Exploring Human–AI Dynamics in Enhancing Workplace Health and Safety: A Narrative Review

Jakub Fiegler-Rudol (), Karolina Lau, Alina Mroczek and Janusz Kasperczyk
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Jakub Fiegler-Rudol: Student Scientific Society at the Department of Environmental Medicine and Epidemiology, Faculty of Medical Sciences in Zabrze, Medical University of Silesia, 41-800 Katowice, Poland
Karolina Lau: Department of Environmental Medicine and Epidemiology, Faculty of Medical Sciences in Zabrze, Medical University of Silesia, 41-800 Katowice, Poland
Alina Mroczek: Department of Environmental Medicine and Epidemiology, Faculty of Medical Sciences in Zabrze, Medical University of Silesia, 41-800 Katowice, Poland
Janusz Kasperczyk: Department of Environmental Medicine and Epidemiology, Faculty of Medical Sciences in Zabrze, Medical University of Silesia, 41-800 Katowice, Poland

IJERPH, 2025, vol. 22, issue 2, 1-14

Abstract: Background: Artificial intelligence (AI) is revolutionizing occupational health and safety (OHS) by addressing workplace hazards and enhancing employee well-being. This review explores the broader context of increasing automation and digitalization, focusing on the role of human–AI interaction in improving workplace health, safety, and productivity while considering associated challenges. Methods: A narrative review methodology was employed, involving a comprehensive literature search in PubMed, Embase, and Scopus for studies published within the last 25 years. After screening for relevance and eligibility, a total of 52 articles were included in the final analysis. These publications examined various AI applications in OHS, such as wearable technologies, predictive analytics, and ergonomic tools, with a focus on their contributions and limitations. Results: Key findings demonstrate that AI enhances hazard detection, enables real-time monitoring, and improves training through immersive simulations, significantly contributing to safer and more efficient workplaces. However, challenges such as data privacy concerns, algorithmic biases, and reduced worker autonomy were identified as significant barriers to broader AI adoption in OHS. Conclusions: AI holds great promise in transforming OHS practices, but its integration requires ethical frameworks and human-centric collaboration models to ensure transparency, equity, and worker empowerment. Addressing these challenges will allow workplaces to harness the full potential of AI in creating safer, healthier, and more sustainable environments.

Keywords: occupational health and safety; artificial intelligence; human–AI interaction; workplace ergonomics; predictive analytics; worker autonomy; ethical frameworks; wearable technology (search for similar items in EconPapers)
JEL-codes: I I1 I3 Q Q5 (search for similar items in EconPapers)
Date: 2025
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