Cloud Wars Live with Bob Evans

In today's Cloud Wars Minute, I dive into Oracle's remarkable Q4 earnings report, where the company delivered results that exceeded expectations across the board. Highlights 00:02 — We had a monster Q4 report from Oracle yesterday, absolutely crushed their numbers for Q4, led by an astonishing leap in their backlog or remaining performance obligation (RPO) of $638 billion, That's an increase of 363%. And no, those are not misprints. 00:29 — RPO represents business that's fully contracted, not yet recognized as revenue, so it's pipeline backlog, as opposed to revenue, which has already been posted for what has happened in the past. So I wanted to quickly pop out a couple highlights here that go along with that. Just remarkable RPO growth, cloud revenue overall was up 47% to 9.9 billion. 00:56 — Within that, cloud applications grew 10% to 4.1 billion, and the big star of the company, now their cloud infrastructure business was up 93% to $5.8 billion. One other number that Oracle put in its Q4 press release, that is pretty darn impressive, their multi-cloud AI database business, they said, was up 404% and they said that now makes this the fastest growing product in the company's history. 02:11 — Looking ahead a little bit, Oracle guided in Q1, they said their cloud business will grow between 57 and 63% so caught about 60% and that extends a long running streak of fast growing numbers there for Oracle's cloud revenue or cloud business. 02:33 — Oracle also said in its Q4 press release that it will be doing no more borrowing to fund its data center expansion throughout for calendar 2026, certainly possible for next year, but for this calendar year, no more borrowing. I think most people would yawn or overlook that fact. There have been a lot of folks on Wall Street, though as I've mentioned, that this has caused them fainting spells and pearl clutching, because they, nobody's done this before. 03:44 — Now, I don't know, I don't think there's a lot of companies that have run into that challenge before. It's a delightful challenge to have, but it is not something that you know a lot of companies can just, you know, reach into the petty cash box and say, you know, here's $100 billion $200 billion dollars to fund it. Visit Cloud Wars for more.

In today's Cloud Wars Minute, I analyze how Sana is helping Workday transform from a system of record into a system of action. Highlights 0:00 — Workday has announced two new agents: Sana for IT Service Management, or ITSM, and Sana Travel Agent. To recap, Workday acquired Sana at the end of 2025, and since then, the technology has evolved into Workday's employee AI layer, what the company describes as its "front door for work." 0:42 — Sana for ITSM automates workflows for tasks like employee onboarding, off-boarding, access changes, and standard IT requests, while the Sana Travel Agent helps employees plan work trips, book travel, and manage expenses. Both agents are built directly on Workday, meaning they have the same security and governance protocols by default, and tap into the bespoke contextual company data and policy information contained within the platform. 00:57 — Cloud Wars founder Bob Evans commented on the development in the official Workday press release: "Extending agents into adjacent workflows like onboarding, travel, and expenses, where Workday already has the people and finance data and policies, is not only practical but also a transformational way to help HR and finance leaders meet and exceed their objectives." 01:25 — Workday's acquisition of Sana was a pivotal moment in the company's recent history and accelerated its push in the enterprise AI era. The deal signaled a strategic evolution beyond Workday's traditional role as a system of record for HR and finance processes. 01:44 — At the same time, that deep system of record foundation is exactly what makes Sana's autonomous AI agents such a strong fit, because the agents can operate with rich context, permissions, policy, and workflow data already embedded within the platform.     Visit Cloud Wars for more.

In today's Cloud Wars Minute, I analyze how a trillion dollars in cloud backlog is driving innovation beyond technology and into corporate finance. Highlights 00:03 — In the Cloud Wars, all sorts of crazy things are going on with the technology, what customers are doing with it, but also in how this whole remarkable time is being funded. I want to talk a little bit today about how Google Cloud and Oracle are choosing to fund this unprecedented market demand and why new possibilities require new ways of doing things. 01:25 — In Oracle's most recent quarter, it reported that its RPO, or Remaining Performance Obligation, similar to backlog, is over $550 billion. For Google Cloud, it had an amazing jump as well in its most recent quarter, ended March 31, $462 billion in backlog, almost double what it had been a year before that. So there's amazing demand, these two companies totaling a trillion dollars. 02:09 — Six months ago, Oracle reached out and said, “No, no, we're going to go to some outside funding, some borrowing, to do that.” But the market reacted with a panic. “Oh my God, nobody's ever done this.” And, you know, "What if they can't pay it back?” So there was a lot of skepticism about Oracle's plan six months ago. 02:58 — Now, a week ago, we see Alphabet step up and say, “Hey, we're going to do some equity financing. We're going to take $10 billion from Warren Buffett and some other places. We need this money. We think it's the best way to pursue funding our own data center expansions, our own CapEx needs, which will be somewhere between $185 and $190 billion.” Oracle's will probably be around $75 billion. 04:37 — Oracle and Google Cloud have risen to the top of the Cloud Wars Top 10 because they brought innovation at levels in technology and go-to-market, how they think about customers, deployment models, and so forth, that have really set the new standard for what's happening in the AI cloud business now. Seeking outside funding to meet this demand shows another way to do it. Visit Cloud Wars for more.

In this special report, John Siefert, CEO, Dynamic Communities and Cloud Wars, speaks with Robbie Morrison about Velocio's acquisition of Domain Six and what the move means for customers, partners, and the broader Microsoft ecosystem. Morrison explains how the acquisition expands Velocio's enterprise capabilities, vertical-industry expertise, and delivery capacity while strengthening its ability to help organizations modernize around cloud, data, and AI. Velocio Expands Expertise The Big Themes: Domain Six Expands Velocio's Reach: Velocio's acquisition of Domain Six represents more than a simple expansion of headcount. Robbie Morrison describes the acquisition as a strategic move that adds highly skilled consulting talent, enterprise delivery capabilities, and valuable intellectual property in specialized vertical markets. Domain Six brings expertise in areas such as rental businesses and professional services, allowing Velocio to broaden its market reach while deepening its industry-specific knowledge. Consulting is fundamentally a people-centric business, making the addition of experienced professionals especially valuable. Customers Gain Access to Broader Expertise: One of the biggest benefits of the acquisition is the expanded access customers receive to specialized talent and services. Morrison notes that existing Velocio customers will gain access to Domain Six's industry expertise, while Domain Six customers will benefit from Velocio's larger global team and deeper Microsoft platform knowledge. The combined organization can now offer expertise spanning Azure, Dynamics, Microsoft 365, Fabric, data platforms, and business applications. Governance Has Become a Competitive Advantage: Data governance is no longer just a security requirement. Morrison explains that governance, access controls, documentation, and process discipline have become business enablers. Proper governance ensures that the right employees can access the right information at the right time, allowing organizations to move faster and make better decisions. As AI systems increasingly depend on organizational data, governance frameworks become essential for both compliance and performance. The Big Quote: “Everything that we do is people-centric. We're a consulting business at heart, and a consulting business is built on the knowledge and the abilities of the people you bring in, so bringing in that great team at Domain Six was key." More from Velocio and Robbie Morrison: Connect with Robbie on LinkedIn, read the press release about the Domain 6 acquisition,  or check out the Velocio website. Visit Cloud Wars for more.

In today's Cloud Wars Minute, I look at how ServiceNow's AI strategy, open platform, and workflow data fabric are driving its next phase of growth. Highlights 00:02 — ServiceNow is off to a hot start, not only with its quarterly results, but also in how CEO Bill McDermott is framing where the company is right now and, in terms of that, how that new position, which he says is, "We're 100% AI native," is going to allow them to pursue five what he called hyper-growth markets for quite some time. 01:06 — Who is AI native, and who is just sort of glossing over, applying some AI lipstick to their traditional solutions and technologies? The term that ServiceNow uses to refer to that latter category is AI sidecars, where they say that's just a little AI glomming onto traditional technology, and that's becoming less appealing to customers. 02:34 — Among the highlights he pointed out to support the strength of the company, he said, "We've got a $28 billion RPO, remaining performance obligation, that grew 23.5% in Q1." In addition to that, he said, "We've got the most open enterprise platform." 03:14 — First, its core ITSM business. He said with the complexity that's going on in enterprises and the more reliance on data that's going to be taking place here in the AI era, we're going to see a 50x —not 50%, 50x — boom in the number of tickets that are being sent through for IT support. 04:12 — He talked about what's going on there with Moveworks and the changes that ServiceNow has made to that, and how that's going to simplify things and help bring down the anxiety some people have about AI. And finally, he said, "Our workflow data fabric," which helps pull all the data together, is so essential for what's going on now with AI. Visit Cloud Wars for more.

In today's Cloud Wars Minute, I discuss how Workday's Extend platform is helping developers build faster while maintaining governance and trust. Highlights 00:03 — Earlier this week, Workday held its DevCon conference in Las Vegas. It was the biggest DevCon that Workday has ever had. They had 8,000 attendees, and of course, these days, the star of the show was new agentic capabilities that, in this case, Workday is pumping into its Workday Extend platform. 00:53 — This Developer Agent is being added to a number of new capabilities within the Extend platform, and I listened to this whole roundtable discussion, and a number of things jumped out. I just want to share some of the reactions with you because they give a sense of what's going on here among developers in the early stages of the AI revolution. 01:58 — One person called it a real game-changer, this Developer Agent, and she said, "What used to take me days, I can now do in about one hour." Another person said that, with Workday ensuring that all the guardrails around security, trust, and governance are there, "I can build now without losing any sleep every night." 03:08 — This person said actually hiring for software engineers here in the AI era is way up. I think what came across in this roundtable that Workday held at DevCon was the optimism that these folks showed. We're not only surviving the changes brought by AI, we're going to have chances to do more than we ever have before. 04:12 — Here they see that now the work, the time, the effort, the energy, the brain muscle that they are putting into their work is going to result in better output, more impact on the business, more capability, because the technology through these agents is both taking care of lower-level work and ensuring governance, trust, and security are wired in. Check out this press release outlining the major introductions at DevCon. Visit Cloud Wars for more.

In this episode of the AI Agent & Copilot Podcast, Giuseppe Ianni, podcast host and industry interviewer, is joined for a second time by Nandita Puri, PhD Researcher at Georgia Tech working at the intersection of bioinformatics and biochemistry. The conversation explores how AI is transforming drug discovery, accelerating hypothesis generation, reducing experimental costs, improving success rates, enabling rare disease research, and paving the way for virtual cell simulation. Key Takeaways AI Is Creating a New Drug Discovery Workflow: Puri describes a major transition from traditional laboratory-first research toward a hybrid approach combining computational and experimental science. Researchers can now use AI, machine learning, and pattern recognition to analyze massive biological datasets before conducting expensive laboratory work. According to Puri, "I see a healthy combination of 50% dry lab and wet-lab validation becoming the emerging standard." This shift allows scientists to move beyond manual analysis and leverage computational intelligence to generate stronger hypotheses, identify promising targets faster, and focus laboratory resources on the most promising opportunities. Higher Success Rates Mean Lower Costs and Less Waste: One of the most immediate benefits of AI in drug discovery is improved experimental efficiency. Puri notes that individual experiments can cost "$10,000-$12,000" and historically have carried significant failure risk. By consolidating fragmented datasets and identifying meaningful biological signals, AI helps researchers prioritize stronger hypotheses before entering the laboratory. Puri explained that some AI-assisted binder-development efforts achieved "40% 50% of success rate," compared with previous rates of "10% 5%." These improvements reduce wasted resources, shorten research timelines, and allow scientific teams to evaluate more potential treatments with the same budget. AI Is Unlocking Opportunities for Rare Disease Research: Rare diseases have historically faced funding and development challenges due to limited patient populations and expensive clinical validation requirements. Puri explains that AI is helping overcome these barriers by generating synthetic datasets, identifying hidden biological relationships, and revealing common signaling pathways between diseases. She notes that "AI is really, really helping rare disease industry to go forward." Visit Cloud Wars for more.

In today's Cloud Wars Minute, I explore why OpenAI could soon rank among the world's biggest enterprise software companies. Highlights 00:03 — Early this year, OpenAI joined the Cloud Wars Top 10 in the number 10 spot. Because of the impact OpenAI has had, moving from the ChatGPT explosion three and a half years ago up to now, and their move very aggressively into the enterprise, they are a player of a major type with huge potential, both in what they're doing themselves and the partnerships they have. 01:07 — The biggest one turns out to be that right now the enterprise part of the OpenAI business is very soon going to be the biggest, and I think it is currently the fastest-growing part of OpenAI. Denise Dresser [Chief Revenue Officer, OpenAI] said that enterprise revenue at OpenAI is now 40% of total revenue, and by the end of this year it'll be 50%. 02:05 — OpenAI Enterprise has two million enterprise customers right now. A year ago, she said it was one million. They're not all giant companies and they're not all paying OpenAI a lot of money, but what they're doing is seeding the way for future opportunities and growth. OpenAI hinted that they're on about a $25 billion run rate. 03:04 — If OpenAI grows 60% this year, making that $25 billion run rate $40 billion, then 50% of that going to enterprise would be a $20 billion business at a fairly conservative guess. It could be closer to $25 billion, making them a bigger, faster-growing enterprise AI software player than Workday, Palantir, and ServiceNow. 04:33 — Customers see that there's a lot of potential in the technology that OpenAI has, but they also want to know if OpenAI has the capability to support it. Dresser said that by the end of this year, OpenAI plans to have 300,000 trained consultants for the OpenAI Enterprise business. Competition is great. It's going to make everybody better. Visit Cloud Wars for more.

In this Cloud Wars conversation, Bob Evans sits down with Bonnie Tinder, Founder and CEO of Raven Intelligence, to discuss how AI is reshaping the systems-integrator (SI) market. Their discussion explores how AI-powered migration agents, deployment assistants, and new implementation models are dramatically reducing project timelines, staffing requirements, and costs. Bonnie explains why traditional implementation approaches are giving way to leaner, expertise-driven engagements centered on outcomes rather than labor hours. Episode 60 | Outcomes Beat Implementations The Big Themes: AI Compresses Implementation Costs: Tinder notes that organizations often spend 10 to 11 times the cost of software licenses on implementation services. AI is beginning to challenge that model by automating some of the most labor-intensive aspects of projects, particularly data migration and system conversion work. Migration agents and deployment assistants can significantly reduce the need for large teams of junior consultants performing repetitive tasks. As implementation timelines shrink and staffing requirements decline, customers will increasingly expect lower costs and faster results. Vendors are also pushing for these efficiencies because lengthy implementations delay customer value realization. The result is mounting pressure across the SI industry to adopt AI-enabled delivery models that are leaner, faster, and more outcome-focused. Outcome-Based Thinking Is Accelerating: Throughout the discussion, Bob and Bonnie discuss the growing demand for measurable business outcomes. Customers are increasingly unwilling to tolerate expensive implementations that fail to deliver value. This pressure is encouraging software vendors and SI firms to move toward outcome-oriented engagements and pricing models. Instead of charging primarily for labor and project duration, firms must demonstrate tangible improvements in efficiency, productivity, or business performance. Boutique Firms May Gain an Advantage: Bonnie sees a major opportunity for boutique consulting firms in the AI Era. Historically, large global systems integrators benefited from scale, brand recognition, and access to specialized tools. AI is leveling parts of that playing field by making sophisticated capabilities more broadly available. Smaller firms can now compete using many of the same technologies while offering highly experienced teams and direct client engagement. Visit Cloud Wars for more.

In today's Cloud Wars Minute, I look at Microsoft's latest moves to help organizations deploy and scale AI agents without sacrificing control. Highlights 00:10 — In the latest updates to Copilot Studio, Microsoft has introduced a series of improvements focusing on visibility and governance, allowing users to expand automation while maintaining control. Regarding visibility, the new analytics viewer role provides read-only access to an agent's analytics page. 00:36 — On top of this, Microsoft has expanded its agent usage estimator to include Dynamics 365 agents, enabling users to forecast Copilot credit consumption across both Copilot Studio and Dynamics 365 from one place. Microsoft already enables users to embed Copilot Studio agents into workflows using its agent node function. 01:16 — Other updates to workflows are designed to enable scaling without introducing governance risk. Workflows can connect to a larger toolkit, such as MCP server-enabled tools, to make it easier to take actions in systems, yet still within the Microsoft Security Framework. Users can also utilize agents built in Copilot Studio to bring interactive app experiences directly into Copilot Chat. 01:48 — This means they can review data, update records, approve requests, or create assets, all without having to switch tools. These are just some of the updates that Microsoft has been working on throughout April, and I really enjoy following the trajectory of these updates because they illustrate to me the current stage of our collective journey with AI. 02:11 — It's clear that agents are integrated into many systems, and now is the time to scale them securely. So, if you're still considering when and if to introduce AI-driven practices into your business, major directional changes like this should serve as a cautionary tale. Visit Cloud Wars for more.

In this episode of the AI Agent & Copilot Podcast, Giuseppe Ianni, AI Practice Lead and industry thought leader, is joined by Nandita Puri, PhD Candidate at Georgia Tech and founder of Illumia.bio. Puri discusses how AI is transforming drug discovery by creating massive therapeutic libraries, connecting fragmented biomedical knowledge, and dramatically accelerating research timelines. Their conversation explores the convergence of AI, structural biology, and life sciences. Key Takeaways AI Expands the Search Space for New Therapeutics: Traditional drug discovery focuses on identifying a single drug for a single target, but Puri argues that diseases are complex biological systems requiring broader approaches. Her team is building an AI-generated library of more than 10 billion molecules across multiple therapeutic modalities. By treating drug discovery as a combinatorics problem, researchers can explore vastly larger therapeutic possibilities. Connecting Fragmented Scientific Knowledge Accelerates Discovery: One of the biggest bottlenecks in pharmaceutical research is the fragmented nature of scientific information. Researchers often spend years reviewing hundreds of papers before forming a hypothesis. Puri describes how her team is integrating 60 to 70 public databases into a connected knowledge platform that links diseases, genes, proteins, pathways, and drug candidates. As she notes, "When we type a disease, we know exactly the gene, we exactly know the protein." This consolidation dramatically reduces research time and enables scientists to make more informed decisions earlier in the discovery process. AI Creates New Opportunities for Rare Disease Research: Rare diseases have historically been underserved because of the high costs and long timelines associated with traditional drug development. Puri says that bringing a drug to market can require "$1 billion and about 10 years." By shortening research cycles from years to months, AI lowers the barriers to investigating diseases that pharmaceutical companies may have previously avoided. This acceleration enables smaller teams to pursue treatments for conditions affecting fewer patients while increasing the likelihood that promising therapies can move forward to validation and clinical testing. Visit Cloud Wars for more.

In today's Cloud Wars Minute, I examine how Google Cloud is using AI Threat Defense to help customers fight AI-powered cyberattacks. Highlights 00:03 — If you're going to be number one on the Cloud Wars Top 10, you've got to fight to keep that position and stay ahead of the incredible and highly capable competition across the Cloud Wars Top 10. Google Cloud, I believe, has taken yet another big step in ensuring that it remains the number one company on the Cloud Wars Top 10 by launching a new cybersecurity approach. 00:57 — The person leading that is Francis deSouza, who is the Chief Operating Officer of Google Cloud, but also president of its security products. In a blog post last week outlining what this new AI Threat Defense is all about, deSouza said it's time now that business customers be able to fight AI with AI, to defend against these very powerful incursions that the bad guys are going to be making using AI. 01:58 — So, there needs to be, among customers, a big shift in how they do things. It can't be, "Let's just do a little bit more of what we've always done." There's got to be a new approach, and Google Cloud believes it's got that now with this AI Threat Defense for Google Cloud. I believe this is the latest in an ongoing series of steps they've made around cybersecurity. 02:54 — About a year ago — or several months ago — the company announced its intention to acquire Wiz, with its end-to-end threat monitoring and awareness capabilities. That deal has now been completed, and the most recent step, I believe, is the launch of this new solution called Google AI Threat Defense. 03:56 — Now, I'm not trying to read more into that than needs to be said. Maybe Google Cloud AI Threat Defense seemed overly clunky, but I wonder if, in some ways, parent company Google is riding this high now. Google Cloud itself had a growth rate of 63%, up from 48% in the prior quarter, so the company is definitely on a run here. Visit Cloud Wars for more.

In today's Cloud Wars Minute, I analyze how Marc Benioff is using Agentforce to drive larger deals, stronger customer spending, and new AI metrics. Highlights 00:02 — We see Salesforce is off to a good start here in its fiscal '27. For Q1 ended, let's see, April 30, it reported that overall revenue was up by 13% to $11.1 billion. I want to look into some of the big numbers within the Q1 presentation, and also the earnings call. It, I think, revealed just how heavily AI, and in particular Agentforce, have become the growth engines here inside Salesforce. 00:31 — Salesforce, after wandering for a few years trying to get its margins right to please institutional investors, is now riding the AI Revolution. So, I've got 10 numbers that I pulled out from that presentation and the earnings call. Agentforce was involved in, and Benioff said drove, almost half of the company's 100 largest Q1 deals. It had 98 that were $1 million or more. 01:15 — Agentforce was in about half of those. The most active AI users that Salesforce has, the ones doing what it calls agentic work units, detailing specific tasks that agents have completed, it said the most active AI users now have increased their spending with Salesforce by 1.5x from the previous year. So clearly customers are seeing the value in this now. 01:46 — Benioff said that over the years Salesforce has generated many, many millions of leads, more than its human salespeople could follow up on over that time. It put Agentforce on it, and autonomously it contacted 220,000 of these customers interested in Salesforce but who never got a call back, generating $42 million in pipeline from that. 02:45 — One other interesting point I'll note here is that Salesforce began to list Now tokens processed in the quarter, and it said it was 28.3 trillion tokens processed in Q1 through Salesforce as agents and applications. Now that's a number that it says it's going to be revealing every quarter here, and I think it's a great idea. It carries some risks. 03:13 — It's a great idea because it shows not just what people are spending on AI, but the work that is getting done in what they call these AWUs, or Agentic Work Units. Salesforce said that relative to Q1, the average work units undertaken by Salesforce customers was up 152%. That's sequential, quarter-to-quarter. Visit Cloud Wars for more.

In today's Cloud Wars Minute, I look at how Microsoft and EY are combining engineering and consulting expertise to scale AI transformation. Highlights 00:10 — Microsoft and EY have announced a substantial enhancement to their existing partnership, committing to invest over a billion dollars over five years into a new initiative aimed at helping organizations to scale AI. 00:40 — So, what's the plan for it? Well, it will combine Microsoft's forward-deployed engineers, or FDEs, with the expertise of EY industry professionals to accelerate AI adoption. Their approach focuses on, and I quote, “change management delivery models powered by Microsoft's FDE AI-native hypervelocity engineering approach.” 01:05 — Now, this initiative will see teams of EY business consultants and Microsoft engineers co-develop AI solutions tailored to address clients' highest-value business opportunities. This collaboration is steering companies toward the goal of becoming frontier firms. It's a term coined by Microsoft that I've used many times, that's gaining traction across the industry. 01:29 — Frontier firms are organizations that integrate agentic AI with the human workforce at scale and continuously optimize AI initiatives while adapting their company culture to thrive in this new future. Now, an interesting aspect of this collaboration is that EY, already closely aligned with Microsoft in terms of partners, was in fact the client zero for the initiative. 01:56 — This means they [the EY team] have an insider's understanding of what works well, how to adapt to Microsoft products, and how to effectively share this knowledge with potential customers and clients. Visit Cloud Wars for more.

In today's Cloud Wars Minute, I break down why Workday sees agentic AI as the key to defending its 80 million-user base. Highlights 00:02 — Workday co-founder Aneel Bhusri resumed his position as CEO. He wanted to help guide the company through the AI Revolution and help bring a solid knowledge of what's happening and how Workday as a company has to be able to innovate and create and get with the AI-native program as rapidly as possible. 00:45 — It's got to be able to move fast, and the margin for error is slight. The Q1 results, which came out last week, I think prove that Bhusri's got the company on the right track. Subscription revenue up 14.3%, almost $2.4 billion. Their total subscription revenue backlog was up 11% to over $27 billion. 01:23 — It's now got 80 million users under contract. Now, the good and the bad of that is those are 80 million users who are heavily dependent right now on yesterday's technology. So, the good thing for Workday is they've got these 80 million users, and Workday's got the first shot at converting them. 02:23 — Bhusri said, “In technology transitions — and I'm old enough to have lived through a few of them — you have to put that new technology front and center. It's got to be your absolute top priority in everything you do.” 03:38 — Bhusri said customers seem to want to have both open technology and the ability to use agents from lots of vendors, but they've also got to ensure that they've got the proper guardrails for compliance and legal compliance, and ensuring the privacy and safety of their customers. He also said it's really important for Workday to reinstitute and reinvigorate a startup mentality. 04:48 — So, Aneel Bhusri is one of the good guys in the tech industry. He's been around a long time. His return here, I called him back in February “the reluctant CEO,” because he was eager a few years ago to get out of the CEO role, but he knows now that with what's going on in the market and this vast change of technology brought forth by AI, he needed to be CEO. Visit Cloud Wars for more.

Bonnie Tinder is the founder and CEO of Raven Intelligence, an independent B2B peer review site that amplifies the voice of the customer. She focuses on software customers, consulting partners, and software vendors and helps identify the best partners for their needs. In this episode, she and Bob Evans speak about Workday's accelerating AI transformation following its Innovation Summit. Bonnie offers a practitioner's perspective on how Workday is rethinking enterprise software around agentic AI, faster deployments, embedded governance, and a startup-like culture shift under returning leadership. Episode 59 | Workday's AI Reset The Big Themes: Workday's Startup Reboot: Bonnie Tinder's biggest observation was that Workday appears to be entering a new operational chapter defined by urgency, sharper execution, and a startup mindset. Rather than behaving like an incumbent defending market share, Workday seems to be restructuring around focused AI ownership and entrepreneurial velocity. Bonnie connected this directly to Aneel Bhusri's leadership style, comparing it to Steve Jobs returning to simplify Apple's priorities. No One Wants DIY Enterprise AI: A major theme was the rejection of the “build it yourself” narrative for enterprise core systems. Bonnie and Bob both strongly challenged the idea that enterprises will vibe-code their own payroll, financials, or HCM systems. The reason is simple: risk. Enterprise systems are compliance-heavy, operationally critical, and intolerant of failure. Bonnie's “you can't get payroll 90% correct” line perfectly captured the reality. CEO Leadership Is Non-Negotiable: AI transformation must be CEO-led. Bottom-up experimentation alone is unlikely to produce meaningful enterprise change. AI affects operating models, workflows, investment priorities, talent strategy, governance, and competitive differentiation. That requires executive sponsorship and strategic ownership. Bob argued that companies cannot approach AI using 2023 or 2024 decision frameworks. Instead, leadership teams must rethink vendor evaluation, operational transformation, and business outcome measurement. Bonnie reinforced that major transformation initiatives succeed when leadership drives adoption from the top. The Big Quote: “The real AI gold rush isn't in the models, it's really that unglamorous work of moving 30-year-old legacy systems to a point where agents can actually do something with the data.” More from Bonnie Tinder: Connect with Bonnie on LinkedIn. Visit Cloud Wars for more.

In today's Cloud Wars Minute, I examine why Agentforce Operations could remove one of enterprise AI's biggest adoption barriers. Highlights 00:03 — While the flow of innovative and transformational agentic AI technologies has certainly shifted from a trickle to a flood, there are still many barriers to success, albeit barriers that companies across the board are diligently working to address and overcome. 00:33 — [Many] workflows were built for manual human oversight, often loosely governed and entirely unsuitable for agentic AI. Now, Salesforce aims to tackle this back-office issue and eliminate these bottlenecks with a new product called Agentforce Operations. 01:24 — The result is a system where, after manual processes are digitized, a task [can] take a mere amount of minutes [and] agents can handle the heavy lifting with human oversight. Business users can continually improve these processes without needing any coding knowledge. 01:48 —Aman Naimat, SVP and GM of Agentforce Operations at Salesforce said the following about this new product: “As companies accelerate AI adoption to become agentic enterprises, most are still burdened by an underlying layer of fragmented manual processes across supply chain, procurement, finance, and the broader back office.” 02:43 — This, particularly, is a clear example of a seamless interaction between agents and human operators. The human in the loop can specify the task that needs to be automated, while the system improves the quality of how the agent operates. Visit Cloud Wars for more.

In today's Cloud Wars Minute, I cover a recent court case leading to OpenAI having to clarify that ChatGPT is not a lawyer. Highlights 00:10 — There has been confusion about what OpenAI's core product, ChatGPT, is and isn't, particularly in a recent court case. OpenAI clarified that ChatGPT is not a lawyer after an individual used the AI tool to build her case and would cite it as a source. 01:30 — In its motion for dismissal, ChatGPT had to very specifically note that it's not a lawyer, it is not a person, and it does not practice law. OpenAI defined ChatGPT as a set of rules and words that help people understand what's going on around them. 02:30 — One of the world's most technologically advanced companies and innovators had to spell this out in court. There is a fair amount of humor to be found in this. 03:00 — To quote Pogo, "We have met the enemy, and it is us." Humans should be rightly proud of the tech innovations and AI advances emerging. However, there's always going to be this goofiness out on the fringes where things have to be spelled out. Visit Cloud Wars for more.

In today's Cloud Wars Minute, I unpack Microsoft's Work Trend Index and what it reveals about the rise of agentic AI in the workplace. Highlights 00:09 — Microsoft's 2026 Work Trend Index annual report is titled "Agents, Human Agency, and the Opportunity for Every Organization." Microsoft analyzed trillions of anonymized M365 productivity signals, surveyed upwards of 20,000 workers in 10 countries, and consulted with experts in AI, work, and organizational psychology. Here are some of the most revealing insights. 01:25 — An analysis of 100,000 Copilot chats found that 49% of conversations were focused on supporting cognitive tasks, ultimately enhancing the capabilities of these human participants. On top of that, 66% of surveyed AI users reported that AI has enabled them to dedicate more time to high-value work. 01:49 — Microsoft states that close to one in five workers are in what they call the frontier zone, which refers to what they describe as "the sweet spot where organizational capability and individual readiness reinforce each other." 02:14 — Microsoft says that the key to alignment is for companies to focus on AI absorption rather than simply AI adoption, and this involves redesigning how work is done and turning AI outputs into actionable insights. Visit Cloud Wars for more.

In today's Cloud Wars Minute, I unpack why Palantir's customer-first AI approach is outperforming much larger rivals. Highlights 00:06 — One of the drivers in 2025 and 2026 of that surge in the greatest growth market here has been Palantir, relatively small. It'll probably do seven and a half, $8 billion in the coming year. 00:42 — So I had a great chat, you can see it all, a one-on-one video conversation with Palantir architect Chad Wahlquist. Palantir's titles are a little peculiar, right? It has its own way of doing things, as it does in a number of ways. Chad's not just a typical enterprise architect. 01:23 — One of the things that's unique about Palantir is how its customers will come, sign an original deal, and then in a very short period of time, three, four, six months, greatly increase that deal because it's showing the value of the AI to the customer. 02:18 — Palantir is the company, I think, in sort of the more modern era, that's really brought this to the forefront. Chad and I talked about the partnership and the significance of that for customers, bringing together the immense data and industry expertise that SAP has. 03:15 — It's not a big rip-and-replace thing. How can we build on what you have and get you some very quick returns on this? Palantir's number one on the growth chart at 70%. Google Cloud surged into the number two spot at 63%. Visit Cloud Wars for more.

In this Cloud Wars special report, Bob Evans speaks with Chad Wahlquist, Architect at Palantir, about the company's explosive Q1 performance and the deeper forces driving enterprise AI adoption. Wahlquist explains how Palantir's model goes far beyond traditional software, combining forward deployed engineering, ontology, agentic AI, and enterprise infrastructure to accelerate customer outcomes. AI Infrastructure Rising The Big Themes: AI Building AI: One of the most striking themes is the shift from companies building AI products to building AI products with AI. Wahlquist describes a major evolution in enterprise delivery models, where Palantir has moved from “boot camps” to “agent camps,” using AI agents to help rapidly construct customer solutions. This dramatically compresses timelines from projects expected to take months down to days. The deeper implication is that AI is no longer just the product layer; it is becoming the production mechanism itself. SAP Migration Gets Reinvented: The SAP partnership emerges as one of the most strategically significant parts of the discussion. Wahlquist describes Palantir helping customers accelerate complex ERP migrations, including ECC-to-S/4 transformations, acquired-company integrations, and even mainframe modernization. Traditionally, these efforts consume years and hundreds of millions of dollars. Palantir's approach uses ontology plus agentic frameworks to interpret structured and unstructured enterprise information, identify mismatches, and automate execution paths. He claims 50%+ time compression in migration work. Efficiency As Corporate Proof Point: One fascinating element is Palantir's operating model itself. Evans references Alex Karp's claim that a company of Palantir's scale would traditionally employ thousands of salespeople, while Palantir operates with a dramatically leaner commercial organization. Wahlquist argues that product effectiveness changes the equation: engineers demonstrating working systems on customer data become the real sales force. He also notes Palantir internally runs on its own software, using Foundry-based systems for CRM, ticketing, finance, and operations. This creates both operational efficiency and credibility. The Big Quote: “What I'm seeing here is really the difference between, hey, I'm building AI products to I'm building AI products with AI.” More from Chad Wahlquist: Connect with Chad on LinkedIn, or learn about Palantir Foundry. Visit Cloud Wars for more.

In today's Cloud Wars Minute, I examine how AI demand is reshaping rivalries between Google Cloud, AWS, NVIDIA, and Anthropic. Highlights 00:03 — According to reports, Anthropic has committed to a $200 billion five-year agreement for Google Cloud services and Google-designed chips, a deal that could account for more than 40% of Google Cloud's revenue backlog. 00:18 — This represents yet another escalation in the rapidly expanding partnership between Google Cloud's parent company, Alphabet, and Anthropic, following Alphabet's previously announced $40 billion investment into the company. 00:49 — The company also holds considerable infrastructure deals with providers, including AWS and NVIDIA, and what this deal underscores is the extraordinary scale of demand for AI services. The need for compute capacity has grown so large that even a $200 billion agreement may not be enough to meet future requirements. 01:33 — However, companies like Google Cloud, with the infrastructure required to support hyperscale AI development, are positioned at the very center of this massive transformation. Visit Cloud Wars for more.

In today's Cloud Wars Minute, I look at how Google Cloud is pairing technical innovation with go-to-market execution to fuel AI growth. Highlights 00:00 — One of the fastest-growing companies in the Cloud Wars Top 10 is Google Cloud, and it has just launched a program of Forward Deployed Engineers (FDEs), specializing in AI to help accelerate AI transformation at the point of the customer. 00:46 — I had a chance to speak about this new AI FDE program with Matt Renner, President and Chief Revenue Officer at Google Cloud, and he was talking about how this brings the innovation out at the point of the customer, the unique challenges customers are facing right now. 01:38 — It isn't Google Cloud's attempt to get into the services business so much as this is what the demand is from customers now: they need to get their AI capabilities up to speed as quickly as possible to become the AI-powered type of company they're going to need to be. 02:25 — Google Cloud, as I've mentioned before, has always been an on-the-front-edge technological innovator, but over the past couple of years, it's been bringing its go-to-market capabilities and go-to-market innovation up. 03:36 — These efforts are going to be ways to help ensure that customers have the support, the resources, the expertise from Google Cloud and the ecosystem to be able to evolve, innovate, and succeed more rapidly than ever before. Visit Cloud Wars for more.

In this Cloud Wars conversation, Bob Evans speaks with Matt Renner, Chief Revenue Officer at Google Cloud, about the explosive acceleration of enterprise AI adoption and how Google Cloud is scaling to meet it. Renner explains why customers are demanding immediate business outcomes, not experimental pilots years down the road, and shares Google Cloud's response through expanded field engineering investments, ecosystem funding, and deeper enterprise co-creation. The discussion also explores Google's differentiated AI stack strategy, the intensifying competitive landscape, and why AI security could become one of the industry's most significant next battlegrounds.Google's AI Scaling Play The Big Themes: AI Demand Has Moved Beyond Experimentation: Matt Renner makes clear that enterprise AI has entered a fundamentally different phase. Companies are no longer satisfied with proof-of-concept experimentation or exploratory pilots. Instead, executive teams want measurable business value quickly. This urgency is reshaping vendor expectations, deployment models, and customer engagement strategies. Google Cloud is seeing demand at a pace that traditional scaling models cannot satisfy, which is driving operational changes. This is not a speculative future trend, it is already happening. The $750 Million Ecosystem Expansion Multiplies Capacity: Google Cloud's $750 million ecosystem investment complements the FDE initiative by scaling partner-led implementation capacity. Renner explains that Google alone cannot meet enterprise AI demand, so partner ecosystems become force multipliers. The strategy is to expand from hundreds of specialists into thousands of technical practitioners capable of building agents, workflows, and AI-powered solutions. This reflects a practical recognition that enterprise AI requires broad execution capability, not just core platform excellence. The AI Market Reset Is Reshaping Cloud Competition: Renner describes AI as a market reset that is materially changing competitive cloud dynamics. Google Cloud's growth rates, contrasted against hyperscaler rivals, are presented as evidence that strategic positioning matters. The broader takeaway is that AI has altered enterprise buying criteria, infrastructure priorities, and vendor differentiation. Long-term investments in chips, models, data infrastructure, and platform integration are beginning to show commercial returns. Rather than incremental cloud evolution, Renner presents this as a structural shift in the market. Enterprises are reallocating attention and budgets around AI capability. The Big Quote: “We're seeing unprecedented demand for Google Cloud products infrastructure, all driven, frankly, from AI." More from Matt Renner and Google Cloud: Connect with Matt Renner on LinkedIn or learn more about Google Cloud AI. Visit Cloud Wars for more.

In today's Cloud Wars Minute, I connect SAP, Palantir, and Ford to AI's expanding economic disruption. Highlights 00:11 — Recently, both SAP, number four on the Cloud Wars Top 10, and Palantir, number five on the Cloud Wars Top 10, have asked: Are we reaching the end of the term software or software company? 00:47 — But I think their idea is that, what we've thought of as software, what we've come to picture it to be, the image we have in our head, the mindset we have around software, is just getting blown away by what AI is capable of. 01:07 — Last week at the SAP Sapphire event, CEO Christian Klein said, “Will SAP be a software company in the future?” He asked the SAP Joule AI Assistant to answer the question, and Joule said, “SAP is going to be a business AI company.” 02:00 — Palantir CEO Alex Karp said, “You can't just lump what we're doing into the term software.” He said, “We're going to have to create a new term, because what we're doing goes beyond software,” and suggested the term AI infrastructure. 04:07 — Ford had built an enormous factory to build electric vehicle batteries, but now is considering shifting toward batteries for AI data centers, showing how AI's impact is extending beyond tech into the broader global economy. Visit Cloud Wars for more.

In today's Cloud Wars Minute, I unpack SAP CTO Philipp Herzig's perspective on AI, APIs, and the company's next era beyond traditional software. Highlights 00:01 — As part of our ongoing analysis of the massive changes that SAP rolled out this past week at their Sapphire event in Orlando, I had an interesting one-on-one conversation with SAP Chief Technology Officer Philipp Herzig, where he discussed a range of things. Particularly this notion of how, as SAP begins to move beyond applications into the realm of AI, what that means across everything from their new Business AI platform [to] updates to their API policy.   00:37 — I think some people got their knickers in a knot unnecessarily over those API changes and the general pace of innovation that not only SAP is cranking out, but that customers are working very hard to consume so that those customers can become leaders in their industries. 01:24 — How does this shape the company that SAP is becoming in the future? And even as talked about with CEO Christian Klein posing the question during his keynote, will SAP be a software company in the future? 02:07 — One of the things that Herzig said was, we've got so many more people using more and more of our APIs, agents are going to access data from all across the company, and certain things just have to be tightened up. One of the biggest things [SAP] did, was try to ensure that there's more security. 03:20 — So, lively discussion here. I think this was a momentous event for SAP, the things they introduced, the way they're talking about going to market, the new sorts of expertise they're putting in. Philipp touches on a lot of this and gives a good insight into the foundational technology layer. Visit Cloud Wars for more.

Bob Evans speaks with SAP CTO Philipp Herzig from SAP Sapphire in Orlando about SAP's AI strategy, platform evolution, customer modernization challenges, governance, and enterprise-scale agent deployment. Herzig lays out SAP's positioning around openness, business AI, autonomous agents, security, and migration support, while addressing confusion around API policy changes and fair-use limits. SAP's AI Inflection Point The Big Themes: SAP's AI Platform Is Becoming Cohesive: A major theme in the conversation is that SAP is presenting a more integrated AI vision rather than a collection of disconnected announcements. Herzig describes a layered architecture spanning UX, autonomous assistants, business process orchestration, governance, and the underlying AI platform. The emphasis is on a consistent enterprise AI framework rather than isolated tools. Migration Support Is Becoming Strategic: Migration is no longer framed as a technical back-office concern. Instead, it's becoming a strategic AI enabler. Herzig discusses SAP's toolchain investments, including LeanIX, Signavio, migration automation, testing support, code modernization, and agent-assisted implementation. The idea is to reduce friction in modernization so customers can reach AI readiness faster. Instead of treating migration as merely an ERP upgrade journey, SAP increasingly positions it as foundational infrastructure for enterprise AI transformation. Change Management Extends Beyond Technology: Herzig acknowledges that deploying AI agents is not simply a software problem, it's an organizational transformation issue. While SAP can accelerate technical deployment through tooling, governance, observability, and automation, customers must still rethink workflows, roles, and operating models. The discussion around developer productivity, AI-assisted coding, and human-agent collaboration reinforces this broader perspective. The Big Quote: ““There are good agents out there… there's also a lot of really bad agents out there… and they, of course, set the enterprise system under risk.” More from SAP and Philipp Herzig: Connect with Philipp Herzig on Linkedin or learn about SAP Sapphire. Visit Cloud Wars for more.

In today's Cloud Wars Minute, I explore how SAP's AI Revolution could redefine enterprise software through agents, data, and industry-specific intelligence. Highlights 00:03 — We are reporting here from the Sapphire show floor in Orlando. It's been a wild week here, and I had a great chance to talk with SAP Chief Operating Officer, Sebastian Steinhäuser about some of the changes that are going on there inside what I call SAP's AI Revolution. 00:21 — Covering everything from what it's doing with agents, how it's redefining their apps, how it's building up its Data Platform, and more. Sebastian offers some great insights into all of that, and we talked about it in a full-length video linked to down below. 01:13 — (Sebastian offers insights about) the rise of data within SAP becoming the foundation for everything, the Business Data Cloud moving into a very powerful area, the Business AI Platform now consolidating some different sort of platforms and technologies that SAP had so that customers can gain more from that more quickly. 02:00 — SAP sees the world, and Sebastian describes this, where there's going to be tens, hundreds of thousands of agents, perhaps millions, you know, a few years out. And certainly SAP is not going to build all of those. So it's going to be the partners that do this. 03:09 — SAP is more focused than ever before on delivering not just code (that happens to be what they make) but what SAP's real focus is: delivering superb business outcomes for customers. Visit Cloud Wars for more.

At SAP Sapphire in Orlando, Bob Evans sat down with Sebastian Steinhäuser to discuss what may be one of the most consequential strategic shifts in SAP's history. As enterprise AI moves from experimentation to execution, Steinhäuser outlines SAP's vision for the autonomous enterprise: where AI agents, assistants, business data, and deep industry expertise come together to solve real operational problems. AI with Industry Depth The Big Themes: Customers Want Outcomes, Not AI Demos: A recurring theme in the conversation is that enterprise leaders are not buying AI for novelty. They want measurable business outcomes. Customers are focused on solving hard operational problems such as improving supply chain resilience, winning in retail execution, streamlining regulated manufacturing, and modernizing enterprise workflows. This reflects a broader evolution in enterprise buying behavior. The AI conversation has moved beyond experimentation into operational accountability. The Autonomous Enterprise Is SAP's North Star: SAP's central narrative at Sapphire is the autonomous enterprise. Steinhäuser describes a future where AI agents and human workers collaborate, with AI taking responsibility for repetitive, process-heavy, and data-intensive tasks while employees focus on higher-value decision-making. This is more than a product launch — it is SAP's strategic framework for the next phase of enterprise software. The company references hundreds of AI agents and dozens of assistants spanning functional domains. Importantly, SAP is positioning these capabilities as practical rather than speculative. Ecosystem Scale Will Determine Execution: SAP clearly sees its partner ecosystem as critical to AI transformation at scale. Steinhäuser points to thousands of ecosystem participants at Sapphire and outlines investments designed to accelerate migration, implementation, and AI activation. This reflects enterprise reality: large organizations rarely transform through software vendors alone. Systems integrators, consulting firms, implementation specialists, and migration partners often determine whether transformation succeeds. The Big Quote: “Building the technology is one thing. Really changing processes, people, and systems to adapt AI, it's a totally different one." More from SAP: Learn more about Sapphire and about Joule Assistants. Visit Cloud Wars for more.

In today's Cloud Wars Minute, I examine why OpenAI bringing frontier models to AWS signals a new era of AI platform pragmatism. Highlights 00:03 — Hot on the heels of the news that OpenAI and Microsoft have re-explored the terms of their partnership, leading to a much more flexible outcome for OpenAI, the company has introduced an expanded partnership with AWS to bring OpenAI's latest models to Amazon Bedrock. 00:23 — The new solutions currently in preview include the launch of Codex on Amazon Bedrock and Amazon Bedrock managed agents powered by OpenAI. Now AWS customers will be able to leverage the latest OpenAI models through their existing Amazon Bedrock APIs and controls. 00:46 — Customers will be able to utilize OpenAI's coding agents to scale software development on Bedrock. And with Amazon Bedrock managed agents powered by OpenAI, teams can build and deploy production-ready OpenAI-powered agents on AWS, benefiting from the global infrastructure and security AWS provides. 01:06 — At the heart of this expanded partnership, particularly in terms of messaging from AWS, is the delivery of frontier AI to the infrastructure millions of organizations already trust, and this is one of the cornerstones we're seeing now in the AI Revolution in terms of partnerships. 01:39 — Companies are focusing on their strengths, which is crucial for the parts of the business that customers rely on and that really define them in the eyes of their users. Ultimately, it's the customers who will benefit from these collaborations moving forward. Visit Cloud Wars for more.

Highlights 00:28 — Over the past couple of years, SAP has been the growth leader in applications, growing anywhere from 50% to 250% faster than some of its major competitors. 00:41 — The company has undergone a shift to consumption pricing. This is something that will be phased in over the next couple of years. CEO Christian Klein says it reflects the way that people are using AI and the value they're getting out of the product. 01:12 — SAP is developing tighter relationships with AI innovators. An interesting one is Palantir, which is now billing itself as an AI infrastructure company, serving as the software foundation enabling AI to do its best work. 02:00 — There are three recent notable acquisitions: Reltio for Master Data Management Dremio for more SAP and non-SAP data pulled together Polar Labs to help SAP move forward with structured data 02:52 — Evidently, SAP is trying to capitalize on what's happening with the AI revolution and the new capabilities that come with it. I think that Klein's leadership, focus, and willingness to take ambitious moves with acquisitions and strategic partnerships will be force multipliers in the market. 03:47 — Forward-deployed engineers will be a big part of SAP's new AI alignment with customers, to help those customers rapidly develop and deploy AI agents and applications. Visit Cloud Wars for more.

In today's Cloud Wars Minute, I unpack why Workday customers are demanding AI agents and agentic capabilities. Highlights 00:03 — I had a chance to speak with Workday co-founder, then CEO, then chairman, now back as CEO, Aneel Bhusri. And absolutely, Aneel, I would say, is back as CEO. He is unplugged in this conversation and definitely fired up about Workday's prospects, and the sort of reimagination of the company as an AI-first, AI-powered, agentic powerhouse moving into the future here. 01:27 — He said none of them is talking about vibe coding applications. He said the enterprise apps are here, but he said "it's our job at Workday to ensure that they are reinvigorated and kept as modern as possible, with as much AI and agentic capability as possible." 02:29 — He also said, “We've got to take on a startup culture, startup mentality, a startup mindset that lets us continually experiment, push new things out, and not get stuck in doing things a certain way.” 02:58 — The opportunity now that customers see is for the right sort of agentic AI to come in to enhance what the applications are already doing, to help these companies move faster, get better insights, allow people to be able to move up to higher-value work. Visit Cloud Wars for more.

In this Cloud Wars conversation, Bob Evans sits down with Workday Co-Founder and CEO Aneel Bhusri for a candid discussion about AI's disruptive impact on enterprise software, the future of agentic workflows, and why Bhusri returned to the CEO role during one of tech's most consequential transitions. The conversation explores whether AI will replace software or labor, why systems of record remain strategically vital, and how enterprise leaders should think about governance, security, and business transformation as intelligent agents begin reshaping the operating model of modern organizations. AI Changes Enterprise Work The Big Themes: AI Replaces Labor, Not Software: One of the most provocative points in the conversation is Bhusri's assertion that AI is not currently replacing enterprise software, it's replacing labor. That distinction changes everything. Rather than displacing systems like HR, finance, or ERP, AI is being layered on top of those systems to automate work previously performed by people. Bhusri sees this as both a business opportunity and a societal concern. Systems of Record Still Matter: Despite “SaaSpocalypse” chatter, Bhusri argues strongly that systems of record remain deeply entrenched. Customers are not planning to rip out core HR or ERP systems and replace them with loosely connected AI tools. Instead, the competitive battle shifts to what gets built on top of those platforms. That's a major strategic advantage for incumbents with trusted enterprise infrastructure, data models, and governance frameworks. Bhusri groups Workday alongside SAP, Oracle, and Salesforce as vendors with durable strategic relevance. AI's Social Impact Is the Bigger Story: The most human part of the discussion comes at the end, when Bhusri expresses genuine concern about AI-driven job displacement. Unlike past automation waves focused on repetitive tasks, he worries this generation affects reasoning and knowledge work. Yet he remains optimistic that technology ultimately improves society. Still, he insists enterprise leaders must become part of the solution, not simply profit from disruption. The Big Quote: “Great tech companies aren't built on one generation of technology.” More from Aneel Bhusri and Workday: Learn more about Workday and AI Connect and Workday Agent System of Record. Visit Cloud Wars for more.

In today's Cloud Wars Minute, I explore how Workday and Achievers are using AI-driven behavioral intelligence to transform employee recognition and workforce engagement. Highlights 00:03 — Workday has made Workday Recognition provided by Achievers, available to its customers. This offering has been developed alongside Achievers, the world's leading employee recognition and reward software, integrating its features into the Workday experience. The new offering leverages AI to make it easier for HR teams to evaluate performance drivers. 00:29 — The integration enables employees to recognize their peers and redeem rewards directly within Workday, while streamlining these processes for HR within Workday Human Capital Management, or HCM. This integration provides HR teams with insights into in-demand skills and creates a broader picture of performance. 00:55 — Ben Carter, Senior Vice President, Total Rewards at Workday, explained, “Recognition fuels engagement, and engagement drives productivity, making it one of the clearest indicators of a thriving workforce. By bringing Achievers into Workday, we are helping customers amplify those everyday moments of appreciation and turn them into actionable insights..." 01:22 — By embedding Achievers directly into Workday HCM, Workday is showcasing a significant use case for enterprise AI. That's behavioral intelligence. This really, to me, represents a shift away from automation and instead leverages AI's ability to provide insights at a human level. 01:45 — Businesses are pursuing tools that can offer them a competitive advantage, especially in a landscape where many are targeting similar goals and deploying the same strategies and tools to achieve them. I believe tools like this, which focus on behaviors and reward performance as a result, will undoubtedly become powerful assets in the competitive business arsenal. Visit Cloud Wars for more.

In today's Cloud Wars Minute, I look at how Palantir's soaring growth reflects rising demand for disciplined, outcome-driven AI platforms. Highlights 00:03 — For the past several quarters, the fastest-growing company in the Cloud Wars Top 10 has been Palantir. It upheld that mark in Q1, and what I wanted to talk about today was their combination of extraordinary growth and also the rise from Palantir of a couple new terms to describe what's going on in AI right now. 00:30 — Palantir believes it's been successful because it is offering real solutions when other tech vendors — many other tech vendors, it says — are offering only incomplete portions of it. Total revenue was up 85% to $1.63 billion. If you take the U.S., which is both commercial and government or defense business, it's up 104% to $1.28 billion. 01:31 — Palantir has blown past its guidance in each of the last several quarters. Its big point about AI slop is that customers are wasting time and money with incomplete AI solutions that don't offer enough precision, enough rigor, enough discipline, so that every move that agents are making can be tracked with great specificity about cost, security, and ROI. 02:30 — Alexander Karp says there's a new category here that he thinks is more befitting of what Palantir does: AI infrastructure. These results are remarkable because it shows that what it is that Palantir is putting together, customers are loving. It's passed now 1,000 customers, and its customers are rapidly increasing the spending they're doing with them. 03:24 — Karp says business leaders have to start thinking differently about what they want out of AI and what a high-quality AI vendor is going to deliver for them. Palantir has been around for 23 years, and despite seeming like a startup company, it continues pushing forward on customer expectations and the value it's imparting to customers. Visit Cloud Wars for more.

In today's Cloud Wars Minute, I unpack how flexibility and competition are reshaping the AI ecosystem. Highlights 00:08 — One of the most important tech partnerships in the past decade has undergone a radical shake-up. I'm talking about Microsoft and OpenAI, the two companies have revealed new terms for their partnership agreement in a joint statement. 00:38 — "Today, we are announcing an amended agreement to simplify our partnership and the way we work together, grounded in flexibility, certainty, and a focus on delivering the benefits of AI broadly. This new agreement frees both companies up to pursue opportunities independently while maintaining a relationship." 00:59 — There is an endpoint for the length of time that Microsoft has rights to OpenAI's model. OpenAI is going to benefit massively from wider partner opportunities, but still, there are additional benefits for Microsoft as well. 01:17 — Microsoft will remain OpenAI's primary cloud partner, with products shipping first on Azure. However, OpenAI can now serve all its products to customers across any cloud provider. Microsoft will continue to have a non-exclusive license to OpenAI IP until 2032. 01:54 — Despite the significant alterations, Microsoft will continue to participate directly in OpenAI's growth as a major shareholder. Microsoft will benefit by not having to allocate so many resources, allowing it to focus on areas that align with its evolving business goals. Visit Cloud Wars for more.

At Google Cloud Next in Las Vegas, Cloud Wars Founder Bob Evans sat down with Managing Director for Internal Innovation, KPMG, Aaron Purcell to discuss how KPMG is accelerating AI transformation with Google Cloud. As both a customer and partner of Google Cloud, KPMG offers a unique “client zero” perspective, using Gemini and Vertex AI internally while helping clients do the same. Purcell explains why Google's full-stack AI platform stood out, how governance and speed can coexist, and why employee familiarity with consumer AI tools is changing enterprise adoption faster than ever before. KPMG's AI Playbook The Big Themes: Why Google Won: KPMG evaluated multiple AI providers, but Google Cloud stood apart because it offered what Aaron Purcell called the “full stack.” Instead of piecing together separate providers for models, infrastructure, and agent development, Google delivered an integrated platform that included model creation, cloud services, infrastructure, and a mature agent-building platform through Vertex AI. That end-to-end capability gave KPMG confidence that execution would be faster and more scalable. Consumer AI Accelerates Enterprise Adoption: One of the biggest accelerators for enterprise AI adoption is that employees are already using similar tools at home. Purcell noted that many people already have experience with Google products in their personal lives, making workplace adoption much easier. Tools like NotebookLM and Gemini Enterprise feel intuitive because users recognize the patterns and workflows from consumer applications. Instead of learning entirely new systems, employees translate familiar habits into the workplace. This reduces resistance, shortens training time, and improves confidence. Keeping Up With Vertical Innovation: Purcell said the pace of AI innovation is no longer a hockey stick. It feels like a vertical line. New capabilities are arriving so quickly that organizations need systems to keep employees informed without overwhelming them. KPMG uses Gemini Enterprise itself as a communication platform, with announcement sections highlighting new features and important updates. They also run office hours, user sessions, and collaborative education efforts to keep professionals current. The Big Quote: “We're providing the general user with the ability to create their own agents for personal productivity.” More from Google Cloud and KPMG: Learn more about Google Cloud and KPMG and Google Cloud's alliance. Visit Cloud Wars for more.

In today's Cloud Wars Minute, I compare AWS's impressive quarter with the even faster momentum of its competitors. Highlights 00:01 — Wanted to talk today a little bit about the Q1 that AWS just had. I think they revealed an awesome acceleration in Q1, but in a competitive sense, it's still falling behind competitors like Google Cloud, Microsoft, and Oracle. 00:36 — After three years, our AI run rate now for AWS is $20 billion, compared to $58 million for cloud in its early years. Jassy emphasized how aggressively AWS is pushing into AI and highlighted four key reasons behind this acceleration. 02:05 — AWS revenue grew 28% to $37.6 billion, its highest growth in 15 years. However, Google Cloud is growing at 63%, Microsoft at 29%, and Oracle at 44%, with all three showing stronger backlog growth. 02:55 — A couple things can be true at the same time. AWS had a strong quarter and happy customers, but on a competitive basis, it ranks last in growth rate, backlog size, and backlog growth among hyperscalers. 03:52 — AWS remains strong in a massive market with many customers, but compared to competitors, it has the smallest and slowest-growing backlog. Those are the facts on the ground today in the cloud market. Visit Cloud Wars for more.

In today's Cloud Wars Minute, I break down how hyperscalers reached a staggering $2 trillion backlog and what it means for the future of AI infrastructure. Highlights 00:03 — The hyperscaler market (the four big companies that are helping to shape the world with the power of AI), their backlog has now hit $2 trillion. So not just their recent revenue, talking about future commitments, contracted business not yet recognized as revenue: $2 trillion. Talk about some responsibility. 01:21 — So you see Microsoft's backlog almost doubled: $627 billion. Oracle's up a whopping 325% to $553 billion. We've got Google Cloud with a huge jump, 93%, $462 billion, and AWS, very nice number, but relative to the others it is not quite up to snuff at 49%, $364 billion. 02:25 — So I think AWS is doing a good job; it's just its competitors are doing a better job — higher growth. All in all, this rolls up to more proof: this is the cloud AI market, the greatest growth market the world has ever known. 02:52 — Google Cloud, on its revenue side, 63% growth, and then by far its fastest growth backlog number here, 93%. This is a red-hot company, not just for the last few months — this backlog shows a huge number coming forward. 03:39 — This is a fantastic time to be a customer in this business because you've got unbelievable demand. The competition from these companies is showing they've got to continue to innovate as rapidly as possible and give their customers more choice. Visit Cloud Wars for more.

In this episode of the AI Agent & Copilot Podcast, Cloud Wars Founder Bob Evans, is joined by James Lennox, Director of Product, Microsoft, who shares his perspective on AI transformation, enterprise adoption, and the evolving human-AI relationship. Recorded live at the 2026 AI Agent & Copilot Summit NA, Lennox explores how tools like Copilot and Work IQ are reshaping productivity, governance, and innovation across industries. Key Takeaways Delegation is the New Productivity Model: Lennox underscores a fundamental shift: “I can delegate those long-running tasks to AI.” This evolution allows humans to move away from repetitive execution and focus on strategic, creative, and decision-driven work. With platforms like Work IQ acting as the “brain behind Copilot,” organizations gain end-to-end visibility into business processes. This changes not just efficiency, but the very nature of work — humans become orchestrators rather than operators, dramatically increasing output and impact across roles. Governance is the Gateway to Scale: One of the biggest blockers to AI adoption isn't capability, it's control. Lennox notes organizations ask: “How do I have the governance and oversight to roll this out at scale?” Tools like Microsoft Agent 365 aim to solve this with “full observability, full control, full security.” Without trust frameworks, AI remains experimental. With them, it becomes operational. This highlights that enterprise AI success depends as much on infrastructure and policy as it does on innovation. AI is Universally Applicable Across Industries: Lennox observed leaders from diverse sectors, manufacturing, healthcare, and food services, all exploring AI adoption. “There is so much broad applicability…to real business process automation.” This reinforces that AI is not industry-specific but function-specific. Whether it's document processing or supply chain optimization, AI can integrate into virtually any workflow, making it a universal transformation layer rather than a niche tool. Visit Cloud Wars for more.

In today's Cloud Wars Minute, I analyze the shifting balance of power between Google Cloud and AWS. Highlights 00:03 — Last week, we had three of the four hyperscalers report their Q1 numbers. It's been fascinating to look at those. While everybody did very, very well, Google Cloud just had an utterly exceptional, spectacular Q1, and I think the evidence of what we see in these comparative numbers shows why Google Cloud has risen to number one. 00:51 — If we compare side by side, Google Cloud and AWS in Q1 on the growth rate, their revenue, their backlog growth, and the backlog numbers — the growth: 63% to 28%. Now we will certainly hear from a lot of the AWS fanboys that that's just because there's a discrepancy in size. That's true, but it does not cover this discrepancy in growth rate. 01:35 — For Google Cloud, the backlog grew 93% to $462 billion. For AWS, the backlog grew 49% to $364 billion. Really impressive numbers here from AWS, but they play in a market with some other pretty good companies as well. Google Cloud shows 93% backlog growth versus 49%, and $100 billion bigger in backlog total versus AWS. 02:31 — AWS in Q1 had 85% more revenue than Google Cloud. Then how do you explain this backlog discrepancy? It shows that going forward, which is what the backlog shows us, future trends of business, Google Cloud is winning much more business in the future. Google Cloud is winning more new business, and that's where the game is being played. 03:25 — So clearly, the whole AI boom had a huge impact on these numbers. We saw Microsoft, just to toss this in, Microsoft's growth rate was 29% in Q1, its fiscal Q3, and its RPO, which is its version of backlog, was up, it said, 99% to$ 627 billion. Oracle, its RPO was up 325% to over $550 billion. So, it's just an incredible market here right now. 04:05 — For a long time, AWS has conditioned the market to say AWS is the king of the cloud and it will be forever. That's just not true anymore. Google Cloud, through innovation and jumping into the AI game early and aggressively, is booming right now, and its core cloud business is doing very well. Visit Cloud Wars for more.

At Google Cloud Next in Las Vegas, Bob Evans sat down with Karen Dahut, CEO of Google Public Sector, to discuss how AI, security, and open cloud strategies are reshaping government services. Dahut shared how Google Public Sector was built on the belief that government agencies deserve the same advanced commercial technologies as private enterprises, and why that decision is now proving critical in the era of agentic AI. AI Reinvents Government The Big Themes: Commercial Cloud for Government: Karen Dahut explained that when Thomas Kurian became CEO of Google Cloud in 2019, he challenged the outdated assumption that public sector organizations should receive different or lesser technology than private enterprises. Instead of building a separate, restricted GovCloud environment, Google chose to accredit its full commercial cloud for government use. This gave agencies access to the same scalability, resiliency, and innovation cycles as Fortune 100 companies. That decision is especially important now because AI workloads demand enormous scale. Leadership Makes AI Real: Technology alone does not create transformation — leadership does. Dahut highlighted examples from the FDA, Department of Transportation, and the City of Los Angeles, where visionary leaders are actively driving AI adoption rather than waiting for change to happen. These executives are not simply buying software; they are rethinking how agencies operate, from transportation systems to drug discovery to citizen services. Dahut stressed that real AI success requires courage, education, and enablement alongside strong technology. Open Cloud Is Responsible Government: Dahut strongly argued that openness is not optional in public sector technology, it is the only responsible approach. Governments operate with decades of legacy systems, massive backlogs of information, and multimodal data spread across many environments. Forcing all of that data into one cloud platform would be expensive, slow, and ultimately harmful. Google's approach is to leave the data where it already exists and analyze it there, avoiding costly ingress and egress fees and preventing vendor lock-in. The Big Quote: “AI and agentic AI is truly going to be one of those technologies that we look back on 10, 15 years from now and say that was truly the most transformational piece of technology since the transistor.” More from Karen Dahut and Google Cloud: Connect with Karen on LinkedIn or learn more about Google Cloud Public Sector. Visit Cloud Wars for more.

In this special episode of Cloud Wars Live, Bob Evans sits down with Steve Miranda, Executive Vice President of Applications Development at Oracle, from Oracle Park in San Francisco to discuss one of the biggest shifts happening in enterprise technology: agentic AI applications. Miranda explains how Oracle is moving beyond embedded AI and AI agents to fully agentic applications that can act on business objectives rather than just automate transactions. From finance and supply chain to HR and customer service, he shares how this transformation is changing operations, competitiveness, employee roles, and the very mindset organizations need to succeed in the AI Era. Rise of Agentic Apps The Big Themes: From AI Features to Agentic Applications: Steve Miranda explains that Oracle's AI journey has evolved in three major stages. First, Oracle embedded AI directly into applications to help generate and enhance content, improving the traditional user experience. Next came AI agents — workflow-driven systems capable of handling transaction sequences across ERP, HCM, supply chain, and CX. Now Oracle is introducing agentic applications, which represent a full redesign of enterprise software. These systems allow users to set business objectives rather than manually manage transactions. Instead of handling purchase orders, invoices, or approvals individually, users provide strategic guidance while AI agents execute, monitor, and optimize outcomes. Competitive Advantage Comes from Speed: Miranda stresses that agentic AI is not only about reducing costs through automation — it is about increasing business speed and adaptability. In competitive markets, companies need to react instantly to supply chain disruptions, shifting cash positions, pricing opportunities, and customer demands. Human-driven workflows create delays, while agentic applications can monitor both internal operations and external market conditions in real time. AI can identify early payment discounts, detect supply chain disruptions, or recommend immediate operational adjustments faster than traditional teams. This responsiveness creates a major competitive edge. Companies that adopt agentic applications can operate faster and more efficiently, while those that delay risk falling behind competitors who are able to move at machine speed Oracle's Pricing Philosophy Supports Adoption: Miranda explains that Oracle's pricing philosophy for AI remains intentionally customer-friendly. Core AI improvements — including embedded AI and standard agentic capabilities — are included within existing application subscriptions. Customers subscribing to financials, HCM, supply chain, or other Fusion applications receive these enhancements as part of the normal service evolution, much like database upgrades. Additional charges apply only when customers extend applications further, such as building custom agents or adding specialized workflows through Agent Studio. Those extensions use token-based pricing, which reflects current industry standards for AI usage. This model gives customers both innovation and flexibility: they benefit from improved core functionality without surprise costs, while paying incrementally only when they choose to expand AI into additional areas of the business. The Big Quote: “We're essentially rebuilding our applications from the ground up to make them agentic.” More from Steve Miranda and Oracle: Connect with Steve on LinkedIn or learn more about Oracle AI Agent for Fusion Applications. Visit Cloud Wars for more.

In today's Cloud Wars Minute, I explore how Oracle is redefining enterprise software with AI agentic applications. Highlights 00:03 — One of the biggest stories of the year, maybe the next few years, is going to be the rise of generative AI, the animating force behind business innovation and unlocking new ways for businesses to work, to run, to see the future, to adapt, and to give people higher-value opportunities as well. 00:29 — Oracle, I think, has been the most articulate and the most active in framing out how agents and applications are going to work together in the future. There has been this false choice brought up that it would be apps or agents, but that is not where things are headed. 01:09 — What we're seeing now is not going to be apps and agents. Oracle is fusing them together, calling them AI agentic applications. Steve Miranda explained in a longer conversation I had with him how these applications are different, what the business benefits are for customers, and how this new AI agentic revolution is changing enterprise software. 02:34 — Oracle is saying these AI agentic applications will trigger a shift of applications being systems of record to systems of actual outcomes. The agents are going to pursue not just task by task, but business outcomes, business goals, and business objectives. 03:51 — Companies that move quickly will be able to reposition their people to do higher-value work instead of drudge work. The risks of waiting are growing scarier as the pace of innovation increases, and leaders need to aggressively and confidently take on these new technologies. Check out my longer conversation with Steve Miranda here. Visit Cloud Wars for more.

In this episode of the AI Agent & Copilot Podcast, host Giuseppe Ianni speaks with Parmesh Rajan, VP of Technology for HSO US, live from the AI Agent & Copilot Summit NA in San Diego, California.Rajan explains how organizations are moving beyond experimentation and embedding AI directly into business processes, implementation delivery, and workforce productivity. The discussion highlights a shift from standalone copilots toward operational, production-grade AI agents that deliver measurable outcomes. Key Takeaways AI Embedded in Core Operations, Not Add-On Tools: Organizations are moving from experimenting with AI to embedding it directly into enterprise systems and workflows. As Parmesh Rajan explains, the goal is to shorten complex ERP implementations and integrate AI into core business processes like finance, operations, and customer engagement rather than treating it as a standalone capability. Automation Across the Entire Implementation Lifecycle: HSO is applying AI across the full delivery stack—from gap-fit analysis and solution design to coding assistance and data transformation. This is helping reduce manual effort in traditionally lengthy 12–18 month implementations while improving accuracy and accelerating time to value for customers. Adoption Depends on Workflow Fit, Not Agent Quantity: Industry-specific AI agents are critical for real-world adoption because they align with how users actually work. Examples like automated timesheets and AI-driven expense processing show that success comes from embedding agents into daily workflows, with effectiveness ultimately measured by usage rather than the number of agents deployed. Visit Cloud Wars for more.

In this episode of the AI Agent & Copilot Podcast, Cloud Wars Founder Bob Evans is joined by Dona Sarkar, Chief Troublemaker of AI Adoption at Microsoft, who shares her perspective on how leaders should approach AI adoption, why fear around AI replacing jobs is misplaced, and how executives can create a culture of experimentation. Speaking from the 2026 AI Agent & Copilot Summit NA in San Diego, Sarkar explains why organizations need AI-first thinking, stronger leadership involvement, and a focus on solving impossible problems rather than simply improving existing workflows. Key Takeaways AI Won't Replace You — But Someone Using AI Might: Sarkar strongly pushes back against the fear-driven narrative around AI replacing workers. She explains that change does not happen overnight and that professionals should focus on becoming AI power users instead of waiting for disruption to happen to them. As she puts it, “We will be relevant, irrelevant. Who's they? Exactly. You can be they.” She encourages workers to learn AI within their own discipline (legal, finance, sales, or operations) and become the person who understands how to train, guide, and supervise it. The future belongs to those who learn to “harness its power.” AI Should Solve Impossible Problems, Not Just Existing Ones: Rather than using AI only to optimize familiar work, Sarkar believes organizations should target the problems they have never been able to solve. She says, “Let's go solve the problems we've never been able to solve because we just don't have the human capital.” This shift moves AI from being a cost-cutting exercise to a growth engine. Leaders should use AI to uncover opportunities, identify market gaps, and rethink what their companies are capable of delivering in the future. Focus on Team Productivity, Not Personal Productivity: Sarkar argues that many companies are stuck in outdated AI use cases like meeting summaries and individual task optimization. She believes the real opportunity lies in workflow transformation across teams. “You have to get outside the personal productivity experiments.” By identifying full workflows — like sales enablement or content operations — and improving them with AI agents, companies reduce fear and unlock capacity for new work. AI should create room for innovation and experimentation, not simply make individuals feel more replaceable. Visit Cloud Wars for more.

In today's Cloud Wars Minute, I explore how Stellantis and Microsoft are launching one of the most ambitious enterprise AI collaborations yet, spanning engineering, cybersecurity, and large-scale operational transformation. Highlights 00:09 — Stellantis, the automaker responsible for well-known brands such as Dodge, Jeep, Peugeot, and Ram Trucks, has partnered with Microsoft in a five-year strategic collaboration. 00:19 — The goal of the partnership is to accelerate the company's digital transformation through advanced AI systems, enhanced cybersecurity measures, and next-generation engineering capabilities. Stellantis has already been an early adopter of AI, embedding the technology directly into its vehicles. 00:38 — Now, by collaborating with Microsoft, the company plans to accelerate this AI momentum across the enterprise. Judson Althoff, EVP and Chief Commercial Officer at Microsoft, explained that combining Stellantis' global scale and engineering expertise with Microsoft's trusted cloud, AI, and security platforms will deliver real value for millions of drivers worldwide. 01:03 — In total, the partnership will lead to more than 100 AI initiatives designed to enhance customer care, product development, and operations. This includes AI-powered product development and validation, predictive maintenance and testing, and faster deployment of new digital features and services. 01:48 — This is an incredibly ambitious project — one of the most significant I've seen not only in the automotive sector but across AI transformation initiatives overall. I'll continue following developments closely and sharing updates. Visit Cloud Wars for more.

In this episode of Cloud Wars Live, Bob Evans sits down with Tirthankar Lahiri, Senior Vice President for Mission-Critical Data and AI Engines. Lahiri explains how agentic AI is transforming enterprise applications from simple question-answer systems into action-driven platforms that can reason, remember, and securely execute tasks. He details Oracle's strategy around unified agent memory, private agent factories, deep data security, and open development standards, all designed to help customers build scalable, secure, and flexible AI systems without added cost. AI Built Securely The Big Themes: Agentic AI Becomes Action-Oriented: Tirthankar Lahiri explains that agentic AI represents the next major step beyond generative AI. While generative AI focused largely on answering questions and producing content, agentic AI is designed to take action. It allows businesses to build systems that can reason, decide, and execute tasks autonomously. Oracle sees this as the future of application development, where AI becomes embedded into workflows rather than functioning as a standalone tool. Oracle Builds AI Directly Into the Database: Rather than forcing customers to move data across multiple isolated systems, Oracle's approach is to bring AI directly to the data. Lahiri argues that data is the “ground truth” and moving it creates technical debt, silos, inefficiency, and security vulnerabilities. Oracle's converged database architecture supports multiple data types, including relational, graph, spatial, and vector, inside one unified environment. This eliminates the need for separate repositories and allows AI agents to access all relevant context without fragmentation. Deep Data Security Protects Against AI Risks: Lahiri strongly emphasizes that traditional application-layer security is no longer enough in the age of AI. Since AI can generate SQL and potentially bypass interface restrictions through prompt injection, businesses must secure data directly at the source. Oracle calls this “deep data security.” He uses the analogy of protecting valuables in a safe bolted to the floor rather than simply locking the front gate. Even if someone gets inside the house, the valuables remain protected. Similarly, Oracle enforces security policies at the database level, ensuring agents can only access data users are authorized to see. The Big Quote: "You need to secure data. Need to lock your valuables into the safe deep inside the house." More from Tirthankar Lahiri and Oracle: Connect with Lahiri on LinkedIn or learn more about Oracle AI Database. Visit Cloud Wars for more.

In today's Cloud Wars Minute, I break down Google Cloud's $750M partner ecosystem investment and its aggressive push to lead the agentic AI transformation race against Microsoft, AWS, and Oracle. Highlights 00:03 — Last week in Las Vegas, we saw Google Cloud roll out an incredibly broad, deep set of agentic AI technologies and solutions. They're making a massive push on this. Google Cloud is the number one player in the Cloud Wars Top 10, and they're looking to really take the big lead in agentic AI transformations for their customers. 00:24 — Now, in parallel with that, we also saw Google Cloud — in addition to all what they're doing on the tech track — on the go-to-market side. They have put together what they're calling a $750 million fund for their ecosystem and partners to help them drive AI transformations for customers, right — to help them get better training, to be more technically proficient, to help deploy engineers, and more. 00:53 — So I'm wondering now, in light of this, both the tech splash that Google Cloud made at Next but also now with this push for their partner ecosystem, will Microsoft and AWS match this massive, I would say unprecedented, investment in the ecosystem? 02:26 — You've got, not so long ago, I think you could look at what we called broadly the hyperscalers, and it was a little bit hard to differentiate, right? They were just sort of known as this one blob. I think the companies Microsoft, AWS, and Oracle are differentiating themselves now to a vast degree. 02:47 — I think what Google Cloud is trying to do here is say, “Hey, we're going to do all the stuff we did for you before, but we are going to focus more intensely than any company on Earth on the agentic AI revolution, to provide not just the technology, but the skills that you need from the partner ecosystem." 03:37 — And then it's putting the money behind this to ensure that those partners have the capabilities to do it — and to do it very quickly — because this is a race to see who is going to get that first-mover status. So far, I believe Google Cloud is in that for agentic AI transformations for customers across the globe and across industries. Visit Cloud Wars for more.

In today's Cloud Wars Minute, I break down how SAP is outperforming Oracle, Salesforce, Workday, and Microsoft in the applications race. Highlights 00:03 — We saw some first-quarter numbers from SAP late last week, and I think it's fascinating to see how, in the light of these very, very strong numbers from SAP, we still seem to hear about this idea that these doomsayers are saying that AI is going to destroy the enterprise apps business. That's certainly not happening. 00:33 — The three big numbers here: cloud revenue up 27%, almost $7 billion. Within that, its Cloud ERP Suite was up 30% to $6.1 billion, and looking out at contracted business not yet recognized as revenue, it calls it current cloud backlog, up 25% to well over $25 billion. 00:57 — That's pretty healthy-looking business for one that is, you know, doomed to the apocalypse and Armageddon any day now, according to some of these wizards of smart who believe that AI is going to come in and just decimate the enterprise apps business. 01:52 — The only thing I can think of that gives them this idea that the whole industry is heading for Armageddon here, they must believe that companies like SAP are unprepared for or unable to participate in the AI revolution, but that notion ignores where the data really is. 02:28 — Agentic AI is the future. Agents need data to run, and who has more and better business data than SAP? So this just confounds me. 02:43 — We continue to see SAP outperform Oracle's applications business, Workday, Salesforce, and also the apps business part of Microsoft Dynamics 365. I think this is a very strong quarter by SAP, and the future here is very bright. Visit Cloud Wars for more.

ogle Cloud Next, Cloud Wars CEO and Founder Bob Evans sits down with Karthik Narain, Chief Product and Business Officer, Google Cloud, to discuss how AI is fundamentally changing enterprise expectations. Narain explains why customers no longer judge technology providers by licenses sold or cloud consumption, but by measurable business outcomes. From forward-deployed engineers to agentic workflows and the evolving role of product design, he outlines how Google Cloud is rethinking engagement, product development, and enterprise transformation in what he calls the third major wave of technology innovation. AI Demands Outcomes The Big Themes: Outcomes Replace Consumption Metrics: Narain explains that enterprises are no longer measuring technology providers by how many licenses they sell or how much cloud consumption occurs. Instead, success is now judged by outcomes delivered. Customers expect providers like Google Cloud to share equal responsibility for business results, not just provide tools and leave execution to the customer. This represents a major shift from prior eras where businesses viewed themselves as the sole owners of converting technology into value. AI's speed and sophistication have raised expectations dramatically. The Third Technology Wave: Narain frames today's AI era as the third major wave of enterprise technology over the past 60 years. The first wave from mainframes through ERP, focused on codifying business processes into repeatable systems. The second wave centered on delivery model innovation, moving software into SaaS and cloud environments. The third wave is fundamentally different because the technology itself learns and evolves. Rather than giving software fixed instructions, enterprises must feed it data, context, and reasoning. This changes how software is designed and deployed. Every Feature Must Become a Skill: Products must now be designed for both humans and AI agents. Narain explains that every feature inside enterprise software needs to be exposed as a “skill” that agents can activate directly. This means software can no longer assume a human user is the only operator. Agents must be able to trigger workflows, execute tasks, and coordinate processes independently. This changes how products are structured from the ground up. The Big Quote: “The application's user interface is no longer clicks and drop-downs. It is going to be prompts and agentic workflows." Visit Cloud Wars for more.