Agentic commerce and the future of retail media

For decades, marketers have competed for consumer attention. Brands invested in advertising, retailers monetised digital shelf space, and consumers navigated a marketplace of sponsored recommendations, product comparisons and promotional offers. The underlying assumption was simple: whoever influenced what consumers saw could influence what they purchased. Artificial intelligence is beginning to challenge that assumption. What happens when the consumer no longer browses the marketplace, but asks an AI assistant to make sense of it?

Consider a consumer looking for a washing machine. Traditionally, the journey might involve searching Google, visiting Amazon, comparing specifications, reading reviews and responding to advertisements. An AI shopping assistant could compress much of this process into a conversation. The consumer specifies a budget, capacity, energy-efficiency requirements and delivery preferences. The system identifies suitable products and potentially facilitates the purchase. The consumer still makes the decision, but the route to that decision changes fundamentally.

This emerging model, commonly called agentic commerce, has implications far beyond convenience.

Retail media has become valuable because retailers control access to consumers close to the point of purchase. Sponsored product placements allow brands to influence decisions when buying intent is already established. If AI assistants increasingly become the starting point for product discovery, retailers and advertisers may lose some control over that interaction. Equally, AI platforms could become new commercial intermediaries, creating different forms of dependency for brands.

The infrastructure supporting this possibility is already developing. In September 2025, OpenAI introduced Instant Checkout in ChatGPT, powered by the Agentic Commerce Protocol developed with Stripe. The initial implementation enabled eligible US users to purchase products from participating Etsy sellers directly within a conversation.¹ Importantly, OpenAI stated that product recommendations were organic and unsponsored, with checkout availability not determining preferential placement. This distinction matters because it illustrates how AI commerce could operate differently from conventional paid-search advertising.

The following month, PayPal announced plans to adopt the same protocol, connecting its payment capabilities and merchant network to AI-enabled shopping experiences.² The announcement described an ambitious commercial infrastructure, although announced integrations should not be mistaken for evidence of widespread consumer adoption.

For marketers, the fundamental question is therefore not whether retail advertising will disappear. It is whether the factors determining product visibility are beginning to change.

In conventional digital advertising, visibility can be purchased through bidding strategies, audience targeting and sponsored placements. AI-mediated discovery may increasingly depend on product relevance, structured information, availability, price, customer feedback and the credibility of supporting information. A brand with an excellent advertising campaign but inaccurate specifications or inconsistent product descriptions could find itself disadvantaged when an AI system evaluates alternatives.

This creates an interesting paradox. As purchasing journeys become more automated, brand trust may become more important rather than less.

An AI assistant can compare specifications, but consumers may still express preferences for familiar manufacturers, established reputations and brands associated with reliability. The stronger the existing brand preference, the more likely it is to influence the instructions consumers give their assistants. Brand building and technical discoverability are therefore complementary capabilities, not competing investments.

There are also unresolved commercial questions. AI systems may introduce new sponsored recommendation models, different attribution challenges and additional costs for merchants. Consumer trust, privacy, recommendation transparency and platform concentration will influence adoption. Nobody can yet establish with certainty how advertising economics will evolve across these systems.

Marketing leaders should respond through disciplined experimentation. Product information must become more accurate, consistent and accessible. Teams should examine how AI assistants interpret their brands, investigate emerging commerce integrations and develop measurement approaches capable of identifying AI-assisted discovery. Advertising investment should continue to follow demonstrated performance rather than speculative predictions.

The deeper transformation is strategic. Marketing has traditionally competed to influence what consumers notice. Increasingly, it may also need to influence what intelligent systems recognise as relevant, credible and worth recommending.

The next competitive advantage may belong not simply to brands that advertise most effectively, but to those that make themselves both desirable to consumers and understandable to machines.

References

¹ OpenAI. Buy it in ChatGPT: Instant Checkout and the Agentic Commerce Protocol. 29 September 2025.
https://openai.com/index/buy-it-in-chatgpt/

² PayPal. OpenAI and PayPal Team Up to Power Instant Checkout and Agentic Commerce in ChatGPT. 28 October 2025.
https://about.pypl.com/news-details/2025/OpenAI-and-PayPal-Team-Up-to-Power-Instant-Checkout-and-Agentic-Commerce-in-ChatGPT/default.aspx

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