Nathan Labenz: prediction

Transcript context

…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? This is an area where we do know so much about what works. Unfortunately, we don't see it implemented. And employees can call ******** from a mile away. And if they see a talk track that's different from what's happening in practice, that does not instill confidence and you start to see a whole bunch of this symbolic use of the technology. Transparency is so important right now for so many reasons, but in particular to understand the why. The why behind organizational changes in either direction, the why helps people understand whether they're willing to believe in it and willing to commit to it in a reasonable way. Now, what I'm seeing overwhelmingly is performative theater at every level of the organization, but in particular with executives. And I spend a lot of time with executives and the amount of conversations I've been part of where one executive decides that they're going to cut 15% of headcount. And then there's a conversation around, should it be 16%, should it be 14%? And there's this very, you know, very disturbing narrative that there's a one-size-fits-all for every organization. There is not, and we've seen efforts to change organizations and dismantle hierarchy, flatten the org chart time and time again. Often they don't work because they're short term, perceived short term fixes that don't help the underlying problem. This is an organizational design transformation in its fullest sense. having an understanding of what is your culture, what sorts of behaviors does your culture embody, does it reward, does it punish? That is very important right now. And articulating that to employees in the context of AI as well. What is AI in relation to humans is very important. And what we see overwhelmingly is in these organizations, and we talk about in the report, employees are significantly more likely in these transformative organizations to view AI as a teammate and how they interact with it. But not as an employee on the same level as them, because that becomes dangerous when we're starting to deflect blame on the AI tool. The blame, the onus, the responsibility rests with humans. But ideally, the organization is positioning AI both psychologically and in the tools and technologies they invest in as a teammate in a way that employees can grok, how might I interact with this technology? How might I start to delegate work to? It's a multi, multifaceted problem. But the answer is not to make cuts or make sweeping changes without understanding the impact of those changes on a smaller level. And I think that's why coinciding with these these layoffs, these cuts is a lot of regret because we don't fully understand what employees do. And we've seen this in customer service cases where you cut the human agents, you realize, wow, those human agents did a really important work in building long-term relationships with customers. You then bring them back.…

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