Artificial Intelligence and Workplace Safety: Prediction, Prevention, and the Management of Occupational Risks

Artificial Intelligence (AI) is rapidly reshaping the landscape of occupational health and safety, presenting transformative opportunities for predicting and preventing workplace incidents. In modern workplaces—evolving into complex socio-technical systems—AI-driven tools such as machine learning algorithms, wearable sensors, robotics, and computer vision are offering unprecedented capabilities for hazard detection, real-time condition monitoring, and predictive risk assessment. However, this technological evolution brings forth a range of challenges including issues of transparency, algorithmic fairness, data privacy, and the robustness of AI-enabled safety systems. Promising results have been demonstrated in real-time injury prediction and risk intervention; however, gaps remain in research of how to responsibly and effectively deploy AI without compromising ethical standards or worker well-being. As organizations accelerate digital transformation, refining the integration of AI to both enhance safety and address socio-technical risks is increasingly vital.

This Research Topic aims to investigate how artificial intelligence can revolutionize risk prediction, prevention strategies, and safety management across diverse occupational settings. One objective is to gather interdisciplinary perspectives and evidence on the effective and responsible use of AI for improving safety performance, reducing harm, and supporting transparent and equitable workplace practices. By drawing on engineering, occupational health, social sciences, and policy, this collection aims to develop a comprehensive understanding of best practices and governance models needed for the safe adoption of AI in workplace safety.

Submissions should address the challenges and opportunities that arise from deploying AI-driven prevention and safety management tools in real workplaces. To gather further insights in this area, articles addressing, but not limited to, the following themes are welcomed:

o AI-based prediction models for workplace injuries, incidents, and near-misses.

o Machine learning applications in exposure assessment and environmental risk monitoring.

o Wearables, biosensors, and computer vision for real-time safety surveillance.

o Human–AI interaction and decision-support systems in safety-critical tasks.

o Ethical, legal, and governance considerations regarding AI in occupational settings.

o Algorithmic bias, transparency, and interpretability in safety-related AI applications.

o Sector-specific solutions for high-risk industries (e.g., construction, manufacturing, healthcare).

o AI-driven approaches to Total Worker Health® and organizational well-being.

o Evaluation of AI-enabled safety interventions and their impact on safety culture.

o Data protection, digital monitoring, and psychosocial risks associated.

Keywords: AI in occupational safety, workplace safety, prediction of occupational risks, prevention of occupational risks, occupational risks, workplace accidents, environmental risk monitoring, high-risk industries

Important note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.