The transcription discusses the retail industry's significant push into AI, as observed at the National Retail Federation's conference. A key example is "Mike," a ChatGPT-powered hologram chatbot designed to attract and engage customers in stores. AI permeates retail, from front-end applications like pizza-ordering chatbots and AI-enhanced search results to backend functions such as data analysis and inventory management. However, a notable gap exists between executives' optimism about AI saving time and the reality for workers and shoppers, who often encounter ineffective or cumbersome tools. For instance, AI shopping assistants frequently fail to deliver better product discoveries than traditional methods. The drive for AI integration also involves extensive data collection, including in-store surveillance to track customer behavior for targeted marketing, raising privacy concerns. Overall, while businesses rush to adopt AI for competitive advantage and shareholder appeal, consumer and worker skepticism persists, partly due to AI's association with poor-quality outputs, intrusive practices, and ethical controversies surrounding its development.
[MUSIC] Not too long ago, reporter Miyasato met a guy named Mike. So Mike is suspended in a tube, in a clear tube. [MUSIC] 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. Okay, so Mike is not actually a person. Mike is a hologram and he has this huge sign above him that says, talk to me. Miyab, 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. [MUSIC] The idea is that all these attendees can go up to this mic. [LAUGH] As a microphone, and talk to Mike, and ask him questions. Because surprise, surprise, the retail industry is betting big on AI. It's powered by chat GPT 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 touchpoint 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. What did people think of him? I hasn't even called him a him. It, it, it, for sure. It was like definitely one of the grabier displays at this convention. Because it's like this weird sort of glitchy human looking thing where it's like talking to people who are passing by. When I was talking to the company that makes Mike, I was like, where would I find him? 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. How much of this retail conference was about AI? 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 in HR software, 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 lost 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. Today on the show, the retail industry wants you to shop with AI. Whether you want to or not. I'm Lizio Leure and you're listening to WhatNextTBD, a show about technology, power, and how the future will be determined. Stick around. 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? I mean, it kind of ran the gamut, I would say. There's definitely like the generative AI side of it, things like 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 chat GPT 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 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. What kinds of products are we talking about here? Everything. There was everything from grocery stores was actually like pretty well represented. There was like a crogr executive doing a talk about how they're using AI. There was a whole section for like food companies. Papa Johns 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 Johns 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 guess? 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. 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 collar 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. Sundar Pichai gave a speech at this conference and I'm curious why Google wants in on this. Like is this all about this back end that you're talking about? We're actually selling to companies, not, you know, frontline consumers. 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 chat GPT or do you go to the other side? This is like a huge base 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, well, I made a 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 you said, like executive 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, 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 chat GPT. I think we're announced and then chat GPT said that they would skim a little off the top, like something like a 4% transaction fee from retailers. 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. You know, I consider myself someone who like, 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, really, really, really important.
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 scamming 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. I have been looking for marino, wool, barrel leg pants for a very long time. I mean, I just getting served the wrong stuff 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 e-bay listings or posh mark 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. After the break, the consumer data vacuum keeps on sucking. 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? 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 has 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 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 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. I don't even know how to feel about that. It's very pin up to come. Yeah, it feels bad. That's all I feel. Do we have any idea how consumers 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 US. 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 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 know. I don't know. I can see it. I can see it. 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, me feeling from customers. 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 a genetic 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. 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? I mean, I think certainly some things, you know, not even like generative AI but more like machine learning. Like it probably does make jobs easier or you know, just like results in better analysis or whatever. But I think, you know, 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 in 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 to 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. - Miyasato, thank you so much for your reporting and for talking with me. - Thank you so much, Lizzy. - Miyasato is a reporter for The Verge. All right, that's it for our show today. What next TVD is produced by Patrick Ford? Our show is edited by Evan Campbell. Paige Osburn is the senior supervising producer for What Next and What Next TVD. Mia Lowe Bell is the executive producer here at Slate. TVD is part of the larger What Next family. I'm Lizzy O'Leary, thanks for listening.
Podcast Summary
Key Points:
The retail industry is heavily investing in AI, showcased at the National Retail Federation conference with tools like hologram chatbots (e.g., "Mike") for customer engagement.
AI applications span from customer-facing tools (chatbots for ordering, AI search integration) to backend operations (data analysis, loss prevention, inventory management).
There is a disconnect between business leaders' enthusiasm for AI's efficiency gains and the experiences of workers and customers, who often find it unhelpful or intrusive.
AI-driven shopping tools, like agentic AI for product discovery, frequently underperform, failing to improve the online shopping experience effectively.
Enhanced data collection, such as in-store computer vision tracking, raises privacy concerns as retailers aim to replicate online personalization in physical stores.
Public skepticism toward AI is fueled by its association with low-quality content ("AI slop"), forced implementation, and ethical issues like unauthorized use of creative works.
Summary:
The transcription discusses the retail industry's significant push into AI, as observed at the National Retail Federation's conference. A key example is "Mike," a ChatGPT-powered hologram chatbot designed to attract and engage customers in stores. AI permeates retail, from front-end applications like pizza-ordering chatbots and AI-enhanced search results to backend functions such as data analysis and inventory management.
However, a notable gap exists between executives' optimism about AI saving time and the reality for workers and shoppers, who often encounter ineffective or cumbersome tools. For instance, AI shopping assistants frequently fail to deliver better product discoveries than traditional methods. The drive for AI integration also involves extensive data collection, including in-store surveillance to track customer behavior for targeted marketing, raising privacy concerns.
Overall, while businesses rush to adopt AI for competitive advantage and shareholder appeal, consumer and worker skepticism persists, partly due to AI's association with poor-quality outputs, intrusive practices, and ethical controversies surrounding its development.
FAQs
Mike is an AI-powered hologram, using ChatGPT, designed as a human-like chatbot to engage customers. It was displayed at the National Retail Federation's annual conference as an example of retail AI innovation.
AI is being applied across retail in areas like customer experience, HR software, loss prevention, inventory management, and even temperature regulation in stores. It was a dominant theme, with many products aimed at enhancing both backend operations and customer interactions.
Papa Johns introduced a chatbot for ordering pizza, which could suggest how many pizzas to buy for a group—a feature some found unnecessary since people can easily count attendees themselves.
Executives often report saving significant time with AI, while many non-managerial workers say it saves little or no time, sometimes even requiring extra effort to correct AI mistakes, highlighting a disconnect in its practical utility.
Technologies like computer vision can track in-store behavior (e.g., what ads shoppers view) to later send targeted promotions, raising surveillance concerns similar to online tracking, though data like video footage may be deleted promptly.
Businesses face pressure to adopt AI for shareholder appeal, staying competitive in hype cycles, and exploring new revenue streams, even if use cases are not always practical or welcomed by customers.
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