Artificial intelligence and occupational medicine

Abstract

Artificial intelligence is fundamentally reshaping occupational medicine through applications in automation, smart monitoring, extended reality training, algorithmic management, and digital work arrangements. The EASOM Summer School 2025 examined how AI technologies enhance occupational health systems by enabling real-time risk identification, predictive surveillance, and targeted interventions to prevent work-related accidents and diseases. Practical applications include smart personal protective equipment, wearable sensors, augmented reality training systems, and predictive diagnostics exemplified by noise-related hearing loss risk assessment. However, significant challenges accompany these opportunities: data quality concerns, new technological hazards, psychosocial risks including surveillance-related stress and work intensification, algorithmic bias, and accountability gaps. Implementation requires comprehensive governance frameworks emphasizing early worker involvement, privacy-by-design approaches, phased pilot programs, and human-centered practices that complement rather than replace traditional occupational safety measures. Professional responsibility and education demand new competencies in digital literacy, algorithmic critical thinking, and applied ethics while maintaining essential clinical judgment and empathy. AI offers unprecedented potential for protecting workers' health and safety when responsibly implemented within transparent frameworks, but poor management risks deepening inequalities and eroding established protections. Successful integration depends on multidisciplinary research, international cooperation, stakeholder engagement, and a commitment to human-centered occupational medicine that prioritizes worker dignity and wellbeing.