Collaborative development of AI capabilities in SMEs

We applied for the CoDeAI project to close the AI capability gap between large enterprises and SMEs, which often lag in digital transformation due to limited resources. This gap dampens their innovation and competitiveness. By equipping future SME employees and leaders with AI knowledge and skills, we aim to foster an ecosystem where SMEs can effectively adopt AI technologies, enhancing their productivity and innovation potential. AI is a key driver of digital transformation, yet while large enterprises have advanced their AI capabilities, SMEs struggle due to limited resources and awareness, impacting their future prospects. As AI tools become more prevalent, it's essential that SMEs understand and adopt these technologies. Educating students, potential future SME employees or founders, with AI skills is vital to addressing this gap. To address these needs we extended the VOIL platform (voil-plattform.eu)with AI training tailored for SMEs. This includes an AI use cases, success stories, and a benchlearning framework to guide SMEs in adopting AI. Additionally, we aim to establish an innovation environment that supports collaboration between universities, SMEs, and large enterprises, focusing on the specific needs of AI technology.

In our project we wanted to achieve four key goals: - Developing AI Training for SMEs: Create an AI training package tailored for SMEs, focusing on advances in tools like AutoML which now make it accessible to people without in depth AI knowledge. The training will be based on insights from SME studies, fostering digital capability across sectors. - Elaborating AI Use Cases in SMEs: Conducting workshops and feasibility studies, resulting in a detailed list of AI use cases and four technology case studies. This effort strengthens collaboration between universities and SMEs and informs higher education curricula. - Revising the Digital Maturity Assessment: Building on VOIL’s framework, we focused on AI capabilities to develop a benchlearning framework. This integrates insights from technology case studies and previous evaluations. - Creating a Joint Innovation Space: We established a collaborative innovation environment that supports the co-creation of AI-driven business models. This space extends the VOIL platform, fostering cross-sector collaboration between HEIs, SMEs, and large enterprises across Europe. This initiative aimed to build an ecosystem that nurtures the skills and experience necessary for AI-based innovation.

The CoDeAI project produced several concrete outputs and results: - Development of an AI training package, now available on the CoDeAI platform, an evolution of the VOIL platform (established in a previous Erasmus+ project). - Involved 104 representatives from 89 SMEs in our workshops and ideated 66 AI use cases with them - Completed four technology case studies on the use of AutoML in SMEs. - Advanced the digital maturity assessment by creating a benchlearning manual. - Established a Joint Innovation Space on the CoDeAI platform to foster collaboration. - Conducted extensive dissemination activities, including publications and events, reaching various sectors, target groups, and countries (details in appendix).