Bret Taylor: prediction

Transcript context

…Well, that gets to one of the biggest conundrums in Silicon Valley right now is what will the shape of AI productivity be? I think there's this strong sense that the AI has gotten really good, and it should change the composition of companies and it should change the hiring plans somewhat. You've seen this in some corners. Block announced their 45%, 50% AI layoff yesterday, and you have some companies not growing as quickly. At the same time in coding, you see a lot of AI benefits. You can argue that either way. You can say, "Engineers have gotten much more productive, therefore, we should hire fewer engineers." Or you could say, "Engineers have gotten much more productive. The ROI on a single engineer is way higher. We now have super engineers that we can hire, therefore, we should hire way more of them because there isn't a fixed amount of stuff for Stripe or any other company to do." Then the AI productivity story in other roles is just a bit less clear because, as we've discussed, AI is uniquely well-suited to coding. What do you make of just... How does the AI productivity show up? I feel like every company in Silicon Valley is trying to figure this out right now. Well, first, I think I'll go back to my why I believe in applied AI. I think the atomic unit of productivity in AI is a process, not a person. I don't think AI... I don't know if you have an assistant, but if you do, he or she might help you prepare for a podcast, might help you prepare for a meeting, he or she might also get you a cup of coffee. AI will be really good at the first two, but quite poor at the last one. No matter of AGI, short of robotics, will get you a cup of coffee. I think it's wrong to think about AI as replacing people. In addition to being inhumane, it's just nonsensical because AI operates in the world of digital technologies. I think if you go to an example of even a mundane process in your business, like onboarding a new supplier, think about all the departments and people involved in that. There's a legal department to do a contract. There's some finance department procurement to negotiate the relationship. You probably have IT that's involved to onboard them into your core systems. Then there's usually a business that's sponsoring it. Fairly mundane, happens all the time. Let's just say you tracked what is the median amount of time it takes to onboard a new supplier, and it was 17 days, just for argument's sake. I bet you could say as a CEO of a company, I want to use AI to optimize that process and make it 17 hours or one day. You could go through, and if you had a product manager on that and optimize every part of it, I bet you could achieve that. But the hard part isn't a person's job. It's actually all the systems and people in between it. I think part of the reason why I think it's been slow to get the productivity enhancement is we ship our org charts as companies naturally. That's the natural state. There's not usually a person responsible for that process. There's the legal team responsible for the contract, there's the procurement team. I think actually we will end up reimagining our companies with the benefit of AI, will we actually think of our companies as a collection of processes, have people responsible them with KPIs who can apply AI. I think I bring it up just because that's my theory of the world. of AI, will we actually think of our companies as a collection of processes, have people responsible them with KPIs who can apply AI. I think I bring it up just because that's my theory of the world. I might be wrong, I might be right, but I'm not sure companies are set up to essentially absorb the benefits of AI efficiently right now, and we need to do that to really do so. But the bigger point, I think, is that there's the paradox of, well, you want more software engineers. But on top of that, most of the world isn't just digital technology. I think a lot of the people in the AGI community have only ever worked at a research lab or a software company. You look around, you're like, "Wow, AI is going to do all of this." As they walk by the flower shop and get their coffee at the coffee shop, and you think about the local flower shop, if you took all the AI in the world and gave it to that, you gave it super intelligence, how much would it impact the flower shop's operations? Maybe a little. I mean, I'm sure it would help, don't get me wrong, but someone's still clipping the ends of the stems of the flowers, arranging the bouquets, and thanking you on your way out the door, and congratulating you for your daughter's wedding, or whatever it is. I think if you think about what parts of the economy can absorb intelligence really efficiently, it's certainly software, and we're seeing that already. Finance seems particularly meaningful here because so much of finance today is just digital information. Everything's in digital systems now, not even just crypto. I mean, just everything's in digital ledgers everywhere. It still doesn't touch a wet lab. It still can't do a clinical trial. You still need to get a crate from this country to that country on a ship. As a consequence, I think I'm not sure we'll see the productivity enhancement we see in software in every sector as quickly. Then on top of that, I think companies need to stop just giving Copilot to every employee and be like, "We're AI now," and start to think about from first principles, what are the parts of your business that have a lot of digital workflows? Where can AI have a real big impact? How do you actually set up your company to actually have someone accountable to drive that? That feels like a real big change management opportunity that most companies haven't done.…

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