00:00I'm taking a look at the notes you sent over to our producers. It seems like you're arguing that there is a bubble here that's being developed in AI, but it's in a specific part of the industry. Walk us through that.
00:11Yeah, well, thank you for having me. So when it comes to the bubble concerns, what we're seeing is that there's a ton of investment and a ton of excitement, particularly starting at the infrastructure layer.
00:23There's trillions of dollars being spent at the infrastructure layer, and that's all investment in what the future of AI is going to be.
00:30And people think this is a bubble in many ways because it's really early to say what's going to happen.
00:35On the flip side, all of this investment will start to pan out in the application layer with real AI, particularly AI agents that are delivering value for businesses and their consumers, just like we're doing here at Forethought.
00:47And we're really excited about a lot of the milestones that we're achieving.
00:52Well, that's really interesting, Dion, because, you know, you hear a lot of people saying, I want to invest in the picks and shovels.
00:58I want to invest in the infrastructure and the things that are, you know, going to power the AI build out.
01:04But what you're saying is that when it comes to this build out, that it's possible that, you know, we're building all these different data centers and all these things that go along with that.
01:11And potentially there isn't necessarily going to be a use case there.
01:16I think the build out is real, and that's where a lot of money is.
01:20In terms of the use case, though, I actually think there are very many real use cases.
01:25So at Forethought, we develop AI agents for the customer experience, customer service particularly.
01:30This means helping businesses serve their consumers better.
01:33And we've actually just announced $1 billion in ROI delivered to our customers, and that's across lower costs, that's across faster resolutions, and across better retention, customer loyalty, and consumer experiences.
01:46So I actually think some of these use cases are truly here and are truly starting to make an impact on real consumers.
01:53But where you're investing, it really matters.
01:55It really depends on what part of the stack you're focused on.
01:58Well, give us a sampling of the types of clients that you're working with and, you know, whether there seems to be one particular industry where it seems like the ROI is more tangible.
02:10I think it's actually going to be across the stack.
02:13So we work with e-commerce companies like fitness brand Cotopaxi.
02:18We work with Lime Scooters.
02:19We work with folks like Grammarly, who are AI companies themselves, all the way over to folks like WordPress, Airtable, and Datadog.
02:26And so many of these companies, high-growth scalers in their own right, whether they're pre-IPO, post-IPO, or scaling even beyond, they're all leveraging forethought AI agents to develop and deliver better customer experiences for their consumers.
02:41And so while we're all thinking about, hey, where is this money going to go, the whole point is, can AI deliver for those billions and billions of people every single day who rely on these products and rely on these services?
02:53Well, a simple question here.
02:55Talk to us about how, you know, the modern-day AI agents are different from some of the, you know, chat windows that would pop up when you would go to a travel agency site or something along those lines and, you know, people typically bat them away.
03:09What is the user experience like for some of these AI agents that you're developing for your clients?
03:15Agreed. And we've all had the really bad experience dealing with a clunky decision-tree-based chatbot that's really, at the end of the day, very rules-based.
03:25And so what I would say is the two big distinctions we're seeing from this AI era in the consumer experience, the first is intelligence and the second is action.
03:32So when I say intelligence, a lot of the old AI chatbots from the past decade, two decades or so, have all been programmed using rules, keywords, and what we ultimately call decision trees.
03:43In many ways, these were more artificial than they were intelligent.
03:46Nowadays, leveraging large language models, leveraging the state-of-the-art technology here, you're getting AI that can reason, can plan, can understand humans, and really take action.
03:55And that brings me to my second point, which is action.
03:58It's not just about answering questions like, you know, tell me about your refund policy.
04:03It's about, hey, can you actually go and issue this refund for me, find out where my order is, figure out or troubleshoot this database for me, and ultimately solve the problem for me as a consumer.
04:13And this is night and day what AI is capable of doing now compared to what it was doing, say, 10 years ago.
Comments