OK.

Right.

And, you know, I don't think any of us would argue that humans shouldn't do that.

Now, of course, there is the efficiency conversation.

Of course, there is a conversation about whether humans are more accurate than AI, et cetera, et cetera.

But I think we.

we're at a point at which we can begin to measure those things, right? AI makes decision, human makes decision, which one is more accurate more frequently, which one is more appropriately accurate for a given situation, again, is a slightly different matter as it relates to judgment.

So how does one go about even evaluating that?

Sure.

And at some point, you know, we have to spend some long form time as opposed to short term kind of posting.

Right.

We have to spend long form time.

because these issues are complex and you have to unravel them.

The answer to AI isn't no AI.

That's not a thing, y'all.

What should a small business or startup selling into a company like SAS understand about how large organizations evaluate partners, particularly in this macroeconomic environment, especially on things around data transformation and any other, any partnership obviously requires a high degree of trust, but you know, something that's sensitive and trust forward as data analytics or insights or measurement or things of that nature.

Okay.

Right.

Because we have to maintain some measure of control and accountability.

You go from 10,000 to 100,000 to a million.

And now you just have, you know, agents running around making decisions on our behalf.

Like, is is that the world that we want to inherit? Again, I go back to for what purpose, to what end and for whom might it fail? We have to be able to answer those questions.

And if we can't answer those questions, we should probably.

But therefore, when we start looking at those organization enterprises out there, you know, what are the things they need to do today, right, right now, to start getting ready for six months from now?

Yeah.

And so we orient around the use case, and we show how the use case then is, is, is a function of the models and agents that are, are driving them.

And we put all of that capability on a dashboard, effectively, that puts executives like me in a position to know how we're doing.

So you look at that [laughs] upper left corner-

Mm

... what AI is doing today, particularly gen AI, is helping us reconsider org design, is helping us reconsider job descriptions.

And so what sort of impacts does that have then on the way that the, uh, work flows through the organization? And then the fourth pillar would be, uh, culture.

And this one, quite frankly, is often overlooked.