Helping Europe’s small retailers get to grips with AI
AI could help retailers forecast demand, improve customer service and cut waste. But for Europe’s smaller shops, adopting the technology can be easier said than done. The EU-funded INAIR(opens in new window) project set out to bridge this gap by identifying the skills retailers need and developing accessible training to help them put AI into practice. Coordinated by Italian innovation SME Lascò(opens in new window), the project brought together partners from five European countries: Germany, Italy, Cyprus, Poland and Romania. “Our research showed that AI adoption in retail micro, small and medium-sized enterprises is closely tied to everyday organisational constraints,” says Miriam Lanzetta, head of international projects at Lascò. “Businesses see AI as a way to save time, ease staff shortages and support routine work, yet limited budgets, time and expertise also make adoption difficult.”
From technical knowledge to a digital mindset
The INAIR team found that being AI-ready means more than knowing how to use a particular tool. Retailers also need to understand AI-generated results, recognise their limitations and judge when they can be trusted. Managers must be able to identify useful applications, assess risks and help staff adapt to new ways of working, explains Lanzetta. To address these needs, INAIR developed an AI Core Curriculum(opens in new window) comprising 16 learning blocks across foundation, intermediate and advanced levels. An online assessment tool(opens in new window) helps users identify their existing skills and access a learning pathway tailored to their role, experience and business needs. The training resources cover topics ranging from data-driven decision-making and customer engagement to trustworthy AI and sustainability. Interactive quizzes, simulations, games and real-world examples are intended to make the subject accessible to people without a technical background.
Putting AI to work in the shop
Inventory management illustrates how AI can deliver practical benefits. In a German retail business the project studied, employees traditionally relied on experience to decide what to order, sometimes leading to excess stock or shortages. An AI-based system used historical sales data and external factors to forecast demand and suggest daily orders. Staff initially remained cautious, manually adjusting the recommendations. As the forecasts proved reliable, however, they increasingly trusted the system, reducing time spent on calculations and freeing them to focus on sales. AI can also help retailers optimise logistics, allocate resources and improve energy efficiency. However, INAIR does emphasise the need to consider the environmental footprint of AI itself, including its energy use and computing requirements.
Training that can reach more retailers
The project tested its learning programme with more than 240 registered users. Among survey respondents, 88 % reported a better understanding of AI in retail, while 85 % felt more confident about considering or adopting AI-based solutions. A further 72 % said they intended to integrate AI tools or approaches into their work. “These results are evidence of increased readiness and perceived applicability within the participant sample,” says Lanzetta, while also noting that follow-up would be needed to establish how often intentions lead to lasting changes in practice. With the project completed, the next challenge is to make its resources available to more businesses. The materials are multilingual and modular, allowing vocational training providers, chambers of commerce and business associations to incorporate them into courses and workplace learning. For smaller retailers, the aim is not to adopt AI for its own sake, but to develop the skills to decide where it can genuinely help – and how to use it responsibly.
