Periodic Reporting for period 1 - INAIR (INcreasing the uptake of AI technology in Retail)
Okres sprawozdawczy: 2024-01-01 do 2025-06-30
Technological advancements and changes in consumer behavior following the COVID-19 outbreak have required retailers to accelerate their digital transformation in order to deliver differentiated consumer experiences and interactions, including through AI-driven solutions. Nevertheless, the AI adoption rate remains significantly low across the EU, with the European wholesale and retail trade sector ranks third to last, with only 6% of enterprises using AI (DESI 2022).
While the global market for AI in retail is growing fast, the lack of a skilled workforce to support AI integration not only hinders market growth in the EU but also poses a significant risk for European SMEs. Without action, they may fall behind global competitors and miss out on key opportunities for growth and efficiency. Additionally, AI can be a powerful tool for making businesses more sustainable: companies around the world are successfully using AI to reduce emissions in production and operations, optimise supply chain management, and improve waste reduction.
In this context, INAIR aims to reduce the AI skills gap among European micro, small, and medium-sized retailers, enabling them to harness the potential of AI to green their businesses, enhance their global competitiveness, and ultimately contribute to achieving the Digital Decade target of more than 75% of European companies adopting AI technologies by 2030.
To achieve such aim, the project consortium has been working to pursue the following objectives:
- Identify AI-related skills needs and gaps in the retail sector;
- Develop and deliver a hybrid AI skills development programme for retail MSMEs;
- Create training resources to support educators and VET providers in delivering AI-related training, integrating the project AI skills development solutions into their work.
While the global market for AI in retail is growing fast, the lack of a skilled workforce to support AI integration not only hinders market growth in the EU but also poses a significant risk for European SMEs. Without action, they may fall behind global competitors and miss out on key opportunities for growth and efficiency. Additionally, AI can be a powerful tool for making businesses more sustainable: companies around the world are successfully using AI to reduce emissions in production and operations, optimise supply chain management, and improve waste reduction.
In this context, INAIR aims to reduce the AI skills gap among European micro, small, and medium-sized retailers, enabling them to harness the potential of AI to green their businesses, enhance their global competitiveness, and ultimately contribute to achieving the Digital Decade target of more than 75% of European companies adopting AI technologies by 2030.
To achieve such aim, the project consortium has been working to pursue the following objectives:
- Identify AI-related skills needs and gaps in the retail sector;
- Develop and deliver a hybrid AI skills development programme for retail MSMEs;
- Create training resources to support educators and VET providers in delivering AI-related training, integrating the project AI skills development solutions into their work.
During the first half of the project, the INAIR consortium carried out research, co-creation and design activities aimed at analysing sector-specific skills needs and laying the foundations for the development of educational tools tailored to retail MSMEs.
A central focus was the implementation of a transnational research work, which employed a multi-method approach to examine AI adoption, digital readiness and AI skill requirements across partner countries. The analysis combined a bibliometric and text-mining review of 1,699 academic publications and 100+ policy documents, statistical data from national and EU-level sources, and the collection and analysis of 44,000+ AI-related job advertisements. Additionally, 13 use cases and 3 best practices were documented to illustrate practical applications of AI in retail. Stakeholder input was also gathered through 9 co-creation workshops with 92 participants and supplemented by expert interviews and a complementary survey. These activities provided qualitative insights into barriers to AI adoption, workforce challenges, and strategic priorities.
Building on these findings, the consortium designed an AI Core Curriculum and Skills Assessment Tool for workers and owners of retail businesses. A methodological and instructional framework was established, drawing on the fractal learning model. This framework informed the structure and logic of the curriculum’s learning blocks and the development of differentiated learning pathways based on learner profiles.
In parallel, the consortium developed a methodology and structure for an AI Skills Assessment Tool, designed to support both entry-level placement and final learning outcome evaluation. The tool was developed using established principles from adult learning and competence-based education and includes profiling features and role-specific assessments to personalise curriculum access.
Hence, by June 2025 (M18), the consortium had completed the core research and design phases and established the operational and pedagogical foundations for developing and piloting the INAIR training programme and supporting tools.
A central focus was the implementation of a transnational research work, which employed a multi-method approach to examine AI adoption, digital readiness and AI skill requirements across partner countries. The analysis combined a bibliometric and text-mining review of 1,699 academic publications and 100+ policy documents, statistical data from national and EU-level sources, and the collection and analysis of 44,000+ AI-related job advertisements. Additionally, 13 use cases and 3 best practices were documented to illustrate practical applications of AI in retail. Stakeholder input was also gathered through 9 co-creation workshops with 92 participants and supplemented by expert interviews and a complementary survey. These activities provided qualitative insights into barriers to AI adoption, workforce challenges, and strategic priorities.
Building on these findings, the consortium designed an AI Core Curriculum and Skills Assessment Tool for workers and owners of retail businesses. A methodological and instructional framework was established, drawing on the fractal learning model. This framework informed the structure and logic of the curriculum’s learning blocks and the development of differentiated learning pathways based on learner profiles.
In parallel, the consortium developed a methodology and structure for an AI Skills Assessment Tool, designed to support both entry-level placement and final learning outcome evaluation. The tool was developed using established principles from adult learning and competence-based education and includes profiling features and role-specific assessments to personalise curriculum access.
Hence, by June 2025 (M18), the consortium had completed the core research and design phases and established the operational and pedagogical foundations for developing and piloting the INAIR training programme and supporting tools.
INAIR has generated results that advance knowledge on AI skills needs and gaps in retail, and contribute beyond the state of the art to AI skills development for MSMEs in the sector.
KEY RESULTS
[1] AI Skills Needs and Gaps Analysis Report: Offers a detailed overview of current and emerging AI-related skill requirements across five EU countries. It identifies relevant technical and transversal skills and presents use cases and best practices demonstrating AI application in retail settings.
[2] AI Core Curriculum: Developed based on the research findings, this structured learning framework spans three proficiency levels (foundational, intermediate, and advanced) and integrates both technical and ethical aspects of AI. It follows principles of modularity and openness to support scalability and adaptation.
[3] AI Skills Assessment Tool: Enables users to evaluate their skills against the curriculum’s learning objectives. Developed using a published methodological framework, the tool includes both ex ante and ex post assessments, customised for different roles in retail businesses.
[4] Map of Trustworthy AI Tools: Provides a curated list of AI tools relevant for the retail sector, assessed using criteria based on the Ethics Guidelines for Trustworthy AI. It supports SMEs in making informed, responsible technology choices.
These results contribute new evidence, methods and openly accessible tools for addressing the AI skills gap in the retail sector. They support the uptake of digital technologies among smaller enterprises, enhance the capacity of education and training providers to deliver relevant upskilling opportunities, and align with broader EU objectives related to digital transformation and SME competitiveness.
KEY RESULTS
[1] AI Skills Needs and Gaps Analysis Report: Offers a detailed overview of current and emerging AI-related skill requirements across five EU countries. It identifies relevant technical and transversal skills and presents use cases and best practices demonstrating AI application in retail settings.
[2] AI Core Curriculum: Developed based on the research findings, this structured learning framework spans three proficiency levels (foundational, intermediate, and advanced) and integrates both technical and ethical aspects of AI. It follows principles of modularity and openness to support scalability and adaptation.
[3] AI Skills Assessment Tool: Enables users to evaluate their skills against the curriculum’s learning objectives. Developed using a published methodological framework, the tool includes both ex ante and ex post assessments, customised for different roles in retail businesses.
[4] Map of Trustworthy AI Tools: Provides a curated list of AI tools relevant for the retail sector, assessed using criteria based on the Ethics Guidelines for Trustworthy AI. It supports SMEs in making informed, responsible technology choices.
These results contribute new evidence, methods and openly accessible tools for addressing the AI skills gap in the retail sector. They support the uptake of digital technologies among smaller enterprises, enhance the capacity of education and training providers to deliver relevant upskilling opportunities, and align with broader EU objectives related to digital transformation and SME competitiveness.