Cloud Wars Live with Bob Evans

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.

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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.

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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.

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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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