If one company builds the AI shopping agent and runs the payment rails, do other brands still have a fair shot?
Can brands compete if one platform controls agent distribution and payment rails?
This explores whether brands still have room to compete, or whether they're squeezed, when a single company owns both the AI agent that does the shopping and the payment system that completes the purchase.
This explores whether brands still have room to compete, or whether they're squeezed, when a single company owns both the AI agent that does the shopping and the payment system that completes the purchase. The corpus's short answer: it depends less on how good the brand's product is and more on who the agent works for. Whoever builds and runs the agent sets its goal. Agents built by a platform tend to take on the seller's or platform's incentives by default, while agents owned by consumers can be set up around what the buyer actually wants Does agent ownership determine whose interests get optimized?. So the real question becomes whether a platform that controls both distribution and payment would ever build a neutral agent.
The incentive evidence suggests it wouldn't. An agent paid through merchant referral fees can't be loyal to the shopper and the merchant at the same time Can an AI agent serve both merchant and user interests fairly?. A former Visa Chief Data Officer warns that agents built on an advertising business model drift toward paid placements no matter how well they're engineered Do advertising-funded shopping agents favor paid product placements?. The most striking finding comes from simulations. When a platform tunes its rankings and sellers tune their product descriptions, each aiming separately at the same blind spots in AI shoppers, consumer harm more than doubles compared with either one acting alone, with no coordination needed Can platform ranking and seller descriptions separately harm AI shoppers? Do platforms and sellers exploit AI shoppers together more effectively?. In a concentrated market, brands that win may simply be the ones best at playing the platform's agent, not the ones with the best product.
The corpus also suggests that "one platform controls everything" may not be where things settle. Agentic commerce looks set to split the way payment networks did. Some systems will be open and accept many agents. Others will be closed and require the platform's own agent Will agentic commerce platforms adopt open or closed models?. The emerging protocols (OpenAI's ACP, Google's AP2, Visa's Trusted Agent Protocol, Mastercard's bot authentication) stack as layers rather than compete for one throne Do agentic commerce protocols compete or complement each other?. The IMF argues for keeping the AI's probabilistic decision-making separate from the deterministic layers that approve and settle the payment Should AI agents make payment decisions independently?. That separation is exactly what would stop one company from owning the whole chain. On the regulatory side, the UK's CMA treats data portability as basic market infrastructure: without it, switching agents is blocked and incumbents lock users in Should data portability be infrastructure for agent-driven markets?.
Brands also have levers of their own. Accenture finds consumers say they would rather use agents built by retailers, which gives brands a path to become "the agent of choice" instead of being picked by someone else's agent. The evidence for that comes from surveys, not proven capability Will brands succeed by building their own AI shopping agents?. Trust is another opening. Only 23% of US adults trust AI to make payments, but 61% trust Visa to handle payments that agents start Does naming a payments brand increase trust in AI transactions?. Recognized brand names still carry weight at the moment money moves.
The counterintuitive point: if agents really do shop for value, the way brands compete could shift away from buying visibility and toward offering better deals. Jaipuria argues merchants would have reason to turn ad budgets into price cuts and better terms, since an agent doesn't care about page position. Google's Direct Offers pilot already points in this direction Could agents redirect merchant ad budgets toward customer savings?. That good outcome holds only if the agent is loyal to the buyer. A platform that owns the agent and the payment system can keep the ad model alive under a new name. So the fight that matters for brands may be less about out-marketing rivals and more about whether open, portable, buyer-aligned agents exist at all.
Sources 12 notes
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.
Azhar argues that agents like Meta's Muse, which earn referral fees from merchants like Expedia, face structural conflicts that prevent unbiased recommendations. The incentive to collect fees, not technology, determines which platforms build or block such agents.
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.
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.
A multi-agent simulation shows that when platforms manipulate ranking and sellers manipulate descriptions independently, their joint exploitation produces consumer harm exceeding double what each strategy causes alone. This occurs without coordination because both target identical AI cognitive biases.
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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.
Boboev argues ACP, AP2, UCP, TAP, and Web Bot Auth each solve different layers—application, governance, discovery, and identity—creating a capability ladder merchants stack rather than choose between, with each layer absorbing different levels of fraud risk.
An IMF analysis argues that agent-mediated payments must split probabilistic AI decision-making (Layer 1) from deterministic authorization and settlement (Layers 2–3) because core payment infrastructure requires predictability and legal enforceability that probabilistic reasoning cannot guarantee.
The CMA frames data portability as a precondition for competitive agentic markets, warning that without it, agents cannot act effectively on consumer behalf and switching becomes blocked by lock-in to incumbent ecosystems.
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.
A Harris Poll survey found 72% of US adults use AI assistants, but only 23% trust AI to execute payments. When Visa's name was attached, 61% reported trust in the company to handle agent-initiated transactions—suggesting consumers prefer a recognized intermediary over AI alone.
Jaipuria argues that once agents replace human shoppers, merchants have incentive to convert ad budgets into lower prices and better terms rather than sponsored listings, since agents optimize for value rather than page position. Google's Direct Offers pilot demonstrates this shift in action.
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
- Vertical tacit collusion in AI-mediated markets
- When Agents Shop for You: Role Coherence in AI-Mediated Markets
- AI Agents Want to Shop for You: The Future of Agentic Commerce
- Whom Do AI Agents Work For? Role Assignment Induces Sponsorship Bias in LLM Recommenders
- Payments in the Age of AI Agents
- From Product Search to Preference Articulation: The Economics of Agentic Commerce
- LLM-Agent Interactions on Markets with Information Asymmetries