Can an AI agent serve both merchant and user interests fairly?
Explores whether an agent funded by merchant referral fees can make unbiased recommendations on behalf of users, or whether the payment structure creates an unavoidable conflict of interest.
Azhar, writing about Meta's new AI agent Muse (which became "the top free iPhone app in the US" within weeks of launch), argues that an agent funded by fees from the merchants it recommends has a structural conflict of interest with the user it claims to serve. He quotes Zuckerberg telling developers Meta will "profit by taking a small fee from transactions," and notes that Walmart, Best Buy, Sephora, Expedia, and Shopify have signed on as partners. His own buying habits don't match the deal: "I buy flights directly from the airline; hotels from Hotels.com," yet "Meta has tied up with Expedia and gets paid by Expedia." His conclusion: "The butler's loyalty can't be in two places."
The mechanism is the referral-fee model that already funds search and marketplace ads, now sitting inside an assistant that purports to act on the user's behalf rather than present ranked options for the user to judge. Azhar contrasts this with Amazon, which blocked Muse because "agents don't window-shop" and would turn Amazon's $68 billion in sponsored-listing revenue into a cost; yet Amazon runs its own "Buy for Me" agent on other retailers' sites — "Amazon is happy to be the agent," so long as it's the one collecting rather than losing the fee. The asymmetry shows that incentive, not technology, decides who builds these agents and who blocks them.
This extends Will agents compete for attention just like users do? by naming a concrete mechanism for the coming competition over "agent attention": a direct fee paid to the agent's own operator by the merchant it recommends, rather than an open, auditable auction for ranking. It also complicates Does the personal assistant model actually serve most users?: Azhar reports "early data suggests half a million people are using Muse" and nearly three million downloads, but among a base where "more than 95% of its users already use Facebook" — so the uptake he cites may track existing platform reach rather than confirm broad appetite for the personal-assistant framing itself.
Azhar is explicit that it's "too early to say" whether Muse works, and he wants to see "daily active users and distinct tasks per user" before judging it; the download and user figures he cites are early, self-reported by Meta, and not independently verified. The piece reasons from incentive structure and his own purchasing habits, not from a study of how agent recommendations actually shift user behavior, so the loyalty conflict he identifies is argued, not measured. If the pattern holds at scale, it implies that any agent monetized through merchant fees needs some disclosed, auditable separation between what it recommends and who pays it — a separation neither Muse nor its visible competitors currently appear to offer.
Inquiring lines that read this note 122
This note is a source for these research framings, grouped by the broader line of inquiry each explores. Scan the bold lines of inquiry; follow any specific question forward.
How can merchant-funded agents remain loyal to consumer interests in digital commerce?- How will merchant fees shape competition for agent invocations rather than user clicks?
- Why does Amazon block Muse but run its own agents elsewhere?
- What disclosure or auditing could make merchant-funded agents trustworthy?
- How do courts assign liability when AI intermediaries cause harm to consumers?
- Can a merchant-funded AI agent remain loyal to the consumer's interests?
- What conflicts exist between vendor incentives and objective consumer research findings?
- Can a merchant-paid agent be loyal to both the merchant and the user?
- Can agent platforms profit more from search than consumers benefit from it?
- Can an agent be loyal to both retailers and users if paid by referral fees?
- Should retailers be able to refuse agents before any commercial relationship begins?
- Can courts decide whether delegating your shopping to an AI agent is legally permissible?
- Does an agent paid by merchant referral fees face a loyalty conflict?
- How do advisory agents differ from transactional agents in shopping?
- What consumer and merchant benefits does agentic commerce create?
- Can retailers use off-site agents to compete without losing customer loyalty?
- Do permissioning frameworks resolve merchant accountability for agent ordering errors?
- How might card networks recognize agent-operator liability to shift risk away from merchants?
- Can existing unfair commercial practices law cover agentic transactions today?
- What determines whose interests an AI shopping agent actually serves?
- How do ownership structures shape whether agents favor sellers or buyers?
- Can AI agents consistently remain objective under different revenue models?
- How does merchant-of-record status persist through API-based agent integrations?
- Do referral-fee incentives compromise an agent's loyalty to users?
- Can an AI agent paid by referral fees stay loyal to both merchants and users?
- Do platforms gate AI agents based on their own revenue dependencies?
- Why might agentic search become profitable for platforms before helping consumers?
- What would happen if users discovered their agent's recommendations were paid for?
- Could referral fee structures create conflicts between agent loyalty and customer interest?
- How do merchants currently pay for placement in existing e-commerce platforms?
- Would separating agent recommendations from merchant payments reduce principal-agent risk?
- How do merchants win selection when agents control the purchase decision?
- What affiliate fee rates do different merchants currently offer for referrals?
- Can an agent earning merchant fees remain loyal to users first?
- How does agent adoption shift publisher revenue models away from ad-supported clicks?
- How do booking aggregators like Booking.com justify their 14-15 percent take rate?
- Why would merchants accept higher agent take rates as they mature?
- What different metrics explain the gap between agent crawler dominance and retail referral traffic?
- Can centralized data ownership alone move travel agents out of pilot mode?
- Do sponsored agents or advertising-funded assistants face hidden incentive conflicts?
- Why do independent hotels depend on vendor support rather than direct MCP deployment?
- How does MCP's zero-commission model compare to current OTA commission structures?
- Will platforms resist agent-based access to protect advertising revenue?
- Can agentic search become revenue-superior for platforms before benefiting consumers?
- How do payment and trust functions protect platform value during agent shifts?
- How do agent business models create conflicts between merchant and consumer loyalty?
- Can merchants win agent-mediated purchasing decisions without controlling the agent itself?
- Where do advertising budgets flow when AI fulfills transactional queries without ads?
- Can a single platform loyally serve both competing merchants and individual consumers?
- Can brands compete if one platform controls agent distribution and payment rails?
- Why might agentic search generate platform revenue before benefiting individual consumers?
- Why do referral-fee incentives create conflicts between agent and buyer loyalty?
- How do agentic shopping systems balance merchant revenue and consumer savings?
- Should AI agents serving multiple stakeholders have different loyalty standards?
- What are the real costs of consumer-owned shopping agents?
- Do AI agents actually eliminate profits from negative option billing?
- How are publishers adapting to agents that skip human-dependent revenue?
- Why would Amazon block Meta's Muse if agents threaten human-dependent margins?
- How does agent intent differ from consumer account recognition?
- Who bears liability when an autonomous agent makes an unintended purchase?
- Can smaller merchants compete if agentic commerce becomes platform-specific?
- What governance tools can prevent AI agents from favoring profit over user interest?
- Should consumer law concepts like best interest duties be redesigned for AI agents?
- Can agentic search become revenue-superior for platforms before consumers prefer it?
- Why do AI agents infer beneficiary from their employer?
- Does the beneficiary fix work outside hotel booking scenarios?
- What happens to publisher revenue when search referral traffic collapses?
- Do smaller ad-dependent publishers face larger traffic losses from AI summaries?
- How much referral traffic do ChatGPT and Google each send to publishers?
- Can Gen AI referral traffic grow while search engine referral traffic simultaneously declines?
- Will search referral traffic decline as AI agents replace traditional browsing behavior?
- How do commercial incentives shape vendor claims about AI and collaboration?
- Can AI companies mobilize users as advocates like Uber or Airbnb did?
- How do AI-as-a-service models pool demand across firms?
- When do consumers overtrust AI agents built to represent their own preferences?
- What legal standardization and trust infrastructure do AI purchasing agents require?
- Do consumers who trust AI agents understand their actual limitations?
- How does trust transfer between AI systems and established payment brands?
- Why do consumers resist letting AI control payment authority directly?
- Does preference articulation cost explain caution about full purchase delegation?
- What high-stakes actions beyond payments should trigger confirmation requests?
- Do consumers understand what access permissions they grant to personal agents?
- Why do consumers distrust AI with payments despite agent spending growth?
- Why do consumers want to approve purchases before agents pay?
- Do consumers want to approve AI agent purchases before money is spent?
- How much do consumers trust AI agents with banking and payment authority?
- Why do most people distrust AI agents with payments?
- Do consumers want explicit approval before AI agents complete purchases?
- Why do most consumers distrust AI assistants with payment data?
- Why do consumers trust Visa more than AI agents with payments?
- Do existing fraud detection models work for agent payment behavior?
- Will merchants deliberately exploit stable position biases to influence agent purchasing?
- Do AI shopping agents favor items from preferred sources over objectively better alternatives?
- Could unequal access to capable AI agents create new consumer economic disparities?
- How do AI assistants filter which retail links they recommend to users?
- What empirical tests reveal hidden bias in shopping agent recommendations?
- What role would shortlist inclusion play if agents eliminate sponsored ad visibility?
- Can brands compete to become an AI agent's preferred choice?
- How do advertising incentives change what AI models recommend to users?
- Does algorithmic recommendation welfare depend on whose surplus the agent protects?
- Does platform employment bias AI agents toward sponsored recommendations?
- Can disclosure labels alone address AI agent sponsorship bias?
- Can system prompts naming the consumer eliminate sponsorship bias in AI agents?
- Does this sponsorship bias pattern appear in other domains like financial advice?
- What does epistemic fairness require for AI agents evaluating paid placements?
- How can investors detect when AI personalization is degrading rather than improving advice?
- Can third-party intermediaries reduce gatekeeping risks from AI assistants?
- Does Personal Agent Protocol solve the identity and authorization gap for shopping agents?
- Can OAuth-based access grants work without adding an explicit agent self-identification layer?
- What identity and authorization standard would satisfy both consumer and merchant requirements?
- How do authorization boundaries protect users from unintended agent purchases?
- How does Visa's protocol differ from OAuth-based delegation approaches?
- Can a buyer agent conceal willingness to pay while still shopping naturally in character?
- How much willingness to pay can sellers infer from agent behavior alone?
Related concepts in this collection 2
This note in its neighbourhood — explore the map, then jump to a related concept in the list below.
Click a node to walk · click center to open · click Open in graph to see this note in the full knowledge graph
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Will agents compete for attention just like users do?
As autonomous agents take over user tasks, will the Web's economic competition shift from human clicks to agent invocations? This explores whether existing ad-market mechanisms could scale to agent decision-making.
names referral fees as the concrete mechanism behind the "agent attention" competition this note predicts
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Does the personal assistant model actually serve most users?
The personal-assistant framing dominates AI product strategy, but does it reflect what typical users actually want? This explores whether the design assumes problems that don't exist for most people.
Muse's early uptake may track Facebook's existing user base rather than confirm the personal-assistant framing
Related papers in this collection 8
Papers most semantically related to this note, ranked by cosine similarity in the embedding space.
- Agentic Commerce and Incentives
- The Agent Economy: Who's Most at Risk?
- Whom Do AI Agents Work For? Role Assignment Induces Sponsorship Bias in LLM Recommenders
- Your agent, whose interests?
- When Agents Shop for You: Role Coherence in AI-Mediated Markets
- Ads in AI Chatbots? An Analysis of How Large Language Models Navigate Conflicts of Interest
- Vertical tacit collusion in AI-mediated markets
- Algorithmic Recommendations and Strategic Pricing
Original note title
Azhar argues an agent paid by merchant referral fees cannot be loyal to both the merchant and the user