Cloud Wars Live with Bob Evans

In today's Cloud Wars Minute, I explain why success in the AI Economy demands bold, uncompromising leadership from CEOs — and why many aren’t ready.

Highlights

00:03 — It’s been fascinating to see that recently, AI transformation has begun to hit hard at the CEO rank. Up until now, as we’ve all seen, there have been hundreds of thousands of job losses that have taken place in lower-level or mid-level jobs. And I think now we’re starting to see that the new victims of AI are going to be CEOs.

00:25 — And I think we can put those into three categories: those who are unable to see what’s happening and deal with it, those who are unwilling to acknowledge the reality of what’s changing, and then there’s those who are unseeing. They choose not to see what’s going around them, or they’re not willing to recognize just how serious it is.

01:15 — But I think what we’re really starting to see now, and I’ll offer some tangible examples here, is this is going to come down to be a real issue for CEOs, because companies that want to succeed in the AI Economy will not be able to do so unless they’ve got full, unbridled, uncompromising leadership and support for the business transformations being wrapped around AI.

02:30 — By every measure, Doug McMillon, the CEO of Walmart, has been a terrific CEO. But late last year, when he announced that he was going to step down as CEO, he said, “I just don’t think I’m the right person for this job. We’ve started a lot of AI changes and transformations. I’m not sure I’m the right person to finish those. We need somebody who’s faster.”

03:20 — Now, another group here is the kind I’m calling the unwilling, and they are the ones that are big on, “Well, let’s have a committee. Let’s form a SWAT team. We’ll see what the threats are to our company. We’ll see what we need to do, and we’ll give them six months or nine months or a year, and they’ll report.” And by then, their company is sort of over the cliff and is not going to be able to make it.

04:08 — Marc Benioff, the CEO of Salesforce, said AI has become a convenient scapegoat for everything. He said there are a lot of CEOs right now who are just saying whatever happens, good, bad, indifferent, it’s all due to AI. “We had to make a lot of layoffs — that’s because of AI. We had to stop doing this — we had to stop doing that — well, it’s all because of AI.” He said that’s a cop-out.

04:55 — So for business leaders, you can smell this in your company. You can feel it. Are we a company that is bullish and going after this thing with AI, or are we going to be one of these people who are unwilling, unseeing, and just not ready to jump in? There are brutal times coming for companies that are not willing to get into this. It starts with the CEO.

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In today's Cloud Wars Minute, I explore how governance gaps are slowing AI agent adoption in enterprises.

Highlights

00:05 —The role of AI agents in enterprise has advanced enormously in recent months, evolving from passive Q&A bots to systems that can take real actions in production environments. This is things like managing finances or accessing confidential patient data for healthcare organizations.

00:23 — However, a major hurdle often remains, and that's compliance. In many cases, audit and risk teams are reluctant to endorse these new capabilities because it's difficult to prove what an agent has done, which policies were in effect, and whether those policies were actually enforced.

00:45 — Panoptic Systems is a Mississippi-based firm developing runtime governance infrastructure for AI agents. Now, the team there recognized early on that as businesses deploy agents capable of taking these significant actions within production environments, a crucial missing layer of the technology stack was deterministic infrastructure-level governance that provided audit-grade evidence.

01:36 — Panopticore offers four possible outcomes for agent actions: allow, warn, block, or require human approval. Every decision is recorded in a cryptographically signed audit trail that can be verified offline by any internal auditor or third party.

02:28 — Panopticore delivers the controls and evidence that compliance teams, auditors, and often insurers need before agents can move from pilot to production. In simple terms, this technology is unblocking agents that are stuck in limbo.

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In today’s Cloud Wars Minute, I analyze Q4 performance to reveal who’s truly leading in cloud growth right now.

Highlights

00:03 — We're just a couple weeks away from getting Q1 results of the hyperscalers and some other companies in the Cloud Wars Top 10, I wanted to take a look at these world-shaping companies. Let's start off by taking a quick look back at Q4 and some numbers for Google Cloud, Microsoft, and AWS.

00:34 — I'm not including Oracle in this hyperscaler comparison because it's on a different financial reporting schedule, and I recently covered Oracle's most recent financial results in detail. So if we compare the Q4 growth rates for Google Cloud, Microsoft, and AWS: 48%, 26%, 24%. Now some people say, “Oh, that's not fair. That's not legit. Google Cloud is so much smaller.”

01:01 — Let's look: $17.7 billion for Google Cloud, $51.3 billion for Microsoft, $35.6 for AWS. So AWS is about twice as big as Google Cloud, and relative to Microsoft, Microsoft is three times bigger than Google Cloud. Riddle me this: how then, if you look at Q4 cloud and AI revenue versus Q3, Google Cloud came up with more revenue — more incremental Q4 over Q3 revenue — $2.5 billion versus $2.4?

02:23 — Yet AWS came up with more — significantly more — revenue Q4 over Q3 than Microsoft did: $2.6 billion versus $2.4. Now what does that mean? Well, it could be a temporary blip. It could be an anomaly. I think all of these things are valid. They all are pointing toward bets that customers are making about who is the company best equipped to take my company into the AI future.

03:49 — Google Cloud came up with almost as much as AWS. And to me, that just says Google Cloud is the hot company right now. So let me wrap up here with an outlook for Q1. I think both Google Cloud and Microsoft say that they will be releasing their financial results for Q1 on April 29. I think we're going to see Google Cloud report a growth rate of 44%, Microsoft 25%, and AWS 23%.

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Highlights

00:09 — Microsoft’s global investments continue to grow. Latest news is the company plans to invest $10 billion into Japan over the next three years to build out AI infrastructure, improve cyber resilience, and train a million engineers and developers by 2030.

00:28 — Our key partnerships include internet infrastructure provider Secura Internet, whose share price rose over 20% following the announcement, and SoftBank, already a major player in the AI revolution. Now, thanks to Secura Internet’s data infrastructure, the data used to develop various AI systems, including domestic large language models, will be processed in Japan.

00:57 — Now, in terms of training, Microsoft is also partnered with five other Japanese IT firms, including NTT Data Corp, NEC, Fujitsu, and Hitachi, to deliver this ambitious target. Now, the two-point focus here on both infrastructure and training is becoming a common strategy for companies building the next generation of AI systems.

01:22 — However, instead of solely focusing on the domestic market, Microsoft is continuing its global investment drive by enabling in-country training, leveraging the incredible skills base already available within existing organizations. Now, let’s not overlook the importance of data sovereignty, either.

01:41 — It’s increasingly important to adhere to the laws governing where data resides, and these laws are only becoming more stringent. Not only is Microsoft future-proofing itself, it’s also cultivating the next generation of Azure customers and AI-native enterprises aligned with its platforms.

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In today's Cloud Wars Minute, I break down OpenAI’s massive $122 billion funding round and what it means for the future of AI infrastructure.

Highlights

00:04 — OpenAI has completed its latest funding round with $122 billion in committed capital. The company explained the reasoning behind such a massive investment by highlighting that after reaching a billion dollars in revenue in its first year, it's now generating $2 billion in revenue per month, more than 40% of which is driven by the company's enterprise products.

00:54 — So what will it do with all of this funding? Well, the answer to that is a lot, but for the purposes of this minute, I'm going to dig into its core goals. Now, one of the major expansion areas is in infrastructure, as demand for AI systems is increasing.

01:13 — OpenAI recognizes that no single architecture can meet the demands of this diverse range of needs and expectations. So to that end, the company is building a broader infrastructure portfolio that incorporates cloud services, chips, and design partners.

01:43 — And then there's the AI Super App. OpenAI said in a blog post, our Super App will bring together ChatGPT, Codex, browsing, and our broader agentic capabilities into one agent-first experience.

01:58 — This is not just product simplification, it is a distribution and deployment strategy. Adding the capital being deployed today is helping build the infrastructure layer for intelligence itself.

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