Rebecca Hinds: prediction

Transcript context

…Yeah, so basically the key is if you're leading an organization, you got to tell who are the good AI users and who are the bot ********. And you're going to want to take steps to retain your top performers. You need to both use your AI detector to know who's using AI, but then also you need like a quality score to know who's actually using it effectively. And those people that are using it a lot, but using it effectively are ones that you're at risk of losing if you don't level up your game in one way or another, which could be better AI tools for them, could be better comp for them, perhaps. The ones on the other end that are just passing off AI work that they can't defend, probably in the end, you're going to have to make your peace with this is part of ways with these people is going to be the cost of transformation. How do you see people telling the difference? And do you see on the upside, obviously in deep in the AI bubble, I'm not this central in the AI bubble, but we've got all these stories of basically sports star, pop star incomes for top end ML researchers. I don't expect that is happening in quite such an extreme way in enterprises. But are we seeing like retention plays where people are getting like meaningfully rewarded in terms of comp if they are really on the cutting edge of helping their organization with AI transformation, if only in terms of embodying it and bringing it to their own role in an elite way. I love this question. No, not in a meaningful way. Should they? Yes. And this is not new, right? My colleague Rob Cross, who has been an inspiration for me for many years, some of his research shows that high performing organizations, they're up to 5.5 times more likely than lower effective ones, less effective ones in measuring and rewarding effective collaboration. The great organizations do this. They build some sort of measurement. It looks different for every organization. Sometimes it's tied to pay, sometimes it's more informal. But fundamentally, the most successful organizations, the most enduring organizations, they do something to reward the collective and not just the individual. I think that could not be more important with AI when we're starting to see this tragedy of the commons, hyper focus on individual productivity in a way that's not translating. I'm seeing it in bits and spurts is one example where they take something like a hackathon or an agentathon and they think very carefully about what are we going to incentivize. And they're not just giving prizes for the biggest business impact as most organizations do. They also give prizes for improvement, best before and after prompt. They give prizes for co-creation feedback, peer feedback, not just are you using the technology to drive your individual productivity gains, but are you creating value together? Those types of things we're seeing in effective organizations, but we're not seeing it at scale in a way that I think we should. And again, if I think 10 steps ahead, if you do have a context graph, if you do have an enterprise graph, well, it can help you make that determination because it will know where value has been created and it can start to give you recommendations and we see it in the data where, A large portion of employees are saying already their organizations are using AI to inform performance management, hiring and firing too. And when we ask, what is your expectation? Not surprisingly, it's even higher. I think we're, I hope, this is the hopeful part of me, I hope we see a world where not only can AI help us drive more objective, fair performance reviews when they've been riddled with biases for forever. And it can help us feed the performance evaluation with a bigger focus on the collective as opposed to the individual. That becomes incredibly exciting. And I think we're going to see it because we are already seeing bits and spurts of it. So tell me a little bit more about how you think leaders should approach this culture building. I have said that many times myself. it's got to be a cultural thing. And, you mentioned like, we need to see executives using AI. That's, I think, a very sensible starting point, but it's got to go farther than that. And in some cases, it's going to be in a pretty tough messaging environment, let's say, right? Because we do have quite a few rounds of layoffs from tech companies, mostly so far, being attributed to AI. Tell me if you think this will play out differently, but I suspect that we're going to see a pretty similar phenomenon extended to the rest of the economy and probably a few successive waves over the not too long of a time horizon. And certainly my sense is that public company CEOs feel like, geez, whether I like it or not, I'm under a lot of pressure to figure out how to make this stuff work. And I'm told that my competitors are gonna be dramatically cutting their costs and can I really compete if I don't? So they're gonna be presumably in a pretty tough spot where they're like, okay, here's me as the CEO using some prompts. At the same time though, we are cutting headcount by 10 to 20% or whatever. And we're going to work better together. And it seems like it's going to be a very tough messaging plane to land. What advice do you have for people that are facing this difficult challenge?…

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