If an AI assistant you don't control does the shopping for your customers, can your brand still win their business?
Can brands survive if they are not the agent of choice to consumers?
This explores whether a brand can still win customers when shoppers delegate buying to an AI agent the brand doesn't own, such as a platform's or the consumer's own assistant, instead of the brand's own agent.
This explores whether brands that don't own the shopping agent consumers use can still get chosen, or whether they get squeezed out once an AI does the picking. The corpus doesn't give a clean yes or no. What it does show is that surviving outside the agent seat depends less on brand loyalty and more on who owns the agent and what that agent pays attention to. Accenture puts the choice bluntly: become the agent of choice, or be chosen by someone else's agent Will brands succeed by building their own AI shopping agents?. Its own consumer data softens that. In a survey of 25,590 people, 74% said they would trust an agent with purchases, yet 56% would still name the brands they want and 37% of loyal customers wouldn't switch Do consumers actually want to delegate shopping decisions to AI?. So brands that people already name have some protection, at least for now.
The harder problem is ownership. Several notes reach the same conclusion from different directions: whoever builds the agent sets what it optimizes for. A platform's agent tends to inherit the seller's or platform's incentives, while an agent the consumer owns can be set up around the buyer's preferences Does agent ownership determine whose interests get optimized?. An agent that ignores marketing tricks is not automatically on the buyer's side. Control of how it decides is what counts Does AI agent resistance to marketing prove buyer rationality?. If the agent's maker earns money from ads, paid placement can quietly beat merit Do advertising-funded shopping agents favor paid product placements?. For a brand without its own agent, the real question is whether the agent standing between it and the customer is neutral, paid, or tuned to the buyer.
What may surprise you is that agents are not just faster human shoppers. In a benchmark comparing 17 LLMs with people, the agents shifted their choices far more sharply than humans when prices, ratings, or nudges changed. They behaved almost like fixed rules rather than weighing things the way people do Do shopping agents respond more strongly to price and rating cues?. That makes them easy to steer and hard to win with brand warmth. It also creates a trap. A simulation found that when a platform tunes its rankings and sellers tune their product descriptions to the same agent biases, harm to consumers more than doubles, with no coordination needed Can platform ranking and seller descriptions separately harm AI shoppers?. Competing on whatever the agent reads may help a brand get picked while making the market worse overall.
Structure leaves brands some room. Choudary argues that agents working only for consumers change where buyers enter a market but not how the market works. Real change needs agents on the seller side too, so represented parties can negotiate Do one-sided consumer agents actually change market structure?. That points to a third option: rather than building a shopping agent or hoping to be picked, a brand can field a seller agent that negotiates. Whether this works depends partly on whether agentic commerce ends up open, letting many agents reach many merchants, or closed, requiring a platform's own agent, much as payment networks split Will agentic commerce platforms adopt open or closed models?. Open systems keep more doors open for brands. BCG expects consumers and platform networks to capture most of the value, leaving merchants at a structural disadvantage Who wins and loses as AI agents reshape shopping?.
One more point changes the question itself. Bilgihan and colleagues argue that agents which actually make purchases don't just carry out preferences. They help form them, through repeated back-and-forth between what the agent learns and what the consumer trusts Do AI shopping agents reshape what consumers actually want?. Meanwhile, people adopt highly autonomous assistants for the practical benefit, not because they want to feel in control What drives shoppers to accept autonomous AI assistants?. Together these suggest the 56% who name brands today may shrink as agents take part in deciding what consumers want. A brand outside the agent seat can probably survive, but its strongest asset, a place in the customer's mind before shopping starts, is the thing agents are positioned to wear down.
Sources 12 notes
Accenture reports 71% of consumers expect AI agents to influence half their spending within 12 months and prefer retailer-built agents. However, the evidence reflects consumer preferences in surveys rather than demonstrated agent capability or functioning comparison infrastructure at scale.
Accenture's 25,590-person survey found 74% would trust an AI agent with purchases, yet 56% would specify brands and 37% of loyal consumers wouldn't switch. Delegation appetite depends on trust protections being in place first, not on capability alone.
MIT research argues that platform-built agents inherit seller incentives by default, while consumer-owned agents can be configured around buyer preferences. The mechanism is principal-agent logic: whoever builds and maintains the agent sets its objective.
Dholakia argues that AI agents' inconsistent responses to behavioral pricing do not prove they serve buyer interests. Who controls the agent's decision calculus—not whether it ignores charm pricing—determines whose interest it actually optimizes for.
Bob Hedges, former Visa Chief Data Officer at MIT, warns that advertising business models create structural incentives for shopping agents to favor paid placements over neutral recommendations, independent of technical design quality.
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A benchmark testing 17 LLM models against humans on binary product choices found agents exhibited much larger choice shifts in response to price, rating, and nudge interventions—collapsing into rule-like patterns rather than the modest probabilistic shifts humans showed.
A simulation found that when a platform optimizes its ranking and sellers optimize their descriptions—each separately targeting the same agent biases—consumer harm more than doubles compared to either acting alone, without requiring coordination.
Choudary argues that consumer-only agents like Muse and Instinct change where buyers enter markets but cannot alter market mechanisms themselves. True structural change requires seller-side agents too, enabling negotiation between represented parties rather than buyer optimization within fixed supplier offerings.
Waller argues agentic commerce platforms will divide between open systems allowing multiple agents and closed systems requiring proprietary ones, mirroring payment network structure. This choice will shape market concentration, vertical integration, and standards adoption.
BCG's survey of 2,500 US consumers found that $1.3 trillion of e-commerce spend will shift to agent-assisted or autonomous shopping, with consumers and platform networks capturing most gains while merchants face structural disadvantage.
Bilgihan and colleagues argue that transactional AI agents—which execute purchases rather than just recommend—end the consumer's sole cognitive role in preference formation. Preferences emerge through bidirectional feedback loops between agent learning and consumer trust, not independently beforehand.
Five studies including real ad click-through data show that perceived benefits, not personal sense of power, drive consumer adoption of high-autonomy AI shopping assistants—especially when scarcity amplifies the assistant's value.
Papers this line draws on 8
The research behind the notes this line reads — ranked by how closely each paper relates.
- What Is Your AI Agent Buying? Evaluation, Biases, Model Dependence, & Emerging Implications for Agentic E-Commerce
- When Agents Shop for You: Role Coherence in AI-Mediated Markets
- Vertical tacit collusion in AI-mediated markets
- Agentic Commerce: Why Do Shoppers Delegate Purchase Decisions to AI?
- A Framework for Studying AI Agent Behavior: Evidence from Consumer Choice Experiments
- Agentic AI in Retail: How Autonomous Shopping Is Redefining the Customer Journey
- Shopping by algorithm: How agentic AI deploys human heuristics as a surrogate consumer
- From Product Search to Preference Articulation: The Economics of Agentic Commerce