The Future of Retail is A.I.

Summary

Podcast Summary: What Next TBD – “The Future of Retail is A.I.”

Slate Podcasts | Host: Lizzie O'Leary
Guest: Miya Sato (The Verge)
Date: February 22, 2026

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Episode Overview

This episode explores the sweeping transformation of the retail industry through artificial intelligence (AI). Host Lizzie O’Leary is joined by Miya Sato, a reporter for The Verge, who recently attended the National Retail Federation’s annual conference. Their discussion unpacks not just how retailers are integrating AI—from holographic greeters to shoplifting prevention systems—but also the implications for consumers, workers, and privacy. The episode asks: Is AI truly making shopping better, or are we barreling toward a future where “AI slop” dominates commerce for the sake of scale?

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Key Discussion Points and Insights

Experiencing AI in the Flesh: Meet “Mike” the Hologram

• [00:36–01:29] Miya Sato recounts encountering “Mike”—an AI-powered hologram in a glass tube that interacts with attendees at the retail conference.
  • Mike is powered by ChatGPT and intended as a curiosity-sparking touchpoint for shoppers, rather than a direct salesperson.
  • “The idea for Mike is that he would be placed maybe in a store and it would be a way to lure potential customers in... make them curious about what was going on.” — Miya Sato [01:36]

The Ubiquity of AI in Retail

• [02:59–03:59] Sato describes the overwhelming AI focus at the conference.
  • AI is being marketed for everything: HR, customer experience, SEO, data sorting, loss prevention, in-store environment control, and of course, chatbots for customers.
  • “It was basically an AI conference, really.” — Miya Sato [03:02]

Defining AI in Retail

• [06:26–06:40] O’Leary prompts Sato to clarify what counts as “AI” in this context.
  • Sato categorizes “generative AI” (chatbots, virtual agents) and “machine learning/data analysis” (recommendation systems, operational optimizations).
  • SEO for AI: Brands now concern themselves with how their products are surfaced in AI-driven chatbot responses, even though the rules are unclear.

Novel AI Retail Use Cases (and Some Gimmicks)

• [07:41–08:38] Grocery chain execs, food companies, and even Papa Johns tout new AI tools.
  • Papa Johns, for example, introduces a chatbot that can recommend how many pizzas to order for a group.
  • O’Leary pushes back, wondering if these features really solve problems: “I can count the number of people I’m having dinner with.” [08:28]
  • Sato observes pressure to adopt AI “even when it makes no sense.”

Disconnect Between Executives and Workers

• [08:38–09:43] Sato references a recent Wall Street Journal poll:
  • Executives report major productivity gains from AI, while non-managerial workers say it often wastes more time fixing mistakes.
  • “There is just like a clear disconnect between what the people running companies want and what everyone else says is useful or good or helpful.” — Miya Sato [09:43]

Big Tech's Bet: Google's Retail Push

• [09:43–12:01] Google’s prominent conference presence signals intent to own both the backend and customer-facing sides of AI retail.
  • Google launches new retailer tools for AI search integration, aiming to be the platform where consumers discover and buy products.
  • “It’s... indicative of a larger shift with AI companies, where the money or the use cases really are these agents, the so-called agentic web bots, doing things for humans, one of which is shopping...” — Miya Sato [11:04]
  • OpenAI’s absence is noted, suggesting different priorities.

The Dreams and Realities of Agentic Shopping

• [12:01–13:52] Both acknowledge AI shopping bots sometimes fail—randomly adding unwanted items to carts.
  • Sato, who enjoys shopping, had hoped AI would finally make online searches less painful, especially for niche finds.
  • “It just doesn’t work... It’s still faster and more effective for me to do a reverse image search.” — Miya Sato [13:49]

The Expanding Customer Data Vacuum

• [15:11–17:40] To power personalized AI assistants, retailers are collecting unprecedented quantities of customer data—now both online and in-store.
  • Example: Space Vision uses cameras to record shoppers in-store, analyzing gender, estimated age, and engagement with displays.
  • This dataset is leveraged to hyper-target follow-up marketing (e.g., coupons after a customer lingers at a chips ad).
  • “The end dream for retailers is that they know your intention for shopping… that is really reminiscent of how we shop on the Internet.” — Miya Sato [17:24]

Consumer Sentiment: Resignation or Alarm?

• [17:40–18:48] O’Leary notes the “Panopticon” vibe of this data-collection; Sato concurs it “feels bad.”
  • Sato points out U.S. consumers may be resigned or indifferent—often trading privacy for coupons.

Why Are Business Leaders So Eager Despite Lukewarm Demand?

• [18:48–21:00] Reasons include impressing shareholders, “hype cycle” pressure, and the search for scalable, agentic tools.
  • Sato acknowledges sometimes AI does improve workflow—her example: using Notion’s AI to quickly build a table is a real convenience.

“AI Slop” and Consumer Fatigue

• [21:00–23:55] The theme of “AI slop”—low-quality AI-generated content flooding platforms and retail—is explored.
  • Sato argues the negative perception is rooted in unauthorized use of creators’ work, poor content moderation, and relentless scale over quality.
  • “It feels like at least, just my sense, for consumers and the public is that there’s this feeling that it’s being forced upon people.” — Miya Sato [22:27]

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Memorable Quotes

• On AI Creep in Retail:
  “AI is inescapable not just for the customer. But also on the back end, like there is pressure for businesses to incorporate AI into their workflow even when it makes no sense.”
  — Miya Sato, [08:38]

• On the Disconnect Between Execs and Workers:
  “A big chunk of executives say they save 12 hours or more a week using AI, and then a big chunk of white-collar non-manager workers say they save no time at all—in fact, sometimes they spend more time fixing the mistakes.”
  — Miya Sato, [09:02]

• On the New Age of Agentic AI:
  “The money or the use cases really are these agents, the so-called agentic web bots, doing things for humans, one of which is shopping.”
  — Miya Sato, [11:04]

• On AI Slop:
  “AI slop has only one goal—scale. It doesn’t matter if the AI-generated clips flooding social media are good or even entertaining. They simply need to take up space and by extension, a human’s time.”
  — Lizzie O’Leary quoting Sato’s reporting, [21:00]

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Timestamps for Important Segments

• [00:36–03:59] — Conference recap, “Mike” the hologram, and the omnipresent AI theme
• [06:26–07:39] — Types of AI in retail (generative, data analysis)
• [07:41–09:43] — Papa Johns chatbot, questionable applications, disconnect in AI productivity
• [09:43–12:01] — Google’s retail AI strategy and the “agentic web”
• [12:01–13:52] — Agentic shopping bots: hopes vs. reality
• [15:11–17:40] — Customer data collection in-store and privacy concerns
• [18:48–21:00] — Executive incentives and the AI hype cycle
• [21:00–23:55] — “AI slop,” consumer fatigue, and questions about quality and consent

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Conclusion

The future of retail may indeed be AI-driven, but the journey is complicated by skepticism, privacy concerns, and the risk of alienating both consumers and workers. Retailers and big tech are betting that personalized, agentic AI can revolutionize shopping, but the sentiment from inside the industry—and from shoppers themselves—is far from settled.

Transcript

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[Lizzie O'Leary]

Not too long ago, reporter Miya Sato met a guy named Mike.

[Miya Sato]

So Mike is suspended in a tube, in a clear tube. He is wearing a hot pink suit and has like bleach blonde cropped hair. And there's a microphone outside of Mike's tube where people can step up and talk to Mike.

[Lizzie O'Leary]

Okay, so, so Mike is not actually a person.

[Miya Sato]

Mike is a hologram. And he has this huge sign above him that says talk to me.

[Lizzie O'Leary]

Mia, who's a reporter for the Verge, met Mike at the National Retail Federation's big annual conference last month where the retail industry goes to talk about the future of selling stuff.

[Miya Sato]

The idea is that all these attendees can go up to this mic, this microphone and talk to Mike and ask him like questions.

[Lizzie O'Leary]

Because surprise, surprise, the retail industry is betting big on AI.

[Miya Sato]

It's powered by ChatGPT and it's kind of like a human ish representation of a chatbot. The idea for Mike is that he would be placed maybe in a store and it would be a way to lure potential customers in. Not even that he would sell anything, but that he would be used as like a touch point for shoppers or customers that would kind of make them curious about what was going on and engage with the brand that deployed Mike or someone or something like Mike.

[Lizzie O'Leary]

What did people think of him? I hesitate to even call him a him for sure.

[Miya Sato]

It was like definitely one of the grabbier displays at this convention, you know, because it's like this weird sort of glitchy human looking thing where it's like talking to people who are passing by. You know, when I was talking to the company that makes Mike, I was like, where would I find him? Like, who would want to use this technology? Where would it be? And they were basically like, he might be outside a store, outside a booth or, you know, the idea is that it's like basically trying to generate Any sort of engagement between customers and the brand.

[Lizzie O'Leary]

How much of this retail conference was about AI?

[Miya Sato]

A shocking amount. Everywhere you turned the buzzword, the solution for problems that retailers have is AI. At least you know, within the walls of this conference, the products that were being sold or advertised were like AI and HR software and AI in customer experience. Like when you shop AI to help your brand be more visible on Google, AI holograms like Mike to lure customers in. Like it is everywhere. AI of course to like sort through data. AI solutions for loss prevention shoplifting AI to regulate the temperature of your grocery store so that it's optimal. Like these are all the places where AI is being shoved into. And of course like AI on the customer side when you order something, when you look for things online, it was everywhere. It was basically an AI conference really.

[Lizzie O'Leary]

Today on the show, the retail industry wants you to shop with AI whether you want to or not. I'm Lizzie o' Leary and you're listening to what Next tbd, a show about technology, power and how the future will be determined. Stick around.

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[Lizzie O'Leary]

So before we really dive in here, I think it's important to define what we're talking about when we say AI. Like, what kinds of AI do you mean?

[Miya Sato]

I mean, it kind of ran the gamut. I would say there's definitely, like, the generative AI side of it. Things like chat chatbots or large language models, People or things like Mike. And then there's also the other side that's more like machine learning and data analysis. I went to one booth that was basically like SEO for the AI era. So it was like advertising service to help brands be more visible. When shoppers are asking ChatGPT for, like, product recommendations, people really don't know how these chatbots surface products. So if you're doing SEO for them, it is kind of a crapshoot. You can, like, collect a bunch of data for it, but that's like, you know, an evolving space. We don't have the answers about, like, how to make sure your products are surfaced in chatbots. So it definitely felt like sort of the bleeding edge of a whole new world of how people shop.

[Lizzie O'Leary]

What kinds of products are we talking about here?

[Miya Sato]

Everything. There was everything from grocery stores was actually, like, pretty well represented. There was, like, a Kroger executive doing a talk about how they're using AI. There was a whole section for, like, food companies. Papa John's was there. They introduced, like, a chatbot for ordering pizza, which I found, like, hilarious. The idea being you can use the chatbot to, like, ask it to fulfill your last order of pizza. The really funny example that Papa John's was pushing was, like, let's say you have to order for a group and you don't know how many pizzas to get. You can ask the chatbot. I have 12 people. How many pizzas should I get?

[Lizzie O'Leary]

Well, this is the question that I had when I was reading your piece, which is like, what is the point of all of this? Because I can count the number of people I'm having dinner with.

[Miya Sato]

Yeah, I mean, I think it speaks to sort of, like, not just retail, but across so many different sectors and industries. AI is inescapable not just for the customer. But also on the back end, like there is pressure for businesses to incorporate AI into their workflow even when it makes no sense. There was a really incredible piece of polling that the Wall Street Journal wrote about a few weeks ago that was like asking C suite executives and then white coll our workers that weren't managers about how much time AI saves them in a week. And the answers are literally inverted. So executives say that they save like you know, a big chunk of executives say they save 12 hours or more a week using AI and then a big chunk of white collar non manager workers say they save no time at all. In fact sometimes they spend more time fixing the mistakes. So there is just like a clear disconnect between what the people running companies want and what everyone else says is useful or good or helpful or you know, like desired really.

[Lizzie O'Leary]

Sundar Pichai gave a speech at this conference and I'm curious why Google wants in on this. Like is this all about this backend that you're talking about of like we're actually selling to companies, not you know, frontline consumers?

[Miya Sato]

I think it's both. So Google introduced a bunch of new features and products at this event over that weekend and a lot of them were geared towards retailers, specifically giving retailers tools to show up in AI search and AI mode in Google. And a big part is obviously that you know, people are looking for products this way and maybe even buying them that way. And brands want in, they want to be incorporated into AI results. But at the same time, you know, it is like a customer facing product as well. It's when you search for things, how do you purchase it? Do you purchase it within Google's AI mode or within ChatGPT or do you go to the other side? This is like a huge space for Google and I would argue other AI companies. Like I found it pretty interesting that OpenAI didn't have that. I saw any presence at the National Retail Federation's event. Google had a huge, maybe multiple huge booths. They had a ton of employees or staffers working the booths and talking to people. They had demos, they had, you know, like, like you said, like executives speaking. And that really points to, you know, the priorities for the company where they think the money is. In some ways I think this is kind of like indicative of a larger shift with AI companies where the money or the use cases really are these agents, the so called agentic web bots, doing things for humans, one of which is shopping or finding products. And Google has had a whole slew of different features that they've introduced that very specifically signal that this is a priority. It's also like a huge money machine, right? Ads in ChatGPT, I think were announced and then ChatGPT said that they would skim a little off the top, like something like a 4% transaction fee from retailers.

[Lizzie O'Leary]

Agentic AI is so fascinating though, because sometimes it succeeds and other times, and we've interviewed people about this, like the AI is putting really random stuff in your cart that you do not want.

[Miya Sato]

You know, I consider myself someone who likes, I really like shopping, to put it bluntly. And I was actually kind of curious, maybe even hopeful about what AI tools could do because one of the experiences I think of shopping online is that it is really shitty. It kind of sucks. It's hard to find things partially maybe because of SEO, right? Decades of it, but it's really hard to find specific products. Search results are clogged with, you know, Google's own tools and the same five different brands plus like unknown kind of scammy looking companies. Influencer content is all over. Like it's really hard in my opinion to find like a good pair of black leather boots for the winter.

[Lizzie O'Leary]

I have been looking for merino wool barrel leg pants for a very long time. I mean, just getting served the wrong stuff.

[Miya Sato]

Exactly. And so I was like, maybe AI tools can help with this. Maybe they can find products that I didn't know about or surface, you know, links that are just being buried. I specifically, I love buying like vintage stuff. And so I was like, this is perfect. I can give very specific specifications, what year something is from, what it looks like and maybe it will, you know, surface links from like buried ebay listings or poshmark listings or whatever. And it just doesn't work like it's. It's still faster and more effective for me to do a reverse image search and then try to find things that way.

[Lizzie O'Leary]

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[Lizzie O'Leary]

in order to do this, these companies need a tremendous amount of customer data. And I'm just wondering, like, in order to power these AI agents to shop or even do some of the more specific retail stuff, is that going to change the amount of data collected about customers? And do people feel comfortable with that?

[Miya Sato]

One thing that really stood out to me from this event was the way that in brands and retailers dreams, the experience of shopping online is recreated everywhere, including in stores. So I talk about this one tool or company startup called Space Vision. One of the employees kind of gave me a demo with, but it was basically like using computer vision to create the experience of being followed on the Internet in person. They basically use cameras to capture video of shoppers in store. And he did say that the, the footage itself is deleted pretty much instantaneously. But the data they capture is like your gender, your estimated age and how much you engaged with in store displays. And of course, like this isn't widespread. It's only used in a, in a few stores in I think Japan and Korea at the moment. But the idea is that they would be able to track how long you look at an ad in a store, whether you picked something off the shelf and then later on the store could set up triggers that would be used to market things to you. So let's say, you know, it's like super bowl weekend and I am shopping for chips for my party. I'm at the chip display and it reg and the technology registers that I'm looking at this ad for chips. Later on it could send like a push notification to my phone or like a coupon to my email or whatever that's like, if you buy the chips you were looking at, you also get 20% off beer to go with it. And so that is the type of like, that is like the end dream for retailers is that they know your intention for shopping. They know what you're interested in, what you're browsing for, what you considered. And that is really reminiscent of how we shop on the Internet.

[Lizzie O'Leary]

I don't even know how to feel about that. It's very Panopticon.

[Miya Sato]

Yeah, it feels bad. That's how I feel.

[Lizzie O'Leary]

Do we have any idea how consumers

[Miya Sato]

might feel about This, I don't know, I'm kind of of two minds. On one hand, I think people hate that feeling of being surveilled. But also I think in the US and in other countries, probably, but I'll just speak to the U.S. like, a lot of American consumers are very used to this experience. They've been through all this. They're used to the feeling of having a product follow them from website to website advertising the same thing. They are kind of indifferent or maybe have given up on the idea that there's privacy. And I also frankly think about like when people don't have money or feel feel broke, maybe they would be willing to give up browsing data or activity or engagement data in exchange for a coupon. Like, I don't, I don't know. I can see it, I can see it.

[Lizzie O'Leary]

I think there's this really interesting tension in AI kind of across the board right now. And you got at it earlier, but between kind of business leaders and CEOs and workers or customers. Why do you think business leaders are rushing to implement AI even when there's kind of a, I don't know, meh feeling from customers?

[Miya Sato]

I mean, I think there are probably a bunch of things happening. One, like it looks good to tell your shareholders that you're doing this, having like a pizza ordering revolution with your AI chatbot. Like truly, this is sort of the language that is used. There's like a few tech companies that I think are right now propping up the US stock market. Yeah. So that also probably plays into it also, like there is the hype cycle, of course. And for, you know, at the beginning of sort of the AI ascendancy, it was a lot about like creative work, image generation and text generation. And in some ways I feel like we're kind of turning a corner more towards this like agentic world, which personally to me seems more useful. Whether it actually is in practice is up for debate and I think depends on the use case and depends on where it's deployed. In some places it makes zero sense. In other cases it might work like I use Notion and they have a feature where you can like add instructions and their AI tool will like create it. And I was on the notion like phone app and I had no idea how to do something and I just was like, create a table that's like two by three. And it did it. And I was like, this is so much easier than me clicking every button in this app. So yeah, it feels like that is sort of like the way that this will go at least right now, and certainly in retail. If you know any of these tools and exhibitors at this conference were an indication.

[Lizzie O'Leary]

There's a part of your piece that seems to be a theme that runs through this, where you write, AI slop has only one goal scale. It doesn't matter if the AI generated clips flooding social media are good or even entertaining. They simply need to take up space and by extension, a human's time. And this seems to be the big question, right? Like, is all this stuff just being made because some company can say it was made with AI, or does it actually have a reason to exist?

[Miya Sato]

I mean, I think certainly some things, not even generative AI, but more machine learning, it probably does make jobs easier or just results in better analysis or whatever. But I think the way we think of AI generated work or content that is created with AI is so colored by this idea that it's bad because there is a lot of bad AI stuff. And it feels like at least, you know, just my sense for consumers and the public is that there's this feeling that it's being forced upon people. It's everywhere from like art and culture and creative works to now how we shop on the Internet, how we're expected to do our jobs, right? A lot of workers say that they're being forced to use AI in a way that makes no sense. And I'm not actually like against the existence of AI tools. Some of them I use. But think back to how these tools were introduced to the public. It was like wide scale, unauthorized use of other people's work. My work has fed generative AI artists and authors and filmmakers and actors and musicians, right? Like, the way that the public was sort of made aware of this was what many would consider broad theft. And I think that has really colored the opinion of a lot of people. So when they see AI anywhere, even if it maybe is kind of useful, they associate it with something low quality. And there's also like the fact that a lot of tech platforms are not trying very hard to moderate that content out. They've kind of just accepted that Instagram will be filled with AI slop. And that's the way it is. And sometimes they're like, yes, this is the future is that like bots will be talking to each other on Instagram. And so, you know, I don't blame anyone for feeling fatigue or like outright hostility towards this technology that comes in a lot of different forms, does a lot of different things, but has this label of AI that people really bristle against.

[Lizzie O'Leary]

Miya Sato thank you so much for your reporting and for talking with me.

[Miya Sato]

Thank you so much.

[Lizzie O'Leary]

Lizzie Miya Sato is a reporter for the Verge. All right, that's it for our show today. What Next? TBD is produced by Patrick Ford. Our show is edited by Evan Campbell. Paige Osborne is the senior supervising producer for what Next and what Next tbd. Mia Lobel is the executive producer here at Slate. TBD is part of the larger what Next family. I'm Lizzie o'.

[Miya Sato]

Leary.

[Lizzie O'Leary]

Thanks for listening.

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