00:00As we continue to get these teams in size, part of what we want to do is then how do
00:03we make everybody more efficient?
00:05And a big push for us has been how are we leveraging AI on both the front end to improve
00:10that customer experience
00:11and on the back end to, for existing team members, you know, continue to help improve sort of efficiency in
00:17our ways of working.
00:19Customer-facing AI-powered apps help Wayfair shoppers navigate through millions of products to find items that meet their needs.
00:26One of the tools I like to play with on the website is called the Discover tab.
00:31Basically, you can, you know, type in what kind of room you're looking for and it populates.
00:36AI generates an image for you, but that image is all populated with products from our catalog.
00:41You can just buy them right then.
00:43The company is also embedding AI into many of its internal processes.
00:47No surprise, since it's been on the leading edge of technology quite literally since its inception.
00:53We actually got our start as entrepreneurs right out of Cornell where we were engineering students in 1995, which is
01:00basically the beginning of the commercial internet.
01:01And so we've seen a lot of technology changes ranging from the internet to cloud to mobile.
01:06AI looks to be the potential of larger than the internet to me.
01:09We think it's really important for all of our employees to have access to AI tools.
01:13We really want people to experiment.
01:15In the finance team, everybody has some level of access to AI technology.
01:20We've used some AI-specific tools that are being developed for finance that are helping with things like the clothes
01:25and, you know, doing that in a more efficient way.
01:28I think we use it in, you know, sometimes a little bit more creative ways around, you know, for example,
01:33when you're thinking about an earnings call, how might something be received?
01:37What might be a back and forth?
01:38You can play with it.
01:39Do you use it at all for, like, when you're thinking about where to put a store?
01:42We were building with it in partnership with the real estate team was mapping out what we call different furniture
01:49nodes around the U.S.
01:50So areas where you have a cluster of furniture stores.
01:53And that's actually very, you know, that's something that an LLM can do quite easily.
01:57Right.
01:57Historically, you maybe would have used a broker to do that.
02:00We also have a third-party tool that we use that provides a lot of data around stores that is
02:05AI-enabled and that allows us to think about traffic flows and traffic patterns in and out of a shopping
02:10center, for example, to understand where, you know, might the traffic be coming from.
02:14And then you can use, you know, AI to sort of simulate what another store within that area might look
02:20like.
02:20It's quite fun.
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