Cloud Wars Live with Bob Evans

In today's Cloud Wars Minute, I explore why Gartner expects many agentic AI projects to disappear as enterprises get more serious about measurable business value.
Highlights
00:14 — We're starting to see some interesting analysis coming out of organizations like Gartner. Gartner is saying that 40% of agentic AI projects die by 2027. There are a lot of projects that are going on within organizations that don't actually have good business value or good return on investment.
00:52 — And we already started to see a lot of pilots that were just failing over and over and over because people were trying to implement technology just for technology's sake. So, I think we're going to definitely see an improvement across organizations around the world.
01:33 — And so, what we want to see is a separation between organizations that are just basically doing what we refer to as agent washing, which is just taking and putting in an agent, whether that agent is actually doing anything of value or not within their organization or as a product. They're just following that trend.
02:02 — Agents or AI technology that's coming in to actually solve new problems, not just put a fancy UI on top of an existing API. So, those types of things, we should continue to see organizations getting better at this, but it will mean we will see a reduction in the number of players in this space over time.


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Bob Evans speaks with Chris Leone, Executive Vice President of Applications Development at Oracle, about Fusion Claw and Oracle’s push toward increasingly autonomous enterprise applications. Leone explains how Fusion Claw combines AI reasoning with deterministic enterprise computation to tackle complex, long-running work involving optimization, simulation, reconciliation, and planning.
The Rise of Fusion Claw
The Big Themes:
From Assistance to Execution: Oracle’s vision for enterprise AI is moving beyond assistants that help employees complete individual tasks toward systems that can actually perform substantial portions of business work. Chris Leone describes Fusion Agentic Applications as being organized around outcomes rather than traditional application functions. Instead of navigating separate processes and modules, organizations can define an objective — such as paying employees accurately and on time — and allow agentic applications to continuously work toward it. Fusion Claw extends this model to harder, specialist-grade problems requiring reconciliation, optimization, simulation, or extensive computation.
Reasoning and Execution Separate: A central architectural idea behind Fusion Claw is separating probabilistic AI reasoning from deterministic enterprise computation. Leone argues that running millions of transactions and calculations through an LLM would be economically inefficient and would struggle to provide the precision enterprises require. Instead, AI interprets the objective, reasons about the problem, creates a plan, and assembles the necessary tools. Oracle says the result is an architecture capable of combining AI’s reasoning abilities with scalable, precise enterprise execution rather than expecting an LLM to perform every stage of the process.
CEOs Can Refocus on Outcomes: Leone argues that the outcomes CEOs care about have not fundamentally changed. Companies still want to close their books faster and accurately, pay employees correctly, improve margins, reduce supply chain costs, and optimize profitability. What may change is how organizations pursue those objectives. Historically, employees often exported information into spreadsheets or specialized applications, performed analysis externally, and then returned to transactional systems to implement their decisions. Fusion Claw is intended to bring more of that optimization work inside the enterprise application environment.
The Big Quote: "The more control you put into the system, the more autonomous you can let the system run. So, the more control and governance we can put into these systems, the more autonomous execution we can allow."
More from Chris Leone:
Follow Chris on LinkedIn or learn more about Fusion Claw and AI governance.

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In today's Cloud Wars AI Minute, I explore the shift from using AI for workforce reduction to using it to amplify human productivity.
Highlights
00:18 — There's starting to be a better understanding that there's not a lot of value necessarily in just using AI to be able to do automation. What we're seeing is it does do a great job at this, and it frees up your resources to be able to go do other things.
00:36 — What we're starting to see, though, is some analysis coming back that is allowing us to be able to understand what we actually think is a wise strategy for those resources that are being freed up, versus bad strategies in organizations that may be looking at doing layoffs of certain resources and things.
01:16 — Gartner is now saying that by 2029, it's expecting 30% of all AI-driven layoffs to be rehired, and not only rehired, rehired at a higher cost than they were before. And that's due to the fact that there's going to be this sort of renaissance that we expect to happen, which is where companies that believe that they were going to get a ton of value out of AI, which they are, and they're getting freed up to be able to free up resources.
03:02 — AI and AI partnership with humans is actually resulting in being able to make a lot more value in a shorter period of time, and that makes it easier for your competition to be able to be even more competitive if they simply reinvest those resources versus just letting them go and taking a short-term bump on their revenue.

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In today’s Cloud Wars Minute, I break down the latest Cloud Wars Top 10 growth chart and the extraordinary momentum reshaping AI and cloud.
Highlights
00:03 — Got the latest Cloud Wars Top 10 growth chart numbers for you, in which we lay out here the hottest AI and cloud vendors in the world. And right now, we've got number one, Palantir; number two, Google Cloud; number three, Oracle. For Palantir, number one, 93% [growth].
00:53 — Google Cloud, up 82% to $24.8 billion. Like Palantir, Google Cloud has been on an upswing for the past few quarters. Oracle's cloud business, powered by its Oracle Cloud Infrastructure, up 62%, $11.6 billion in total cloud revenue. AWS completing, or now topping, a very nice return to growth over the last several quarters, up 37%, more than $42 billion in revenue.
01:30 — Microsoft's been growing its cloud business in the range of 25%, 26%, 27% for the last several quarters. Stayed on that, and at this size, $59.3 billion, this is just an extraordinary achievement. But I would point out here that this is the first time in a very long time that AWS has grown more rapidly than Microsoft.
01:54 — ServiceNow up 24.5% to almost $4 billion in revenue. SAP, 24% growth, $7.2 billion. Got Workday in at 14%, $2.47 billion. So they're at about a $10 billion annualized run rate. Salesforce, 11% growth, but a very big $11.3 billion in revenue.
02:18 — OpenAI is not a publicly traded company, so it doesn't have publicly disclosed details There's been a lot of talk that its annualized run rate is about $70 billion. And it said earlier this year it expected enterprise revenue to make up about half of total business. And if we take that $70 billion number, that's about $35 billion for the enterprise business.
03:39 — We see that while models continue to be very important, what's really powering some customer moves here and these big growth numbers is the rise of platforms for AI. We've got a number of the Cloud Wars Top 10 companies making it very, very easy now for customers to build their own agents, extend their own applications.
04:24 — Oracle and Microsoft both have RPOs that are approaching $700 billion. So, enormous demand. This isn't even revenue yet. This is contracted business that hasn't yet been recognized as revenue. So this is still to come in the future, but it shows incredible demand, and it isn't just coming from OpenAI and Anthropic.

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In today's Cloud Wars AI Minute, I look at how Microsoft is using Work IQ to make AI agents faster, more efficient, and potentially less expensive to operate.
Highlights
00:10 — Today, the topic is going to be Work IQ, and we're actually starting to see Microsoft make very interesting moves inside of Work IQ. We've already seen AI agents doing a lot of really interesting things, specifically around the Graph API. But the big difference here is Microsoft is really looking to monetize the ability for them to be able to do preloaded context, and so this allows us to be able to optimize our token spend.
00:47 — It's already pre-calculated and just provided to you. And what we're starting to see is that, with Work IQ, you can get about an 80% reduction in the amount of tokens that it would require for you to go derive the same sort of information out of your Graph implementation of your data.
01:10 — This is really powerful for organizations who are looking to optimize their token spend. It also means that there's going to be a lot of power coming into Microsoft around the ability for them to monetize this in a way that could be quite effective.
01:57 — This is going to be a very interesting world as Microsoft leans into the ability to monetize all of this context that it has from its Graph. The other thing that's a little interesting about it as well is that it didn't offer it as yet another SKU.

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