
Hosted by Bob Evans · EN

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 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 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 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 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 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.