Measuring direct ROI from AI investments is extremely difficult because efficiency gains get absorbed into other high-value activities rather than translating to headcount reductions.

37:40uh and you're able to turn that from uh 8 hours of work into 2 hours of work, you're able to now do that not only with more precision, cuz you can put an additional layer of nuance into those forecasts, but you're just able to have your folks do other stuff. There's clear ROI there. If you're able to take marketing QA from 2 weeks to 2 days, like there's so many examples of that um

38:03that we see. And and the way we've done that again is by pairing the business folks with the AI engineers. The the second thing I think that >> Are you actually seeing that today? Because Alex Karp came on CNBC or CNN and and said like, "No, the the ROI question is still there." Like, to to validate what you said, to be clear. Outside of coding and customer support

38:23with the greatest of respect, I think anyone who runs a budget in a large enterprise state would say, "Yes, it's still not material at best." >> I think it's just hard to know. Like, these things are just hard to quantify and so you do have to be a bit top-down um and belief-based about it, right? I I think three examples I just gave there. Assume there are dozens of more of

38:44those. The natural question is, "Okay, great. Like, how many of those people can I take out of my organization so that I get the cost back and that flows through to the bottom line or I can put it into other things?" But formulaically doing that is really hard cuz guess what? The The 8 hours of value that was created or the 8 hours of excess time gets filled with some other

39:04activity, which is also like presumably high value. And maybe before wouldn't have got done to or wouldn't have been done to a level of precision. So, it's just very hard. So, I think the way companies ultimately have to extract AI efficiency, at least from like a pure OPEX perspective, is just in your target setting, hold the constraints tighter. Like, if we really believe that AI is making our employees 10% or 20% or 30%

39:28more efficient, then next year we should just not increase head count. Or we should increase it by 2% instead of 10% or we should decrease it by 5% and say, "You all should be getting more done with less." And here are all these sub examples of of people doing that. But drawing the direct line between I transform this process and therefore like I need two less operations analysts.

39:50>> is is really tough to do. So, I do think there's ROI there, but to be able to like precisely quantify it is is challenging. >> How do you think about effective budgeting then having been through what you've been through with this kind of blowing through it in 4 months with the difficulty of budgeting and us both acknowledging that? >> Well, I I think what you have to do is

40:07you you have to um you have to create combined pools of budgets and then let the people that you trust allocate where they see a higher ROI. So, if you're talking about, you know, our our CTO, I think it'd be totally reasonable for Dara to say, you know, your your head count budget is X, our compute budget is Y. Just add X and Y together and then spend it as you see fit. And