European retailers are increasing investment in artificial intelligence (AI) as they seek to improve efficiency, manage costs and adapt to changing consumer behaviour.
Findings from a new analysis by McKinsey & Company show that AI in retail Europe is shifting from small-scale pilots to wider operational use across core business areas, including pricing, forecasting and customer engagement.
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The report, Rewiring retail in Europe: the AI imperative, highlights a sector under pressure from thin margins, uneven demand across markets and rising operational complexity.
In response, many retailers are using AI tools to support decision-making and automate routine processes.
Efficiency focus
Retailers are increasingly using AI to improve productivity in areas such as supply chain management, merchandising and demand forecasting.
Machine learning systems are being applied to large sets of sales and inventory data to help predict demand more accurately. This is particularly important in Europe, where fragmented markets and multiple sales channels make planning more complex.
The report notes that AI can reduce manual work in planning functions, allowing teams to focus more on strategy and category performance. It also supports faster reactions to changes in consumer demand, which can help reduce waste and improve stock availability.
Cost pressure remains a key driver. Retailers are exploring AI-enabled automation in areas such as procurement and finance to streamline back-office operations and improve efficiency.
Customer shift
AI is also being used to reshape how retailers interact with customers, particularly through personalisation and digital experience improvements.
Retailers are investing in systems that analyse customer behaviour across online and in-store channels. The aim is to deliver more consistent experiences and more relevant product recommendations.
Search and recommendation tools are becoming more advanced, helping customers find products faster and improving conversion rates in digital channels. This is especially relevant in categories such as fashion and grocery, where purchasing decisions are frequent and often driven by preference.
However, adoption levels vary. Larger retailers with stronger data infrastructure are moving faster, while smaller firms often face challenges related to systems integration and investment capacity.
Scaling challenge
Despite growing investment, scaling AI across retail organisations remains difficult.
The report highlights legacy IT systems and fragmented data as major barriers. Many retailers still operate with disconnected platforms, limiting the ability to apply AI consistently across functions.
Skills shortages also remain a constraint. Demand for data specialists and AI engineers continues to exceed supply in many European markets, prompting some companies to work with external technology partners to accelerate deployment.
Governance is becoming more important as AI use expands. Retailers are paying closer attention to data privacy, transparency and regulatory compliance, particularly within European frameworks.
Overall, the analysis suggests that AI in retail Europe is moving into a more mature phase of adoption, with investment rising and use cases expanding. The pace of change will depend on how quickly retailers can modernise systems, build skills and integrate AI across their operations.
