Mapping the Scientific Production on Artificial Intelligence Training for Workers in the Industrial Sector

Abstract

The advent of Artificial Intelligence (AI), based technologies within the industrial sector has precipitated profound and disruptive transformations in operational routines and work dynamics, exerting a direct influence on the skill profile required of workers. These changes directly impact the set of skills required of professionals, who now need to transcend traditional technical expertise and develop new dimensions of knowledge. Given this context, the objective of this study is to map national and international scientific production about AI literacy for industrial workers. This is narrative research whose purpose is to identify, as evidenced in the literature, both the gaps and opportunities for improvement in professional training. The study revealed that, despite growing industry investments in intelligent systems, initiatives aimed at cultivating AI literacy among non-specialist professionals continue to be neglected. Furthermore, the available courses show a low alignment with industrial practice and fail to adequately consider the sociocultural profile of participants. Research indicates that AI training should go beyond the acquisition of technical knowledge, encompassing the development of reflective, adaptive, and interventional skills. Moreover, the literature highlights the importance of integrating inclusive strategies that address cultural, generational, and skills-level diversity in industrial environments, as these factors directly influence engagement, learning outcomes, and the equitable distribution of opportunities in an AI-driven economy. The expected results of this research are to identify the main challenges that can support more effective and sustainable educational strategies for professional qualification in the use of AI in the industrial sector.