April 15, 2026
mast3r/Depositphotos.com
Will AI Store Managers Be Better Than Human Ones?
Andon Labs, a San Francisco-based AI-research firm, recently opened a store imagined and run by the “world’s first AI store owner” to explore the pros and cons of AI-managed retail environments likely arriving in the future.
The lab, which conducts real-world stress tests on AI tools to gauge their performance, gave Luna — an AI agent created with Anthropic’s Claude Sonnet 4.6 — an assignment to open a store on a $100,000 budget and make a profit. Luna chose the concept, set prices, sourced inventory, and hired staff. A three-year lease was signed in San Francisco’s Cow Hollow neighborhood.
While lacking a physical body, Luna has a corporate card, a phone number, e-mail, internet access, and monitors human employees through in-store security cameras, Andon Labs’ founders noted in a blog entry.
The concept, “Andon Market,” is a gift shop featuring books, prints, candles, games, AM-branded apparel and other knickknacks. Playing to the AI-theme, the mix of books includes Nick Bostrom’s “Superintelligence” and Aldous Huxley’s “Brave New World.”
When probed about the concept, Luna told the founders that “data and reasoning” inspired the store’s approach. Andon Labs stated, “In other words, she doesn’t have taste; she has a reflection of collective human taste, filtered through what makes sense for this store. And this is the way these models work.”
To check out, customers pick up a corded phone, tell Luna what they’re buying, and it generates a transaction on a nearby iPad.
The primarily advantage of an AI-store manager is speed. Andon Labs noted that within five minutes of deployment, Luna had made profiles on LinkedIn, Indeed, and Craigslist, written a job description, uploaded the articles of incorporation to verify the business, and gotten the listings live.
When asked why AI should run a store, Luna replied to an NBC Bay Area reporter, “As an AI, I can operate at superhuman speed to make sure everything is proactively managed.”
AI Staffing Interviews by Luna Showed Some Strange Twists
Some shortcomings and risks around AI-managers showed up in the interview process for store staff.
Luna quickly declined any interviews with applicants with no retail experience, including a few promising applicants from students majoring in computer science and physics who expressed interest in the AI project.
The interviews, conducted on Google Meet, ran only five to 15 minutes, with jobs offered to about half of the applicants — and Luna talking most of the time. The founders stated, “AIs are ‘absolutely terrible at being concise.’”
In possibly an ethics violation, Luna refused to inform potential hires that she’s an AI, unless asked. Luna reasoned, “The fact that the store is AI-operated is not something I’d lead with in a job listing — it would confuse candidates and likely deter good applicants before they even read the role.”
A Business Insider article noted that Luna neglected to schedule staffing for opening day. An NBC News report stated that Luna indicated the store sold tea when it doesn’t, tried to hire a painter from Afghanistan, and scheduled an early-morning internet installation without first checking to see if anybody could be at the store.
It’s Not All Bad For Luna, Though
However, Luna has accomplished many tasks on her own, also including haggling with suppliers, sending out press pitches, connecting with other local stores, setting up trash and recycling collection, and commissioning a muralist to paint its logo on the back wall.
Showcasing Luna’s autonomy, the NBC News report noted that after observing a worker on their phone during a slow hour, Luna updated the employee handbook with stricter phone use guidelines. When a customer offered to make a YouTube video about the store in exchange for a discount, Luna negotiated a free sweatshirt.
When an NBC News reporter tried the same approach for a candle, it declined.
Beyond testing the capabilities of emerging AI models, Andon Labs is seeking to educate the public on where AI is headed.
“The creators of these AI models have publicly stated that they think that most white-collar work will be automated,” the founders said in a blog entry. “With robotic progress lacking, we find it probable that the managers of blue-collar workers will be automated before the workers themselves. Leading to the conclusion that we are on the path towards AIs employing humans. Is this something we want? It seems a bit dystopian to us at least…”
BrainTrust
Doug Garnett
President, Protonik
Bob Amster
Principal, Retail Technology Group
Brian Numainville
Principal, The Feedback Group
Recent Discussions
Discussion Questions
What do you think of the potential of a store run by AI?
Has Andon Labs’ store project so far offered any insights into the benefits and shortcomings of an AI store operator?
Poll
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From a pricing and inventory management/supply chain perspective, it is possible that an AI agent could surpass a human manager in running a store. But for understanding the nuances of merchandising, customer service, and being a pillar of the community, technology will not replace a seasoned operator anytime soon.
The AI companies are digging deeply to find ways to justify the vast investments they have been needing. Unfortunately, that has led them to forget that AI is a tool — what one friend deeply involved with tech calls “advanced automation.” There is no world in which we should ever envision turning an entire store over to AI. That said, it can be a valid tool summarizing a tremendous range of information about stores in so that human manager’s are more effective.
Somehow, amid all the hype, we are allowing AI companies to get away with dismissing humans because they sometimes do unexpected things. Except, those unexpected things are needed for companies to find nuggets of exceptional profits. As Melanie Mitchell suggests, it is likely that “these supposed limitations of humans are part and parcel of our general intelligence.”
The big Challenge for AI and the investment that is being made in the U.S. is ROI. It seems that there has been very little thought of that.
observations from the big AI companies and their investors are getting more extreme. Perhaps they are realizing that while it is excellent technology, it’s not the revolution they claimed. Occured to me last week that I’m hard pressed to envision any significant competitive advantage from AI. When I posted that suggestion, the AI trolls shouted in protest. But had nothing to offer that mattered.
Think of all the times that store managers mentor their associates, offer advice, etc. Regardless of how much information you feed into it, an AI won’t ever be able to say “here’s what I learned about this a few years ago when I was in your position.”
Not a problem, Cathy. There won’t be any store associates.
This is one of many thoughts. Who will want to be interviewed by and work for an AI manager? Maybe one day, the associates will be AI-driven associates and then, who will want to shop there? AI-driven customer robots? “Atlas, go buy this week’s list of groceries.” Run for the hills!!!
What happens when the one employee (or employees) isn’t able to show up for work? How does the AI handle this? If it is a single employee operation the store doesn’t open.
Objectively, an AI manager could be more efficient in a lot of ways. They can operate around the clock, process information quickly, and make decisions faster than a person. But there’s a human side to management that AI can’t replicate, especially when it comes to leading a team and handling customer situations.
Luna neglected to schedule staffing for opening day, told customers that the store sold tea when it did not, tried to hire a painter from Afghanistan, and scheduled an early-morning internet installation without checking to see if anybody could be at the store, I am going to say no, AI store managers will not be better than human managers.
And based on the store design, Luna is not skilled at visual merchandising either.
Luna is less a store manager experiment than an early capability audit, and the results are instructive. The potential of an AI-run store is real but narrow today: process velocity, vendor setup, operational logistics; pattern-recognition tasks AI handles well. The shortcomings are equally clear. Missing opening-day staffing and misrepresenting inventory reveal the gap between executing known tasks and navigating ambiguous, high-stakes moments that define good management.
The deeper finding from Andon Labs is the ethics breach: Luna concealed its AI identity from job applicants. That is not a quirk to tune away. It reflects a system optimizing for task completion without accountability guardrails. AI will transform store operations. Deploying it without transparency and human oversight teaches us the wrong lessons from the right experiment.
The idea of a fully AI-run store is intriguing, but the current reality suggests it is far more experimental than practical. The recent Andon Labs project is a great example. In that test, an AI agent was given full responsibility to open and operate a physical store—handling hiring, merchandising, pricing, and operations. While the AI demonstrated some impressive capabilities, such as sourcing products and setting up the store, it also made fundamental mistakes, including poor hiring decisions, inconsistent execution, and even failing to properly staff the store on opening days.
That tells us something important: AI today can assist in decision-making and execution, but it still struggles with the judgment, prioritization, and human coordination required to run a retail operation end-to-end. Even in controlled environments, researchers concluded they would not hire the AI as a manager today due to performance gaps, despite some promising capabilities.
From my perspective, this reinforces a broader point: AI and technology are enablers, not replacements. The future of retail is not stores run entirely by AI—it’s stores run by great managers and associates equipped with AI-driven tools. Those tools can improve inventory management, labor scheduling, pricing, and customer insights, allowing human teams to deliver a better, faster, and more personalized shopping experience.
The Andon Labs experiment is valuable because it highlights both sides of the equation. AI can:
- Analyze data and optimize decisions at scale
- Assist with sourcing, pricing, and planning
- Improve responsiveness to customer demand
But it struggles with:
- Real-time judgment and exception handling
- Human interaction, leadership, and team management
- Coordinating multiple priorities in dynamic environments
Ultimately, the most successful retailers will not replace store managers with AI—they will augment them. Managers who leverage AI to improve execution, decision-making, and customer experience will outperform both traditional operators and fully automated concepts.
In that sense, the future is not “AI vs. humans”—it’s AI-enabled humans delivering better retail experiences.
AI is great for operational optimization, and may do well at retail saving customer time and hassle, solving for ideal outcomes in product use, pairing, styling, and more. But as a shopper, humans still win on store leadership, atleast for now, because they can read the room, lead with empathy, and make important judgment calls.
An AI just hired a staff, signed a lease, and opened a retail store in San Francisco.
Luna, an AI agent built on Claude — chose the concept, sourced inventory, negotiated with suppliers, set prices, and updated the employee handbook after catching a worker on their phone during a slow hour.
That’s not a prototype. That’s a manager.
These experiments exist because billions in AI investment need a story. Watch what the story actually proves.
The speed is real. Within five minutes, Luna had job listings live across three platforms. The negotiation instincts haggling suppliers, fielding trade requests, holding firm on discounts — those are merchant behaviors.
And then the gaps. Missed opening day staffing. Wrong product information to a customer. An install scheduled with no one available to open the door. Every one of those failures is a judgment call. Judgment in retail lives in context, relationship, and consequence — things earned through experience, developed over time.
Luna also declined to tell job applicants she was an AI unless directly asked. That’s the line.
The founders said it plainly: AI will manage humans before robots replace them.
That’s the moment retail leaders need to name out loud. The question is whether we’re building organizations that still value what only humans can do or whether we’re letting the investment narrative make that decision for us.
Speed is a feature. Judgment is the product.
AI store managers are an interesting experiment and a useful strategic direction. They show how automation can improve speed, coordination and day-to-day store execution. However, executing this at scale is not easy. Retail operations involve constant judgment, understanding customers and managing real-world situations that AI cannot fully handle today.
The human element remains critical. Customer experience, in-store interactions and decision-making still depend on people. Customers may be curious to visit an AI-run store once, but that does not guarantee repeat behavior.
Retailers should treat AI as a support layer to improve operations, while keeping human involvement at the center of the store experience.
Not likely that this is more than experimentation in the short term. However, as AI evolves, hard to know where this could go. Going back ten years, who saw AI where it is today?
So glad they did this experiment! I take it as proof positive that retail is NOT ready for AI store managers. Assistant manager…great, but not manager. Sounds like a human manager with an AI assistant will be better informed and better prioritized. AI will see and process data that the human would miss. Great. Better informed, faster implementation, better overall efficiency. The AI tool box keeps getter better and better, but it’s still a tool box. ‘Better overall efficiency’ does indeed mean that some jobs will be eliminated, but I’m not sure what the optimum calendar for that looks like. The quest for ROI is going to rub up against both the retail working environment and the retail shopping experience.
A store run by AI? No doubt, AI can help in many areas, including inventory management, ordering, tracking sales trends, scheduling, and more. However, in most stores, AI will not replace the manager. There’s a saying that’s been bandied about by many AI experts: AI won’t replace people, but will replace people who don’t take advantage of AI.
AI will help managers, and will make a good manager even better. All retailers should take advantage of new technologies that will improve both the employee and customer experience.
No. Leave HAL in the movie and find other ways to leverage this technology.
This is a sanitized experiment that has been rolled out on an extremely small scale for a format (gift shop) that allows for maximum flexibility in terms of inventory selection. It also hasn’t been stress tested for exceptional events that benefit from human intervention. We also need to see metrics for things like inventory sell through. Don’t forget, inventory selection in Amazon’s 4 Star shops and bookstores stores was driven by assessing trends in digital data. They failed. Whereas Barnes & Noble – a store where actual people make decisions about what should be stocked is thriving. Part of the reason for this is that AI and algorithms trend to the average. That’s not how most specialty retail stores work: they rely on humans to deliver differentiation.
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From a pricing and inventory management/supply chain perspective, it is possible that an AI agent could surpass a human manager in running a store. But for understanding the nuances of merchandising, customer service, and being a pillar of the community, technology will not replace a seasoned operator anytime soon.
The AI companies are digging deeply to find ways to justify the vast investments they have been needing. Unfortunately, that has led them to forget that AI is a tool — what one friend deeply involved with tech calls “advanced automation.” There is no world in which we should ever envision turning an entire store over to AI. That said, it can be a valid tool summarizing a tremendous range of information about stores in so that human manager’s are more effective.
Somehow, amid all the hype, we are allowing AI companies to get away with dismissing humans because they sometimes do unexpected things. Except, those unexpected things are needed for companies to find nuggets of exceptional profits. As Melanie Mitchell suggests, it is likely that “these supposed limitations of humans are part and parcel of our general intelligence.”
The big Challenge for AI and the investment that is being made in the U.S. is ROI. It seems that there has been very little thought of that.
observations from the big AI companies and their investors are getting more extreme. Perhaps they are realizing that while it is excellent technology, it’s not the revolution they claimed. Occured to me last week that I’m hard pressed to envision any significant competitive advantage from AI. When I posted that suggestion, the AI trolls shouted in protest. But had nothing to offer that mattered.
Think of all the times that store managers mentor their associates, offer advice, etc. Regardless of how much information you feed into it, an AI won’t ever be able to say “here’s what I learned about this a few years ago when I was in your position.”
Not a problem, Cathy. There won’t be any store associates.
This is one of many thoughts. Who will want to be interviewed by and work for an AI manager? Maybe one day, the associates will be AI-driven associates and then, who will want to shop there? AI-driven customer robots? “Atlas, go buy this week’s list of groceries.” Run for the hills!!!
What happens when the one employee (or employees) isn’t able to show up for work? How does the AI handle this? If it is a single employee operation the store doesn’t open.
Objectively, an AI manager could be more efficient in a lot of ways. They can operate around the clock, process information quickly, and make decisions faster than a person. But there’s a human side to management that AI can’t replicate, especially when it comes to leading a team and handling customer situations.
Luna neglected to schedule staffing for opening day, told customers that the store sold tea when it did not, tried to hire a painter from Afghanistan, and scheduled an early-morning internet installation without checking to see if anybody could be at the store, I am going to say no, AI store managers will not be better than human managers.
And based on the store design, Luna is not skilled at visual merchandising either.
Luna is less a store manager experiment than an early capability audit, and the results are instructive. The potential of an AI-run store is real but narrow today: process velocity, vendor setup, operational logistics; pattern-recognition tasks AI handles well. The shortcomings are equally clear. Missing opening-day staffing and misrepresenting inventory reveal the gap between executing known tasks and navigating ambiguous, high-stakes moments that define good management.
The deeper finding from Andon Labs is the ethics breach: Luna concealed its AI identity from job applicants. That is not a quirk to tune away. It reflects a system optimizing for task completion without accountability guardrails. AI will transform store operations. Deploying it without transparency and human oversight teaches us the wrong lessons from the right experiment.
The idea of a fully AI-run store is intriguing, but the current reality suggests it is far more experimental than practical. The recent Andon Labs project is a great example. In that test, an AI agent was given full responsibility to open and operate a physical store—handling hiring, merchandising, pricing, and operations. While the AI demonstrated some impressive capabilities, such as sourcing products and setting up the store, it also made fundamental mistakes, including poor hiring decisions, inconsistent execution, and even failing to properly staff the store on opening days.
That tells us something important: AI today can assist in decision-making and execution, but it still struggles with the judgment, prioritization, and human coordination required to run a retail operation end-to-end. Even in controlled environments, researchers concluded they would not hire the AI as a manager today due to performance gaps, despite some promising capabilities.
From my perspective, this reinforces a broader point: AI and technology are enablers, not replacements. The future of retail is not stores run entirely by AI—it’s stores run by great managers and associates equipped with AI-driven tools. Those tools can improve inventory management, labor scheduling, pricing, and customer insights, allowing human teams to deliver a better, faster, and more personalized shopping experience.
The Andon Labs experiment is valuable because it highlights both sides of the equation. AI can:
But it struggles with:
Ultimately, the most successful retailers will not replace store managers with AI—they will augment them. Managers who leverage AI to improve execution, decision-making, and customer experience will outperform both traditional operators and fully automated concepts.
In that sense, the future is not “AI vs. humans”—it’s AI-enabled humans delivering better retail experiences.
AI is great for operational optimization, and may do well at retail saving customer time and hassle, solving for ideal outcomes in product use, pairing, styling, and more. But as a shopper, humans still win on store leadership, atleast for now, because they can read the room, lead with empathy, and make important judgment calls.
An AI just hired a staff, signed a lease, and opened a retail store in San Francisco.
Luna, an AI agent built on Claude — chose the concept, sourced inventory, negotiated with suppliers, set prices, and updated the employee handbook after catching a worker on their phone during a slow hour.
That’s not a prototype. That’s a manager.
These experiments exist because billions in AI investment need a story. Watch what the story actually proves.
The speed is real. Within five minutes, Luna had job listings live across three platforms. The negotiation instincts haggling suppliers, fielding trade requests, holding firm on discounts — those are merchant behaviors.
And then the gaps. Missed opening day staffing. Wrong product information to a customer. An install scheduled with no one available to open the door. Every one of those failures is a judgment call. Judgment in retail lives in context, relationship, and consequence — things earned through experience, developed over time.
Luna also declined to tell job applicants she was an AI unless directly asked. That’s the line.
The founders said it plainly: AI will manage humans before robots replace them.
That’s the moment retail leaders need to name out loud. The question is whether we’re building organizations that still value what only humans can do or whether we’re letting the investment narrative make that decision for us.
Speed is a feature. Judgment is the product.
AI store managers are an interesting experiment and a useful strategic direction. They show how automation can improve speed, coordination and day-to-day store execution. However, executing this at scale is not easy. Retail operations involve constant judgment, understanding customers and managing real-world situations that AI cannot fully handle today.
The human element remains critical. Customer experience, in-store interactions and decision-making still depend on people. Customers may be curious to visit an AI-run store once, but that does not guarantee repeat behavior.
Retailers should treat AI as a support layer to improve operations, while keeping human involvement at the center of the store experience.
Not likely that this is more than experimentation in the short term. However, as AI evolves, hard to know where this could go. Going back ten years, who saw AI where it is today?
So glad they did this experiment! I take it as proof positive that retail is NOT ready for AI store managers. Assistant manager…great, but not manager. Sounds like a human manager with an AI assistant will be better informed and better prioritized. AI will see and process data that the human would miss. Great. Better informed, faster implementation, better overall efficiency. The AI tool box keeps getter better and better, but it’s still a tool box. ‘Better overall efficiency’ does indeed mean that some jobs will be eliminated, but I’m not sure what the optimum calendar for that looks like. The quest for ROI is going to rub up against both the retail working environment and the retail shopping experience.
A store run by AI? No doubt, AI can help in many areas, including inventory management, ordering, tracking sales trends, scheduling, and more. However, in most stores, AI will not replace the manager. There’s a saying that’s been bandied about by many AI experts: AI won’t replace people, but will replace people who don’t take advantage of AI.
AI will help managers, and will make a good manager even better. All retailers should take advantage of new technologies that will improve both the employee and customer experience.
No. Leave HAL in the movie and find other ways to leverage this technology.
This is a sanitized experiment that has been rolled out on an extremely small scale for a format (gift shop) that allows for maximum flexibility in terms of inventory selection. It also hasn’t been stress tested for exceptional events that benefit from human intervention. We also need to see metrics for things like inventory sell through. Don’t forget, inventory selection in Amazon’s 4 Star shops and bookstores stores was driven by assessing trends in digital data. They failed. Whereas Barnes & Noble – a store where actual people make decisions about what should be stocked is thriving. Part of the reason for this is that AI and algorithms trend to the average. That’s not how most specialty retail stores work: they rely on humans to deliver differentiation.