Cloud Wars Live with Bob Evans

In today's Cloud Wars Minute, I examine how Google Cloud is using AI and unified solutions to radically accelerate enterprise modernization.
Highlights
00:03 — We know that on the road to AI transformation, tech modernization is a key element. Unfortunately, for a lot of organizations, the traditional approach to this has been very tactical, very point-solution-oriented, and talking about technologies, kind of disconnected from business cases, from ROI, from business outcomes.
00:27 — And that's left a lot of business leaders with that glazed look, where they're just dying to get out of the room and get out of that discussion. Google Cloud's made a fairly simple but highly effective step, I think, in fixing that. It's consolidated a lot of its products together — its migration and modernization products — into a simple solution.
01:00 — The significance of this is there's still some very deep, heavy-duty technology in there, but it's been packaged in a way that lets business leaders understand the significance. And it's also not just the packaging of it, but there's some new AI-driven technologies here that allow some of these complex processes, these complex steps that have to be taken for modernization, to be greatly collapsed in time.
02:02 — Over the past couple of years, it's taken multiple products that it has in a certain area, put them together in a single, unified, end-to-end solution so that customers have an easier time to consume those, to get value out of them, to drive toward the appropriate business outcomes, rather than having to evaluate every single point solution.
02:54 — And I think this is something its's going to see a lot of other providers move into: to try to have these comprehensive solutions for customers, get away from having customers be the general contractors pulling together lots of very detailed technical point solutions, and instead put together a suite that is a full portfolio that is oriented toward the business outcomes that the businesses have to have.

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In today's Cloud Wars AI Minute, I look at the tension between AI regulation, industry self-governance, and America’s determination to remain competitive in the global AI race.
Highlights
00:18 — Some regulatory things happening as the government in the U.S. started to take a look at AI in general. We had six of the CEOs of the major AI providers in the world really, went over to Washington and started talking about how they were going to do self-regulation. Now, the issue with this is going to be that that agreement has actually no penalties associated with it.
00:50 — So, if someone actually breaks the rules, doesn't mean that there's actually any penalties that are going along with this particular situation. And now, the other interesting part is that two of the six are now actually under FTC investigation over consumer risk, and so we have to really ask ourselves: Do we really believe that they're going to properly self-regulate?
01:54 — Now, the other thing is that there is a report that needs to be due to the Trump administration in 120 days. So, what I would tell you is, over the next 120 days, I would fully expect that we're going to get a lot of movement in this space on what are we going to do specifically around AI, which is now also being kind of formed on superintelligence.
02:18 — Now, I believe what they're trying to do here is say that AI governing maybe is not as necessary as superintelligence governing, and they're really kind of trying to draw a line in the sand on the difference between artificial intelligence and superintelligence. And so, I really think this is going to be interesting to see over the next few months what's going to happen in this space.

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In today's Cloud Wars AI Minute, I break down why ServiceNow and Microsoft are embracing open protocols as the AI Agent War shifts to the control layer.
Highlights
00:01 — What I want to talk about today is that we're actually seeing the Agent War moving up to the control layer. You're seeing that there's a new control layer that's becoming the core part of what everyone is fighting over in this space, and this is really where we're going to start seeing governance and control becoming the more important part as we continue to move forward.
00:55 — ServiceNow is building a layer that governs what agents do with it, and this is going to be shipped on the open protocol of MCP. But if we look over at Microsoft, which is building out Work IQ, it's going to make sure that it also exposes over MCP, A2A, and REST.
01:32 — It's actually leveraging the out-of-the-box available [protocols] that are basically industry standards at this point, and that's actually a really good sign for the way that things are going. And it also means that what we're also starting to see in this governance space reliance and integration starting to happen across all of these different layers.
02:17 — And I would fully expect that this is going to be a place that we need to keep a strong eye on as we continue to move forward. And, of course, here at Cloud Wars, we'll make sure that we continue to take a look at this particular space .

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In today's Cloud Wars Minute, I look at why SoftBank is turning to the bond market to finance its latest $10 billion OpenAI investment.
Highlights
00:03 — It's fair to say that we're at an interesting inflection point when it comes to how AI innovation is set to progress, what might constrain it, and where, eventually, lines may be drawn. However, that hasn't slowed planned investment in some of the biggest U.S. firms.
00:19 — Most recently, Japanese investment giant SoftBank has announced that, through the issuance of senior unsecured bonds, it will be borrowing over $11 billion to help fund its planned $10 billion investment in OpenAI. Now, $10 billion of the new bonds will be issued in U.S. dollars, with another 1 billion issued in euros.
00:41 — This is SoftBank's third tranche of its follow-on investment in OpenAI, with the $10 billion payment expected to close on October 1. It's a very significant amount, and if the bond sale is completed at this planned size, it will be the largest corporate bond deal by a non-financial company ever recorded in Asia Pacific and Japan.
01:03 — Now, quick note here: despite its name, SoftBank isn't a bank. It's primarily an investment holding company and tech investor. I think the interesting thing here is that SoftBank isn't just investing $10 billion of spare cash into OpenAI; it's borrowing billions from the bond market to help fund the investment.
01:27 — Effectively using debt to finance this continued relationship with OpenAI, at the very least, signals a significant level of confidence in the company.

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Key Takeaways
AI investments: Simms explains that a top priority for organizations currently is determining how to get value out of AI investments. He says an estimated 80% of AI initiatives aren't seeing the value that was anticipated, which begs the question: Are you choosing the wrong initiatives? Are you using the correct data? Have you defined the processes correctly? "All the underlying pillars that are required for these things to actually work and actually provide value, those need to be revisited and looked at," he says.
Data readiness: Data readiness is, in Simms' opinion, "the biggest single issue that's out there right now" as it relates to AI projects. He suggests that organizations need strong data governance and an "iterative approach" to ensure both structured and unstructured data are clean, organized, and ready to support AI systems and workflows at scale.
Adoption: Simms says his approach to AI adoption is different because he focuses on building the right organizational and process foundations first, rather than rushing to implement technology. He compares it to building a house, noting that "you don’t put on the shingles and the shutters and the paint before you actually build the foundation and the frame."
New roles defined by AI: Simms expects AI to create and reshape job titles and also create demand for expertise that helps organizations adopt, manage, and govern it. Specifically, he foresees roles focused on governance and engineering, as industries determine how to implement and maintain AI systems.

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