Enterprise AI ROI has climbed sharply, from roughly 5% a year ago to roughly 30% today depending on segment, as organizations move past experimentation toward solving concrete problem statements.

3:57it in, what do I need to do to curate it, cleanse it, prepare it, and all that. That's still a huge, huge challenge, right? And then protecting the data as well, as you mentioned. but then also I think it's, We're seeing a, an uplift, I think, in ROI, right? So I think a year ago, NVIDIA has done some independent studies and others as well, and we were at the five percent range for ROI.

4:17I think we're now moving up to the 30% range, depending on which segment you're looking at. But as a generality, we're seeing a, big uptick, I think, in, in true ROI return, implementing AI into the organizations. So that process of understanding where to apply AI, I think, has shifted from experimentation and for the sake of AI to now let's look at problem statements and figure out how does AI agentic systems solve

4:45for those problems, how can we overlay AI, and that's where we're finding enterprise specifically is making a lot of, I think progress in terms of that, value add. The places where I've seen people be very, successful is prioritization, right? And that continues to be a challenge, because, if you take a room full of 100 people They will, come up with 100 different amazing ideas how AI can transform a bank or a hospital.

5:12Sure. But really being intentional and saying, "I'm gonna pick four or five projects, and we are going to go deep," and actually go see it end to end, like the workflow, measure the productivity, how is it actually being useful. Because there's a lot of projects start with a lot of enthusiasm, and then y- there has to be an intentionality towards that. And so the companies that I feel

5:36are very successful are, who are doing it in a more intentional way. The second thing that I feel is a consistent theme is, like I said, there's a very subtle difference between optimizing a process and reimagining a process. Once you actually put an effort into reimagining a process and you've drawn the workflows, the ROI, and you have-- you've done-- assuming you've done it well, the ROI is just so obvious, and then

6:05the adoption just goes, you know- Sure … skyrocket-rockets across the organization. And then the third thing, I think a lot of times when customers have to, and or organizations have a choice whether they optimize their internal processes or they try and, bring AI to their customers. Try to do a lot, together. but again, it comes back to intentionality about what processes, what are the times that you're trying to fix.