AI skills SMEs need to stay competitive

Artificial intelligence (AI) is transforming the manufacturing industry – from predictive maintenance and quality control to sustainability. For small and medium-sized enterprises (SMEs), staying on the sidelines of digitalisation means losing competitiveness. As technical expertise is needed to develop AI solutions, deploying them should be accessible for professionals from diverse backgrounds – for SMEs it remains a challenge.

More than 26 million SMEs represent 99% of all businesses in the EU, according to the European Commission. Despite growing AI opportunities, the manufacturing industry is under pressure to adapt quickly. However, SMEs often lack the skills, confidence and resources to adopt new solutions. This is why the EIT Manufacturing-funded project AISME developed a learning path tailored to SMEs, including Essentials of AI in Manufacturing, Explainability, Safety & Reliability, as well as Maintainability in AI Systems.

Vinicius Affonso de Carvalho, Research Engineer in Pedagogy and International Development at Grenoble INP, shares the inspiration behind the AISME (Supporting AI Solutions in SMEs) training that builds not just knowledge, but also trust and autonomy for SMEs to adopt AI.

Overcoming digitalisation barriers with a blended learning path

Only 13.5% of all EU enterprises had adopted at least one AI technology in 2024. In the manufacturing sector, AI software or systems were used mostly for marketing and sales, accounting for 27.11%, followed by 26.23% for production processes, according to Eurostat.

To break down the barriers in AI adoption by SMEs, like limited skills and high costs, the AISME project offers flexible, targeted and applied training rooted in real use cases. A blended learning programme was developed by partnering with academia and industry experts.

Grenoble INP coordinated the project consortium and designed the AISME course methodology. Together with the University of Groningen and the Faculty of Engineering of the University of Porto (FEUP), they developed educational content, with each university focusing on key aspects: the University of Groningen carried out a European skills gap analysis and defined learning priorities, while FEUP tailored content and tools for AI in manufacturing. InTechCentras analysed Lithuanian and Eastern European needs to adapt the training for SMEs. The training was tested by SMEs, like Technogaja UAB (Lithuania) and piloted by ISP System (France) in real industrial environments. Aerospace Valley ensured the training addressed industry challenges and broadened outreach for professionals.

Making AI understandable for non-specialists is a challenge

Talking about the motivation behind the course, Carvalho noted: “Digital transformation is about people.” Making AI understandable and practical for non-specialists in SMEs was the core challenge for the team. To tackle it, the team developed a modular blended learning model tailored to SME realities through co-design with end-users and use-case-driven content.

The course is ideal for managers, engineers, or technicians with a basic understanding of digital tools and a keen interest in applying AI to improve operations. “Seeing non-expert SME employees confidently engage with AI concepts and express excitement about applying them was the moment that truly confirmed AISME was solving the right problem, in the right way,” highlighted Carvalho as a sign that the team was on the right track.