Learning for AI in Industrial Settings: the Importance of Transversal Skills for AI in the Metallurgy Sector

Purpose - The authors consider what kind of knowing and learning is required in the emerging age of intelligent machines in the industrial sector. The paper derives from a project that aims to integrate a semi-automated artificial intelligence (AI) system to optimise production processes in European metallurgy industry production, in line with environmental, economic and quality parameters. The authors consider the skills and training implications that flow from anticipated AI technology insertion into the specific production contexts of four project plants (France, Italy, Poland and Spain) of two participating companies, focusing on transversal skills. Design/methodology/approach - The authors identify skills and training needs for workers using desk-based research, observations, incorporating discussions with workers in situ, and interviews with employees, considering the diverse needs of the companies using the platform. Findings - The authors identify the need for a range of transversal skills and propose a three-pillar framework for understanding skills and training activities, including: the skills requirements related to the operation of a specific digital system or other technology (Pillar 1); specific transversal skill requirements arising from the integration of digital systems and other technology into specific production contexts (Pillar 2); and the general transversal skills required for wider digital transformation of companies and the integration of technology into wider organisational contexts (Pillar 3). Originality/value - This paper provides a case study of an energy-intensive-industry's engagement with AI and an analysis of the digital transformation of the European metallurgy sector. The authors argue that transversal skills are becoming increasingly important in the human-centred manufacturing workplace.