A Review of Human-Centric AI in Industry 5.0: Integrating Data Science with Mechanical Automation

Abstract

The shift towards Industry 5.0 from Industry 4.0 represents the paradigm shift in industry, not only highlighting automation and efficiency but also human-centered innovation, resilience, and sustainability. Central to this transformation is the synergy between Artificial Intelligence (AI) and Data Science with mechanical automation to produce intelligent, adaptive, and collaborative industrial environments. This review identifies the new frontier of human-centered AI in Industry 5.0 as the intersection of data-driven intelligence, mechanical engineering, and human-robot collaboration (HRC). It methodically examines how models of AI/Machine Learning (ML), such as explainable AI (XAI), prediction analytics, and systems of human-in-the-loop are redefining mechanical automation into cognitive, user-oriented settings. A systematic methodology based on major scientific databases was employed in order to choose more than 150 high-impact articles published between the years 2015 and 2025. Fundamental enabling technologies like collaborative robots (cobots), digital twins, cyber-physical systems, and edge AI are discussed in detail, with special emphasis on how they facilitate ergonomic, transparent, and secure interaction between humans and machines. In addition, the review discusses how data science frameworks are implemented to maximize the performance, trust, and well-being of humans in automated machinery systems. The paper also identifies some key missing gaps, such as the absence of scalable explainability of industrial AI, poor integration of ergonomic models with robotics, and difficulty in implementing real-time feedback systems from humans. In overcoming these challenges, this review provides a research and development pathway towards ethically oriented, resilient, and inclusive production. The research is expected to be used as a basis of reference by academics, engineers, and policy-makers who are leading the humanity-oriented shift of smart production systems.