HUMAN CAPITAL DEVELOPMENT IN THE TRANSITION FROM INDUSTRY 4.0 TO INDUSTRY 5.0: ETHICAL, EDUCATIONAL, REGULATORY PERSPECTIVES

Abstract

This study focuses on the transition of European industry from Industry 4.0 to Industry 5.0, examining the role of trustworthy artificial intelligence (AI), human–machine collaboration and the regulatory and socio-economic requirements of sustainable development. Key enabling technologies – such as artificial intelligence, the Internet of Things (IoT), big data analytics, blockchain, and additive manufacturing – are examined, as well as their role in ensuring the transparency, accountability, and adaptability of production value chains. Methodology. This study employs a systematic review of the current academic literature on Industry 4.0/5.0 technologies, EU regulatory frameworks and practical implementation cases. Based on this analysis, it develops a conceptual framework of trust in AI within the context of Industry 5.0, integrating the dimensions of ethics, safety and governance. The main challenges and opportunities for technology integration in industrial ecosystems are synthesised and presented. The research also proposes a set of measurable indicators for evaluating the adaptability, data transparency, security, accountability and human oversight of industrial systems. The objective of the present article is twofold: firstly, to identify the fundamental requirements for the implementation of integrated technologies within the European industrial sector; and secondly, to develop a recommendation framework for the realisation of Industry 5.0. The latter is defined as the combination of technological innovation with the social, ethical and legal dimensions of industrial transformation. Results. The study identifies the main barriers to effective integration as being data governance, process explainability, trust in AI systems and accountability for automated decisions. It proposes a multi-level trust framework encompassing the following dimensions: data transparency, explainability and auditability, security and privacy, human control and accountability, and standardisation and certification. The findings demonstrate that integrating AI with the Internet of Things (IoT), edge computing and big data analytics enhances the adaptability and product quality of manufacturing systems, but this requires robust change management processes, workforce training and appropriate regulatory support. If implemented through practical monitoring instruments and applied industrial cases, EU regulatory frameworks can drive this transformation. Conclusion. A resilient transition to Industry 5.0 requires a comprehensive approach that combines technological modernisation with social and ethical norms, human capital development and robust legal regulation. Institutionalising and adhering to the principles of AI trust, explainability and accountability is crucial for achieving sustainable industrial growth and maintaining the global competitiveness of European manufacturing in the new industrial era.