The Exchanges

Q So can you give me an example of what happens when all this goes right?

A Oh, um, I actually have a really interesting example that one of our customers gave, gave us a couple of days ago. Um, large global financial services institution, non-US based, um, and they have to, and they have transactions that happen around the world with their customers that are flagged as being suspicious. As a regulated bank and with global know your customer anti-fraud and anti-money laundering rules, they have to evaluate each one of those. So originally, and, and they've got, and it's a bank that's come to get through acquisitions. They have a business they bought in Geography A, and they're on different systems with different repositories, and then the systems they have could be securities trading systems, cash machine systems, and, and all these are not tightly integrated because they're all kind of have been separate over time. So you basically have this issue that's flagged, and you have to have a human go investigate it. You know, what were their credit card transactions? Did they happen to buy a plane ticket and let's go to this place? And it would take a thousand people a full-time job to basically on a daily basis, go through these types of issues. And now they've created an agent where they were basically when an incident comes up, they score it based on this agent going, looking, oh my gosh, there's been, I'm, I'm making this up, but there was a cash deposi…

AI assessment note: “I actually have a really interesting example that one of our customers gave”

Q But you only have nine percent of people that are able to access it? What is, what's going on there?

A Well, I would say putting in a Cloudera commercial, that was the value proposition that we've talked about that our new products are designed to address. But, but taking a big step back, what AI needs to run is it needs, um, Accelerated compute, and it needs high fidelity data. The accelerated compute and the models are being deployed, but, but large corporations, their, their data estates are like a dusty old closet with things shoved in drawers. And in, in, in forums where people get together and talk about it, people are kind of embarrassed, but it turns everybody has the same issue. You know, we don't have a clean and pristine set of data across our various enterprise applications, but the AI The AI initiatives are rolling out, and so IT is running very quickly to try to maintain or improve the quality of the data. What our perspective has been, the answer can't be you take all that data and move it to the cloud so it can run very neatly on these cloud-based models, because then you lose kind of control over that enterprise context that you built over years, the transactions with your customers, the unique insights that you have, um, but you also can't wait A year or two for IT to get the data in shape and put it into, uh, one place so that you can bring the, basically the models to that data. So, so what we're trying to do is what we are doing actually through a combinatio…

AI assessment note: “large corporations, their, their data estates are like a dusty old closet”

Q So let me ask you, do, do all those divisions need to run through IT? So for instance, marketing, does marketing, which is using AI for content generation, need to run through IT? Because I imagine you're going to be more successful if IT is involved in some circumstances, but where's the balance?

A So The concern, especially as you move from generative to agentic AI, where you have autonomous agents moving through your systems doing stuff without checking back in with a human, I think it creates risks that we haven't got our hands around yet. So, um, I was, I was having a conversation today with one of the folks who was presenting at our conference, and that person runs IT Governance for a large global financial services organization, and that person said that right now the business is pushing back On IT based governance and regulation, but that actually once it's in place, governance will be an accelerant, not a detractor, because if you have a set of approved tools and processes, you can then allow the business to go to go deploy that. But I just, I, I'm very uncomfortable personally, and from a governance model perspective, from not having some oversight that exists For technology that are going to be deployed on inside an enterprise infrastructure. So I'm, that is my concern. And I know that there are, there are people in the organization who think I'm being overly cautious. Um, but, but that's how I'm thinking about it.

AI assessment note: “I'm very uncomfortable personally... from not having some oversight that exists”

Q Where do you believe those numbers? How should we read this study?

A Um, maybe it's also, so I think that a lot of things are tried and, and fail quickly. Um, and, and I think that it's also very hard for the business user right now, um, to To identify the use case that matters, and, and, and maybe an example of that is, it requires not just facility with the technology, but also real deep understanding of business, and historically, um, a lot of our IT folks have not been experts in the business, and our business folks have not been experts in the IT. So I think it takes a pretty unique individual right now to put those two things together, and a lot of the use cases I believe are being driven by, you know, business users who don't have as much technology experience, or IT users, Who don't have as much business experience driven by the urgency of, oh my gosh, we got to do something. And I think that's what we're seeing right now. The, we've got to do something. So we're going to run a prototype. And even if the report up to management is we ran through prototypes and they failed, that's still better than we didn't do anything.

AI assessment note: “I think that a lot of things are tried and, and fail quickly.”