The Exchanges

Q Let me say taking on, right? Not replacing, but saying, hey, like if we had these 5000 experts, maybe now we can have 20,000 if we hire quote unquote 15,000 AI.

A Yeah, look, you, you already start, I think we're early in it, but you're already starting to see this where it's a, I think about it like a glide path, right? Where in the, in the early days you might have the humans doing a hundred percent of the work, and then over time you start to have the model maybe suggest what the person might want to pick or, or come up with ideas in a sort of co-pilot fashion. And so you've sort of got the human in the driver's seat, the AI being there as a sort of an assist. And then you move to the next phase where you've probably put the AI in the driver's seat, and there's some, still some level of human oversight that's checking that, that's quality controlling, that's handling the more sort of extreme circumstances. And then at some point you get to a point where the, you're confident enough in the AI and you're able to move the human completely out and move them onto other more complicated or more messy activities. And that glide path is just going to sort of Basically work its way through every process, and there's things that are easier to move through that process, and then others that will be, um, take longer to fall, but I think ultimately everything is going to follow some version of that trajectory.

AI assessment note: “I think about it like a glide path, right?”

Q not everywhere, but in many places is about as good as it's ever been. And I think that means companies probably, you know, can benefit tremendously from gaining technology That will increase the average employee's productivity and, and adeptiveness and, and, um, subject matter expertise in a way that, you know, might be difficult to hire for at this moment. Am I reading that right or is that completely off?

A No, I think that's right. There's sort of two things going on simultaneously. One is I think we've seen huge shifts in the global talent markets, both sort of skills and high quality talent has become much more global than I think companies have hysterically thought about it. There's a lot more people that are moving into sort of fractional or freelance work, and that companies are still thinking about You know, hiring full-time employees within 20 miles of their office or whatever is missing out on an increasingly huge percentage of the overall talent pool. And so the companies that are rethinking the talent strategy and how they access talent are getting, um, really significant advantages there. And then the second is, is being able to leverage these tech AI technologies to really democratize knowledge and expertise and the ability, you know, even if you go back to that investment case, the ability to bring in A relatively junior untrained staff member and wrap them in an Ironman suit that gives them the expertise and knowledge of, you know, a career long professional is really extraordinary. And you're seeing that in sort of high talent industries like this, but also dealing with the sort of aging knowledge transfer of call centers, all sorts of, um, expertise that are sort of moving out of the workforce that companies don't know how to replace. These technologies provide fi…

AI assessment note: “No, I think that's right. There's sort of two things going on simultaneously.”

Q Right. And so can you talk about a few, let's say concrete examples that you've worked on, uh, that you can share exactly how this works for a company that's looking to integrate it?

A Yeah. Um, one of them, the sort of really interesting use cases that we've been going through recently is working with, um, one of the sort of top tier investment managers where they obviously, um, are investing billions of dollars of capital around the world. They have a very sort of high talent, expensive cost base, and they're looking at saying, how can we improve the throughput of this sort of very profitable enterprise? And one of the ways we're looking at that is saying, Look, they've got this huge body of knowledge that they've built up over decades of investing, all the investments they passed on. How do they take that knowledge and actually build a sort of super brain that consumes all that knowledge over decades of work and empowers the first year analyst to be able to access all that knowledge and analysis and apply it to a new deal or apply it to a new opportunity. And so you're not talking just here about efficiency gains. You're talking about a fairly transformative experience where you can basically take an inexperienced first-year analyst and give them the power of someone with decades of experience and hundreds of deals under their belt, um, and scale that globally. And so these are one of the, this is a really interesting, exciting use case that's sort of been in progress over the last few months that's really transformative. This is not just five, 10% better …

AI assessment note: “one of the sort of really interesting use cases that we've been going through”

Q So your view is that the value really is going to be unlocked in enterprise before consumer. Am I reading that right?

A Yeah, look, I think consumers are already benefiting from these technologies. I mean, I don't, I can't even go to the fruit shop without someone talking to me about how they're using ChatGPT to do something here and there. Um, I think the business model around that is sort of much more unclear in the same way that, you know, sort of advertising really drove the, the sort of search business. But I think consumers are already benefiting from these technologies and were probably the first to adopt and that enterprises are actually lagging a little bit in terms of how do they actually rewire the fabric of the organization using these technologies, but very early in the adoption cycle of that. Um, and companies just don't have the capabilities in house to go after a really ambitious transformation agenda.

AI assessment note: “consumers are already benefiting from these technologies and were probably the first to adopt”

Q but it's sort of going back to that original discussion around chat GPT, which is, that's a demo that sort of shows the capabilities and the rest of the, um, Industry and, you know, in AI and beyond is starting to find ways to apply that technology in intriguing ways. So can you talk a little bit about how AI is starting to spread today beyond that chatbot use case?

A Yeah, look, I think it's interesting that the release of ChatGPT sort of helped in some ways and hurt in others. I think the way it helped is really spurring a huge amount of imagination around what might be possible for these technologies and really getting boards and executive teams thinking about what might be possible. The way it hurt is I think it sort of overrepresented how mature these technologies are and how ready they are for enterprise applications. And as you said, Really shaped people's perception around what AI really is, which is only just sort of one form factor and imagination. And so I, to me, you sort of got to think about a much more holistically. And I think we're starting to see that with some of these multimodal interfaces where you can use video to sort of film the surrounding around you and start to interact and ask questions. And you're engaging in multiple modalities simultaneously, which is much more natural for humans. It's the same way you and I are going back and communicating and seeing each other and interacting with the world around each other. So I think these sort of multimodalities, I think the next frontier of that is going to be AI agents, agents that rather than just talk to you and go back and forth and chat, can actually go do work on your behalf, can take down a complex problem, plan out the work that it wants to go do and execute beyo…

AI assessment note: “the next frontier of that is going to be AI agents, agents that rather than just talk”

Q is that happening already? I mean, I know that you're working with companies to put AI into their operations, right? So is that agent based? Does it look more like the Apple intelligence example where it sort of is aware of what's going on and give smart suggestions? I mean, talk a little bit about how companies are integrating this into their operations today and what you've seen so far.

A Yeah, I'd say most of the use cases that end up people start with is much more on the efficiency side of things. It's like, okay, can we take, um, something and reduce the cost of that by 50%? Or can we take an employee and make them 50% more productive? And you're seeing that with co-pilots and all sorts of technologies. I don't think you sort of broadly speaking, you're seeing companies fundamentally rethink how their business might exist in a sort of AI first world. And I think we're going to start seeing The first round of startups that are sort of AI native that are really going after that from, from day one. And you'll see a real divergence in outcomes in sort of more traditional enterprises, those that actually cross this chasm and make that transformation. And that those that sit on the sidelines, I think are really going to be left behind.

AI assessment note: “most of the use cases that end up people start with is much more on the efficiency side”