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

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?

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]

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]

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

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.