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AI Agents: The New Interface of the Customer Journey

  • Writer: Hélène Allouard
    Hélène Allouard
  • 3 days ago
  • 3 min read

How Agentic Commerce is Redefining the Rules of Retail

By Thaddée Reynaud, Chief Product Officer at Valiuz


AI agents are progressively re-intermediating the customer journey—whether it is recommending a product, comparing offers, or, in the near future, orchestrating an entire shopping cart. Consumers are now destined to delegate these tasks to AI entities such as ChatGPT, Perplexity, Google Gemini, or Amazon’s Rufus. This is a very real shift, considering that one in two consumers plans to use AI for their online shopping.


Thaddée Reynaud - Chief Product Officer at Valiuz


What are the stakes in this new algorithmic logic?


The user experience is becoming more conversational and personalized, but above all, entirely delegated. Soon, users will no longer search through multiple sites themselves; instead, they will formulate a precise intent for a personal agent (e.g., “Find me a pair of running shoes suited to my needs”). The agent then handles the rest: criteria analysis, instantaneous comparison of a nearly infinite catalog, trade-offs (price, quality, availability, etc.), and more recently, the management of payment and delivery. For advertisers, it goes without saying that a massive disruption is on the horizon: we are moving from mechanics designed for humans to mechanics designed for machines. Consequently, structured data becomes the key material, and the primary challenge shifts from narrative persuasion to algorithmic relevance.


The first consequence is the potential sidelining of "traditional" content. Indeed, AI agents do not "see" banners or videos; they consume data feeds. Visibility now depends more on the quality of these signals than on the displayed content. The legibility of information as perceived by robots becomes the deciding factor: catalog consistency, semantic enrichment, inference logic, intent data, and so on. This underscores the importance of a rapid transition toward AI-native architectures.


Finally, it is impossible not to mention the new constraints of GEO (Generative Engine Optimization)—specifically, understanding the diversity of signals that AI agents rely on, and will rely on, to recommend a specific brand. We already know that, in addition to product specifications, an agent shapes its recommendations based on reputation, customer reviews, perceived credibility, proof of quality, and demonstrated performance.


What happens to Retail Media in the era of agentic commerce?


To stay competitive in the face of this revolution, Retail Media players must launch several strategic initiatives. This involves leveraging structured, reliable data that is interpretable by AI models, which will directly influence the consumer’s agentic shopping journey. Furthermore, European players must act as a counterweight to US and Asian Big Tech by developing their own proprietary agentic solutions as quickly as possible to regain control over conversational data. The goal is to establish natural entry points in the omnichannel journey, capable of integrating into agentic flows, interacting with third-party agents via A2A (Agent-to-Agent) protocols, and, if necessary, assisting the consumer right through to their in-store experience.


Embracing the shift toward agentic commerce does not necessarily require a complete pivot, but rather diversification. In the same way that the web did not eliminate physical stores, AI agents will not immediately replace traditional shopping journeys. In fact, the initial impacts of agentic commerce appear to be boosting website traffic—a phenomenon expected to be confirmed in 2026—even if long-term impacts may differ once agents are massively deployed and adopted.


In any case, AI must be integrated broadly into the management of Retail Media campaigns: automation at scale, content generation, format adaptation, continuous optimization, and, of course, agentic interfacing.


In short, the advent of agentic commerce opens a new era where trust, data quality, and algorithmic relevance take precedence over direct exposure and impressions. While this revolution poses a threat to stagnant players, it represents a historic opportunity for those capable of adapting quickly.



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