Using an AI agent to shop for you can be a peculiar experience. While tech companies market them as personal assistants capable of democratizing labor, they often require extensive instructions, run into technical hurdles, and occasionally return solutions that deviate from the original prompt.
Retailer Resistance
Major technology firms including Meta, Google, and OpenAI have introduced agentic shopping tools designed to streamline purchases, book travel, and secure event tickets. However, these systems rely on the willingness of third-party platforms to permit automated access.
Meta, Google, OpenAI, and others have all introduced some version of agentic shopping tools that promise to make buying things even easier than it already is. Demos show AI agents that can seamlessly book flights and hotels, browse billions of products to find the right one, and secure tickets to sporting events on a human’s behalf. But as AI companies — and their users — are finding out, buying things requires that the other party is willing to sell them in the first place.
Amazon has emerged as a prominent example, blocking tools like Meta’s Muse and initiating legal action against Perplexity over automated browsing. Other platforms, including financial institutions and travel providers, have similarly restricted outside agents due to security and risk concerns, while standard bot-blocking firewalls frequently disrupt agent reliability.
Even without hard blocks, agents’ access to retailers is spotty. For example, Muse, which I instructed to look for a specific face moisturizer, was caught in Target’s bot check one day but was able to get through the next. It suggested a listing from a grocery chain that doesn’t ship to my address when I searched for the best price on granola bars. When I asked for mattress recommendations under a certain price point, Muse was once again blocked by Target, despite being able to pull from the site just a few minutes prior.
Target representatives noted that platform access depends on specific tasks and security safeguards designed to protect customer data and transaction integrity, despite active partnerships with major AI developers.
The absence of major marketplaces like Amazon limits comprehensive price comparisons, requiring users to manually navigate gaps in automated searches and highlighting why platforms fiercely protect their ecosystems.
Amazon representatives confirmed requesting the removal of third-party applications that conduct purchases on behalf of customers without direct platform participation.
Company representatives emphasized that third-party services making purchases for customers should operate openly and respect platform participation decisions.
I instructed Muse to bulk-add all 10 of the newest listings from a favorite brand to my cart
Market Manipulation Risks
When shopping agents do function successfully, they introduce new complications for digital marketplaces. Automated tools can repeatedly claim limited inventory items by exploiting cart reservation systems, potentially locking out human consumers.
If I were a less honest, pure-hearted person, I would deploy an agent to run this personalized, technically allowed reserve system endlessly. But as I watched the items continuously pop back into my cart, exasperation flooded my psyche — on behalf of the other shoppers interested in these items, but also for my future self, who may soon be competing with someone else’s agent doing this same thing. Perhaps I already am.
Marketplaces like secondhand luxury retailer The RealReal maintain an open stance toward third-party AI agents while deploying safeguards to protect user experience and prevent disruptive automation.
“Our approach is to remain open to third-party AI agents, allowing them to browse, log in and interact with our marketplace, while maintaining safeguards against automated activity that could disrupt the customer experience,” Friang said.
The Future of Digital Discovery
While traditional e-commerce presents an overwhelming array of choices, agentic shopping narrows the experience significantly, functioning more like a constrained search window that requires constant parameter adjustments.
For complex or highly specific purchases involving strict personal preferences, agents can assist in deep research, though they still require substantial user guidance and verification.
The joy and thrill of discovery is largely gone
Meta representatives stressed that current tools maintain human oversight, requiring explicit permission before executing transactions and adhering to ethical browsing standards.
“Importantly, users can take over at any time, Muse is designed to always ask permission before buying, and it applies ethical browsing principles when asked to do things that a human could not - like buying all the tickets to an event,” Clayton said. “The response from retailers has been overwhelmingly positive, and we look forward to working with them as we continue to grow Muse and improve the purchasing experience.”
Ultimately, the widespread adoption of automated shopping agents risks altering the recreational and exploratory aspects of retail, transforming a common pastime into an optimized mechanical process.
