercise. As Wells notes, "Having a mindset that's really around learning as much as I can as things are changing" is essential. He also reminds listeners, "It's changing so fast," making curiosity and adaptability foundational qualities for future IT leaders. AI enhances leadership — but doesn't replace technical understanding. Wells argues that AI is helping close the gap between technical specialists and business leaders, allowing executives to understand complex technologies more quickly. However, leaders still need enough technical context to ask intelligent questions and make informed decisions. As he explains, "Being able to really as a leader leverage AI as much as possible" creates significant advantages. He also emphasizes that "bridging that gap with your leadership skills and leveraging AI on the technical side" will define successful IT leadership moving forward. Governance and security are becoming even more important. Throughout the conversation, Wells repeatedly emphasizes that AI initiatives require close collaboration between infrastructure, information security, governance, and data teams. Without proper oversight, organizations risk exposing sensitive information, creating compliance issues, or building unreliable AI systems. Wells reminds listeners that "It's very important to make sure that those two departments are aligned" and warns that "Employees are doing it whether or not you like it," making proactive governance and secure enablement far more effective than restrictive policies alone. Visit Cloud Wars for more.

In today's Cloud Wars Minute, I look at why Salesforce's new Help Agent represents a major shift toward performance-based enterprise AI. Highlights 00:03 — Salesforce is launching the Agentforce Help Agent, a pre-built AI customer service agent that customers can deploy in a matter of minutes. It's designed as an alternative to custom-built agents, connecting to existing Salesforce knowledge articles and support content, which means only minimal configuration is required. 00:23 — I'm going to walk you through the features of this new agent before getting to the part I'm most excited about, and I think you will be too. The agent was built on the Agentforce platform and uses the Salesforce Data Cloud and CRM data for context, incorporating the responsible use and governance policies there too. 00:43 — It delivers enterprise-grade customer support by answering customer questions, troubleshooting issues, escalating complex cases to a human support agent. Salesforce validated the agent internally before the launch, and the company has reported that its own Help Agent handled 4.3 million customer conversations and resolved around 70% of inquiries autonomously, really showcasing its effectiveness. 01:16 — Here's the kicker: the new Help Agent operates on a resolution-based pricing model. This means that customers are only charged when the agent successfully resolves a customer's issue. There's no charge if the conversation is handed off to a human agent before resolution, and this approach is quite groundbreaking. In many ways, Salesforce is testing a new pricing model for enterprise AI. 01:50 — From an AI in the workplace perspective, this agent operates on a performance-based pricing scenario, similar to how a gig worker is paid for successful tasks completed, right? So, Salesforce is not the first company to use outcome-based pricing for software, but bringing it to Agentforce and pushing it further into enterprise AI is remarkable stuff and a great step forward from Salesforce. Visit Cloud Wars for more.

In today's Cloud Wars Minute, I explain why hyperscalers are rewriting the rules of deal-making to build the next generation of AI infrastructure. Highlights 00:01 — We are seeing the beginnings here of an incredible round of innovation, not just in technology, but in deal-making, partnerships, alliances, and financing, all by the hyperscalers trying to meet this insatiable AI demand. We're seeing these companies undertake some very innovative, bold, distinctive new strategies to build the capability and capacity to get these AI data centers built out to meet this insatiable demand. 00:49 — Google Cloud did a joint venture with Blackstone, in which Blackstone invested $5 billion into the joint venture. We have seen Amazon issue a series of debt and bond offerings totaling over $100 billion. AWS has said that in calendar year 2026 it will spend $200 billion on CapEx, most of which is going into AI data centers. Oracle announced $50 billion in debt and equity financing. 01:57 — This funding, this raising of funds to build out the data centers, is because there is, among these hyperscalers, over $2 trillion in committed contracted business. While Oracle right now is the smallest by revenue of the hyperscalers, it has the largest backlog, and in order to meet that, it has to spend a lot of money to build the capacity. 02:46 — Microsoft is using proceeds from its brilliant early relationship with OpenAI to help secure some of the funding. Under a newly restructured agreement between the two companies, Microsoft now will receive 20% of OpenAI revenues for the next few years. Plus, Microsoft has a huge ownership stake in OpenAI. 04:17 — Remarkable things are going on here as the technology buildout by all these companies has helped create this incredible demand. What we're seeing now is extraordinary efforts by the hyperscalers to combine with other companies, move into different industries, and do everything possible — at staggering expense — to meet this insatiable customer demand for AI. Visit Cloud Wars for more.

In today's Cloud Wars Minute, I look at how reasoning-focused AI will strengthen SAP Joule agents with enterprise-grade security and governance. Highlights 00:03 — SAP has partnered with Giotto.ai to explore the integration of Giotto.ai's AI reasoning capabilities into SAP Joule agents. Now, for some background, Giotto.ai is a Swiss AI company that has developed compact, reasoning-focused AI models designed for deployment in secure and controlled enterprise environments. 00:25 — Quick recap here: reasoning-focused AI models are designed not just to generate answers, but to really work through problems in a more structured and logical way before giving a response. The partnership will initially focus on pilot projects aimed at enhancing SAP Joule agents in enterprise scenarios that require structured reasoning, reliability, and integration with enterprise data. 00:50 — The collaboration will also serve as an opportunity for Giotto.ai to validate its technology in demanding real-world business environments. According to CEO Aldo Podestà, the partnership will demonstrate the practical value of the company's reasoning-focused models in an enterprise setting. 01:10 — For SAP, the collaboration provides an opportunity to explore how reasoning-focused AI can enhance its enterprise agents, particularly in use cases that require dependable decision support and close integration with the business data processes available there. 01:29 — For SAP customers, the partnership could result in AI agents that provide more reliable recommendations, better decision support, and greater automation of more complex business processes, critically, and this is the USP of Giotto .ai critically, while maintaining enterprise-grade security and governance. Visit Cloud Wars for more.

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.   Visit Cloud Wars for more.

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. Visit Cloud Wars for more.

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. Visit Cloud Wars for more.

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." Visit Cloud Wars for more.

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. Visit Cloud Wars for more.

In today's Cloud Wars Minute, I explain why the next phase of agentic AI is all about governance, security, and business processes. Highlights 00:03 — Salesforce has expanded its partnership with Databricks to help organizations better connect enterprise data with business outcomes in the era of agentic AI. At its core, the expanded partnership is about recognizing that as AI agents take on a larger role across the enterprise, they need access to complete, connected data that's paired with business context, security controls, and enterprise processes. 00:51 — Access to data alone really is not enough for AI agents to deliver meaningful business value. "Customers consistently tell us they want AI agents to become a larger part of how work gets done across the enterprise," said Andy Kofoid, President of Global Field Operations at Databricks. "To make this a reality, they need access to trusted data, business contexts, and governance controls wherever that information lives." 01:32 — "Together, Salesforce and Databricks are helping customers connect governed data and business contexts across platforms, giving humans and agents the shared foundation they need to search, reason, and act with confidence." 01:46— I think this partnership is, yet again, part of a pattern that's emerging here. It's representing a broader shift that's taking place across the AI industry as organizations move beyond experimentation and toward large-scale deployment of AI agents. 02:00 — As this is happening, success really depends less on the models and more on the ability to unite these agentic capabilities with data governance, security, and business processes. Salesforce and Databricks are betting that enterprises need all of those elements working together cohesively if agentic AI is to deliver on the promises it has made. Visit Cloud Wars for more.