Retailers adopting artificial intelligence to personalise shopping experiences face a fast-evolving regulatory landscape, particularly in Europe where new rules are reshaping how AI can be used. The promise of AI lies in its ability to tailor the entire customer journey – from product recommendations and adaptive search results to dynamic content and in-store assistants – but delivering this potential demands a careful balance of innovation and accountability.
AI personalisation uses data to customise retail experiences, from homepage feeds and smart search to checkout suggestions and real-time assistance via chatbots or virtual stylists. These tools are often powered by machine learning or large language models integrated into ecommerce platforms.
However, Europe’s regulatory environment is tightening. The EU AI Act, set to take effect between 2025 and 2027, introduces a tiered risk framework for AI systems: unacceptable, high, limited and minimal. Most retail tools fall into the limited or minimal categories, requiring transparency, documentation and consent. High-risk systems, such as those affecting credit or employment, will be subject to stricter rules including human oversight and third-party audits.
Retailers must also continue to comply with GDPR and cookie consent rules, while mapping how and where AI is used. This means documenting data sources, limiting collection to relevant behavioural or contextual information, and steering clear of sensitive attributes. The focus is on using data that enhances shopping without compromising privacy.
In practice, personalisation can be both effective and compliant. Reordered category pages, search suggestions based on past behaviour, and transparent product recommendations (“Based on what you viewed this week”) improve customer experience without overstepping ethical or legal boundaries. AI also supports merchandising by targeting banners, offers and bundles to different user segments. Inventory and fulfilment systems benefit from AI-powered forecasting based on anonymised local data, improving efficiency and sustainability.
Transparency remains key. Labelling AI features, such as chatbots or autogenerated descriptions, builds trust. Dedicated pages explaining AI use, data types and user controls help customers make informed choices. Retailers are advised to embed lightweight governance rather than build large compliance units. Maintaining a central register of AI tools, their purpose and data inputs, and forming cross-functional review teams can help flag risks early. Logging decisions improves traceability and supports internal oversight.
Ethical concerns persist. A recent academic study warns of declining consumer trust linked to data overcollection. It recommends transparency, regular audits for bias, consumer input in AI design, and options to reset or override personalisation. Retailers should test AI systems for fairness across diverse user groups and ensure personalisation never limits access or choice.
In-store applications are evolving too. Smart kiosks, digital shelves and loyalty-based offers enhance service without relying on banned methods like biometric recognition. Opt-in features ensure transparency and consent.
With key transparency and high-risk provisions becoming mandatory from 2026, the coming year is critical. Retailers should begin by cataloguing AI features, assessing risks, updating transparency statements and aligning consent mechanisms. Assigning product owners to each AI feature will help maintain clarity and accountability.
Used responsibly, AI can deliver smarter, more intuitive shopping while upholding consumer rights. With clear governance and a focus on ethics, UK and European retailers are well-placed to lead in AI innovation that benefits both business and the customer.
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