Would You Let AI Shop for You?

Oct 29, 2025

Malique Morris, a reporter at The Business of Fashion specializing in AI and ecommerce, joins the discussion on the emergence of AI shopping agents. He explains how these agents differ from traditional recommendation systems by not just suggesting items, but learning shopper preferences to facilitate transactions. The conversation covers the necessity of trust and accuracy for consumer acceptance, while also touching on how these agents could replicate the in-store shopping experience without requiring brands to change their offerings significantly.

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INSIGHT

Agents Move Beyond Static Recommendations

AI shopping agents aim to learn a shopper's tastes and act on their behalf beyond simple recommendations.
They can respond to highly specific prompts and may complete transactions once trusted.

INSIGHT

Two Paths: Search Vs. Fashion-First

Search-driven players like OpenAI and Perplexity pull results across the web but lack deep personalization.
Fashion-first startups focus on learning users' closets and calendars to provide tailored buys.

ANECDOTE

Who Tries Them First

Early adopters are avid shoppers who enjoy new tech and will upload closets to train agents.
Startups expect a small but committed user base to iterate the product before wider adoption.

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A new wave of AI shopping agents has emerged as Big Tech and start-ups alike vie for dominance of this new market. OpenAI, Google and Perplexity are experimenting with search-to-checkout, while fashion-specific entrants like Vêtir, Phia and Gensmo are learning users' tastes before recommending and purchasing across retailers. But before they get off the ground, trust, accuracy, privacy and simple usefulness remain open questions.

Senior correspondent Sheena Butler-Young and executive editor Brian Baskin are joined by BoF reporter Malique Morris to map the agentic ecommerce landscape.

Key Insights:

AI shopping agents aim to move beyond static recommendations to truly act on a shopper’s behalf. As Morris explains, “traditional e-commerce has algorithms that recommend items based on what you’ve already browsed or purchased,” whereas “an AI shopping agent is supposed to learn the shopper and can act on their behalf,” handle “very specific prompts” and, ultimately, complete the transaction.

Agents are trying to replicate the best in-store experience for the ecommerce space. “They’re supposed to be about replicating the in-store salesperson, surfacing the right piece based on the conversation that you might have,” says Morris. As a result, “it’s not calling for brands to rethink how they’re designing their goods,” but more about tools that “help them sell them better and help them get into the hands of the people who are actually really going to want them.”

Early users are avid shoppers who love new technology. Morris doesn’t expect a sudden tipping point, but rather gradual mass adoption. “Agentic commerce is [already] here because the tools are being built and experimentation is happening,” he says. “People are going to be conditioned the same way that they were conditioned when Netflix rolled out their algorithms, the same way TikTok and Instagram have with ‘for you’ pages. It’s here, it’s happening and it’s only going to get more efficient.”

While the consumer should benefit from this new suite of AI shopping agents, Morris is blunt about power dynamics: “Outside of ‘the consumer is going to win,’ I think it’s going to be who has the resources to perfect this.” Consolidation is to be expected as many smaller platforms are “probably going to get consumed into an OpenAI or a Google or an Amazon. Those already huge [players] are probably going to be the ultimate winners.”

Additional Resources:

What It Will Take for Consumers to Let AI Shop For Them | BoF

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