Artificial Intelligence in the Retail Sector

This report, developed as part of the Horizon Europe INAiR project, explains how retail—particularly SMEs—is preparing to implement AI-based solutions. It includes an overview of AI applications in key areas of the company, a diagnosis of the level of digitalization, and competency guidelines necessary for effective and scalable implementations. It is based on nine workshops, 13 in-depth interviews, an analysis of over 44,000 job postings, and a literature review. This approach combines the perspectives of employers, employees, technology advisors, and educators. The full English version is available on the project website.
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What exactly does the report contain?

AI Technology Map in Commerce

 The report organizes the most commonly used solution classes. It describes machine learning, deep learning, augmented intelligence, knowledge engines, natural language processing, computer vision, speech recognition, chatbots, process automation, and generative solutions. It embeds each technology into company processes, from knowledge and customer service to inventory and operations.

From data to decisions

 It shows where AI can truly help across the value chain: knowledge management, customer engagement and service, inventory and supply chain management, and operations optimization. It emphasizes the shift from "data" to on-the-job decisions.

The level of digitalization and contrasts in the EU

 The report presents digital intensity indicators (DII) and differences between countries. In Poland, 33 percent of retail companies have a high or very high DII, while Germany ranks much higher in the EU. Twenty-five percent of retailers in Germany and 12 percent in Poland sell via e-commerce. This illustrates the starting point and the potential for improvement.

AI in practice. Scale of adoption and application.

 In EU countries, 59 to 86 percent of retail companies are not yet using AI. The most common implementations are process automation, customer service, and first-time analytics applications. The report indicates that companies that implement AI are choosing areas with rapid, measurable returns.

The foundations without which AI will not work

 The cloud and the Internet of Things are crucial as a foundation for subsequent AI implementations. Italy: 58,4 percent of companies use the cloud, Germany: 41,9 percent, Romania: 13,8 percent. In Poland, IoT is used by approximately 11 percent of companies. The report shows that without these elements, AI implementations remain patchy and difficult to scale.

Competencies and the labor market

 An analysis of over 44 job postings shows that only 0,5 percent of job offers require AI-related competencies. Basic digital skills are widely sought after: Excel, ERP and CRM support, and working with e-commerce platforms and digital marketing tools. The conclusion: before advanced AI emerges, teams need to be "digitally ready" and their data organized.

Conclusions and recommendations for companies

 The report provides a list of conclusions: commerce is below average in terms of digitalization, the barriers are technological and mental, and AI won't exist without ERP, CRM, and e-commerce. It recommends strengthening foundations, starting with small usage scenarios, assigning ownership to metrics, and only merging islands once the impact is proven. It also includes practical training and organizational tips.


Why is the report important?

  • It provides a reliable starting point. It shows where we are and how conditions vary across countries, allowing us to plan actions that are appropriate to the company's realities.
  • It shifts the focus from technology to decisions. It teaches thinking in use cases that immediately connect data to action in the process.
  • It organizes the sequence of steps. First, data foundations and simple integrations, then the smallest pilots, and finally, combining what works.
  • It identifies the competencies needed "for today." It highlights how to train teams to use data and tools before more complex solutions emerge.
  • It provides a "language of conversation" with suppliers and within the team. Conclusions and checklists make it easier to assess readiness, costs, and risks, and to choose the right pace of implementation.