gensai.aiArtificial intelligence continues to transform many sectors, and retail is one of the areas where change is particularly fast.
In an article devoted to agentic AI in retail, the Journal du Net (JDN) recently interviewed several sector experts, including Gensai, to identify the concrete use cases emerging for retailers.
This coverage highlights an important shift: consumers no longer interact solely with websites or apps. They can now converse with artificial intelligence capable of understanding their needs, searching for information and acting on their behalf.
Why does agentic AI interest retailers?
The emergence of AI agents opens new perspectives for retail players.
These systems can interact with users in natural language and carry out various actions: searching for a product, comparing offers, answering a question or supporting a purchase.
With the arrival of new technical standards, some platforms are now working to let artificial intelligence and commerce systems communicate directly with each other. In time, this could automate part of the purchase journey, from finding a product to placing the order.
In this context, retailers also need to adapt their online presence. Content must be structured and understandable by AI models. This shift is part of an emerging discipline: GEO (Generative Engine Optimization), which consists of optimising content for AI-powered search engines.
What are the first concrete uses in retail?
Among the applications already visible, customer service stands out as one of the most promising areas.
Conversational agents can answer customer questions, access product sheets and provide precise technical information. They can also guide consumers in their choices.
For example, an AI agent can analyse the characteristics of several products and help a customer identify the one that best matches their need. This kind of assistance can improve the user experience and reduce cart abandonment.
These tools must nevertheless be deployed carefully. A poorly designed experience or imprecise answers can quickly damage how a brand is perceived.
AI can also transform internal operations
Artificial intelligence is not limited to customer relations. It can also play a role in retail's internal processes.
AI agents can help automate certain tasks related to order management, supplier relations or data analysis.
In some scenarios, AI can for instance turn an order sent by email or voice message into a ticket a supplier can act on directly.
It can also analyse several information sources in order to anticipate supply needs.
In large-scale retail, various parameters can be taken into account to adjust orders: the weather, sales history, store footfall or changes in raw material prices.
Agents connected to company data
Deploying artificial intelligence agents depends largely on the quality of the available data.
Companies need structured, usable information in order to avoid errors or approximate answers.
A common approach is to connect the agent to an internal knowledge base through a RAG (Retrieval-Augmented Generation) architecture. This method lets the AI query company documents directly in order to produce more reliable, contextualised answers.
Agents can also be connected to various tools and applications in order to automate certain tasks and make information easier to reach.
Specialised models rather than ever-larger ones
One of the lessons highlighted in the Journal du Net article is that performance does not depend solely on the size of AI models.
In many cases, smaller, specialised models connected to internal knowledge bases can produce more relevant results.
This approach also allows better control over the data used and limits risks related to information security and confidentiality.
The essential role of human oversight
Despite the rapid progress of these technologies, artificial intelligence does not operate on its own.
Human oversight remains essential to supervise agents, validate certain decisions and guarantee the quality of customer interactions.
In retail, these tools can above all act as assistants for teams, making information easier to reach and helping handle repetitive tasks.
This hybrid model, combining artificial intelligence and human expertise, should progressively establish itself in the years ahead.
Going further
Agentic artificial intelligence therefore opens new perspectives for retail players. It can improve customer relations, make information easier to reach and automate certain internal operations, while leaving an essential place to human expertise.
To read the full analysis and the viewpoints shared in this interview, the Journal du Net article is available here (in French):