| Summary: | Purpose: This study investigates the transition from Industry 4.0 to Industry 5.0, focusing on the integration of artificial intelligence (AI), machine learning (ML), and the Internet of Things (IoT) to support human-centric, sustainable and resilient production systems. It aims to identify key trends, challenges and opportunities within this evolving industrial paradigm.
Design/methodology/approach: A scientometric approach was employed using bibliometric and co-word analysis to examine global scientific literature on Industry 5.0. The study maps the evolution of research and technological advancements across sectors such as manufacturing, education, supply chains, and disaster management.
Findings : The analysis highlights the growing importance of predictive maintenance, collaborative robots and cyber-physical systems in advancing sustainable and inclusive industrial practices. It also reveals increasing academic focus on ethical concerns such as workforce inclusion and data privacy. Emerging technologies like augmented reality and blockchain are identified as key enablers of Industry 5.0.
Social implications : The findings support the development of inclusive, human-centered technologies that enhance societal well-being and promote ethical digital transformation in educational and industrial contexts.
Originality/value: This study contributes to the field by offering a comprehensive scientometric overview of Industry 5.0 literature and its applications. It underscores the significance of interdisciplinary research and ethical frameworks in achieving balanced technological and societal progress. Moreover, this study bridges the gap between theory and practice by offering actionable insights for SMEs, healthcare and digital supply chains. It contributes a methodological framework applicable to other emergent interdisciplinary fields beyond Industry 5.0.
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