Cloud Wars Live with Bob Evans

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.

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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.

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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.

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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.

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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.

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