Bridging the AI skills gap in Europe: a detailed analysis of AI skills and roles

Authors Willemijn van Haeften, Ran Zhang, Sabine Boesen-Mariani, Xander Lub, Pascal Ravesteijn, Paul Aertsen
Published in 37th Bled eConference – Resilience Through Digital Innovation: Enabling the Twin Transition: June 9 – 12, 2024, Bled, Slovenia, Conference Proceedings
Publication date 2024
Research groups Process Innovation and Information Systems
Type Lecture

Summary

This study provides a comprehensive analysis of the AI-related skills and roles needed to bridge the AI skills gap in Europe. Using a mixed-method research approach, this study investigated the most in-demand AI expertise areas and roles by surveying 409 organizations in Europe, analyzing 2,563 AI-related job advertisements, and conducting 24 focus group sessions with 145 industry and policy experts. The findings underscore the importance of both general technical skills in AI related to big data, machine learning and deep learning, cyber and data security, large language models as well as AI soft skills such as problem solving and effective communication. This study sets the foundation for future research directions, emphasizing the importance of upskilling initiatives and the evolving nature of AI skills demand, contributing to an EU-wide strategy for future AI skills development.

Downloads en links

On this publication contributed

  • Ran Zhang
    Ran Zhang
    • Lecturer-researcher
    • Research group: Organisations in Digital Transition
  • Xander Lub
    Xander Lub
    • Professor
    • Research group: Organisations in Digital Transition
  • Pascal Ravesteijn | Professor | Process innovation and information systems
    Pascal Ravesteijn
    • Professor
    • Research group: Process Innovation and Information Systems

Language English
Published in 37th Bled eConference – Resilience Through Digital Innovation: Enabling the Twin Transition: June 9 – 12, 2024, Bled, Slovenia, Conference Proceedings
ISBN/ISSN URN:ISBN:978-961-286-871-0
Key words AI skills, AI roles, Europe, workforce development, mixed-method research
Digital Object Identifier 10.18690/um.fov.4.2024

Process Innovation and Information Systems