Cloud Wars Live with Bob Evans

John Siefert sits down with Christopher Jones, Vice President of Ecosystems and Partner Alliances at T-Mobile, to explore why enterprise connectivity is becoming foundational to the AI Era. Jones explains how T-Mobile for Business is moving beyond the traditional perception of a telecommunications provider to become an infrastructure layer supporting distributed workforces, AI agents, enterprise applications, and data at the edge.

AI Runs on Connectivity

The Big Themes:

• Connectivity Underpins Enterprise AI: AI may dominate enterprise conversations, but Jones argues that connectivity remains the foundation that makes AI useful. Applications, agents, enterprise data, and mobile workforces all depend on networks capable of delivering reliable access wherever work happens. That makes connectivity increasingly important as AI pushes workloads and data beyond traditional office environments and toward the edge. T-Mobile for Business is positioning itself not simply as a telecommunications provider but as an underlying infrastructure layer supporting whatever technologies enterprises deploy today and tomorrow.
• Co-Creation Replaces Technology Silos: The conversation repeatedly returns to co-creation. T-Mobile doesn't want partners to build specifically into its solutions, nor does it necessarily want to embed itself deeply inside an SI's technology. Instead, Jones describes a co-sell and co-creation model in which different providers contribute their respective expertise toward a common customer outcome. An SI may own the application or industry solution while T-Mobile provides the connectivity that allows that solution to operate reliably across locations and devices. That distinction matters as enterprise architectures become more complicated. Rather than expecting one vendor to provide every component, customers can benefit from ecosystems that combine networking, applications, cloud, AI, consulting, and domain expertise while keeping each participant focused on what it does particularly well.
• Resilience Requires Multiple Paths: One example of T-Mobile's infrastructure strategy is SuperBroadband, which Jones describes as pairing its 5G network with Starlink in a managed connectivity solution. The objective is to provide two independent connectivity paths rather than leaving an organization dependent on one. T-Mobile's current materials describe SuperBroadband as integrating its 5G Advanced network with Starlink and supporting capabilities including failover and load balancing. This reinforces the broader message of the conversation: as organizations place more mission-critical workflows on cloud applications and AI systems, network resilience becomes inseparable from business resilience.

The Big Quote: “No one owns the whole solution. It's how do you bring together a variety of partners that have their own individual expertise [to] work together for the joint customer outcome.”

More from T-Mobile:

Learn more about T-Mobile for Business Advanced Network Solutions and T-Mobile SuperBroadband.

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In today's Cloud Wars Minute, I explain how AWS is combining custom silicon, enterprise applications, and agentic AI to drive its resurgence.

Highlights

00:02 — I wanted to talk about an interesting development at AWS, which over the past several quarters has been on a very nice upswing in its business, powered in part by their development of what is now a very large and extremely fast-growing custom chips business.

00:37 — That comes down to a billion-dollar chip deal that AWS has just secured with Synopsys, a chip designer that AWS has been working with closely over the last several years, as AWS has built what is now a custom silicon chip business that has an annualized run rate of $25 billion.

01:09 — This new deal between AWS and Synopsys calls for the creation of new chips that they say are “application-optimized solutions.” So, the incredible advances in the power and capability of silicon now being tied directly into helping enterprise applications run more quickly, more securely, more insightfully, and to handle the incredible volumes of data and transactions in the AI economy.

02:28 — And I think this is something that, as I mentioned, has been a huge part of the resurgence of AWS. Last quarter, ended June 30th, AWS's growth rate jumped to 37 percent, by far the highest it's had in several years. We'll see some new numbers from AWS coming out at the end of this month or early November for Q3.

03:41 — So, this demand for more speed, more power, more insight, more security for all of these, I think, comes along at a time when business customers are starting to say, “Yeah, I'm going to use a lot of agentic AI, but I'm also going to continue to use the enterprise applications that are such an integral part of my business and how I work and where I work.”

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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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In today's Cloud Wars Minute, I look at why Microsoft Work IQ could become increasingly valuable as enterprises deploy more specialized AI agents.

Highlights

00:12 — Microsoft's much-anticipated Work IQ is finally going into preview. Quick refresher: Work IQ is an intelligence layer that gives Copilot and AI agents context about how work happens across an organization.

00:27 — That understanding is grounded in business data from D365 and Power Platform. Cloud Wars CEO John Seifert has written up a great analysis of the launch and what it means for customers, which you can read now on CloudWars.com, but I wanted to take the opportunity to look at the wider implications of what Work IQ could potentially mean for the direction of the AI industry.

00:54 — Work IQ really demonstrates a shift in what it means to personalize AI. Up until now, Microsoft, like many other vendors, has talked about AI personalization in terms of your emails, your documents, your preferences. But, with Work IQ, there's a shift towards understanding the individual employee in the context of the organization.

01:23 — Work IQ is coming in at a point where the proliferation of agents has really become quite significant. We're way beyond general-purpose agents now, and we have specialized agents working across different areas like sales, finance, HR, etc. Increasingly, those agents need to coordinate.

01:42 — The question is whether agents can understand the shared organizational context well enough to coordinate with one another, and Work IQ is really enabling that shared understanding. And that links to my final point: the value of Work IQ could increase as Microsoft expands its agentic AI ecosystem.

02:14 — The more agents Microsoft introduces, and the more those agents need context to operate efficiently, the more valuable Work IQ could become as that intelligence layer underpinning them. And I think we could see that exact scenario play out in the companies using Work IQ as well. The more agents they deploy, the more valuable a shared intelligence layer will become.

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In today's Cloud Wars Minute, I unpack Sam Altman's comments on AI safety, security, and responsibility during his Dreamforce conversation with Mark Benioff.

Highlights

00:03 — I wanted to talk today a little bit about a discussion at Salesforce's recent Dreamforce event. It was a conversation with Salesforce CEO Mark Benioff and the CEO of OpenAI, Sam Altman, and they talked specifically about this whole notion of AI safety, AI security, responsibility, trust, and the recent disaster that OpenAI had when one of its models went rogue and attacked a Hugging Face server.

00:39 — Altman and Anthropic CEO Dario Amodei have become the leading proponents for, "Hey, let's slow down the whole industry." Let's slow down the whole industry while OpenAI gets its stuff together and moves forward. I've got a detailed, extensive article with a lot of verbatim comments from Altman that really do bear out the points I'm going to be making here.

01:35 — One of the big things here is that Altman just seems to be begging to be trusted. He says things like, "You should trust us to do the right thing because we want to do the right thing, and we know that the right thing to do is to do the right thing." I think you want to come in a little bit humble: "Hey, we made some mistakes. Here's what we're doing to correct it. We're going to redouble our efforts here, here, and here."

02:02 — Altman was more like saying, "Ah, you know..." It's almost like he's saying this happened to somebody else. He doesn't refer so much to OpenAI, but he said these big AI companies, and some of these big AI companies might now have more control, and some people are worried about what some of these AI companies might do. It was just a little bit surreal.

02:49 — And then he says, "Well, I'm disappointed in how it was framed." Now, I get to be disappointed. I've made a million mistakes, and I wish people hadn't always discovered them and pointed them out. But those were my mistakes, and I have to be responsible for them.

03:02 — And this was just totally the wrong note to hit, especially for enterprise customers. This whole thing about saying we always do the right thing, but he said now, in some cases, people won't do the right thing. He's talking about the whole industry here. So we always do the right thing, except when we don't do the right thing. It's hard to tell just what he meant.

04:54 — I don't think all this obfuscation and the fog that Altman was pumping out is going to help the case. I think that OpenAI needs to clean this up quickly. You know, spill on aisle six. We need the cleanup team over here. Anyway, check out this detailed article and the verbatim comments from Altman. I'll have that later this morning on CloudWars.com.

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In today's Cloud Wars Minute, I look at how Salesforce plans to unleash trapped data, make software do more of the work, and expand beyond its CRM roots.

Highlights

00:03 — Had some time to digest the big things that happened at Salesforce's recent Dreamforce event, and I wanted to share with you some thoughts of what I think are the five big takeaways from that big combination of Dreamforce, AI partnerships, and Salesforce moving in some new directions outside the traditional CRM space.

00:40 — The big promise that I took away from it was that it is going to unleash trapped data within Salesforce systems and other systems. This is a promise that business people have been hearing about, but not necessarily seeing delivered, for quite a long time.

02:02 — And Marc Benioff made a big promise about this: that this age of software doing a little bit but not quite enough, and forcing humans who want to get higher output to do more and more of that work to get the higher output, is going to be over.

02:38 — I think Salesforce is ready now, with the rise of AI, with some new technologies like AIforce, with some new partnerships I'm going to talk about, I think it's going to spread beyond the traditional CRM boundaries. It'll still, of course, be a major player in CRM, but I think it's going to move into some other areas as well.

04:38 — And finally, Mark Benioff's Q&A with OpenAI CEO Sam Altman was absolutely priceless. Altman's one of the creators of the "Let's Slow Things Down" idea and that whole model. And I think Benioff's careful but straightforward, very simple questions really forced Altman to describe in plain language what OpenAI intends to do.

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