AI in retail

Concrete uses

AI has become a strategic infrastructure for retail, applied to every link in the commercial chain. In stores and online, it automates customer service through conversational assistants that answer questions about products, orders and deliveries. It forecasts demand by analysing large volumes of historical data, factoring in seasonality, promotions and external conditions. It recommends items to each customer in real time by studying browsing behaviour and past purchases. It also analyses shelf video to flag stock-outs or misplaced products, guiding the work of floor teams. Finally, it secures payments by detecting abnormal transactions within milliseconds, without slowing down checkout.

Issues and limits

The widespread adoption of AI in retail raises multiple tensions. Customer data remains a central concern: personalisation relies on the collection and processing of sensitive data, framed by the GDPR. Recommendation or dynamic-pricing systems can create discriminatory bias, offering different products or prices depending on a customer profile. Payment security grows more complex as generative AI tools make it possible to engineer more sophisticated fraud. Transparency is also at stake: how do algorithms decide to display one product rather than another, or to block a transaction? Finally, the growing automation of customer service raises questions about the role of human interaction and the quality of the customer experience.

Regulation and the European framework

Across Europe, the retail sector must navigate a dense regulatory landscape. The GDPR imposes strict obligations on consent, transparency and the exercise of consumer rights over personal data. National data protection authorities oversee local enforcement and publish guidance on AI use for profiling and recommendation. The European Union's AI Act applies progressively, classifying certain systems, such as real-time fraud detection, according to their impact. On the public side, national authorities and some regional bodies support retail SMEs through practical guides and funding to broaden access to these technologies. Traditional merchants, small and large alike, are integrating AI to stay competitive against digital leaders, while commerce solution vendors offer products tailored to every size of business.

What ActuIA tracks

ActuIA monitors how retail is evolving in relation to AI: the emergence of new uses such as autonomous AI agents and in-store video recognition, the regulatory tensions between innovation and data protection, the real impact on jobs and skills in stores, documented cases of algorithmic discrimination or error, and the accessibility of these tools for small merchants competing with e-commerce giants.