Artificial Intelligence and Occupational Health: Opportunities and Challenges for Prevention in the Digital Age
- Pietro Ponzoni
- May 17
- 4 min read
The introduction of Artificial Intelligence (AI) systems in the workplace represents one of the most significant transformations in employment relationships.
This evolution, sometimes referred to as AI-based Worker Management (AIWM), involves extensive – often real-time – data collection about the work environment, workers, the tasks performed, and the digital tools used.
Such data feed AI models that support or make decisions related to worker management. While AI can offer significant benefits for occupational health and safety (OSH), potential risks must not be underestimated, especially those affecting mental health and overall well-being.
The Regulatory Framework and New Challenges for Occupational Medicine
The European and national regulatory context is rapidly evolving. Regulation (EU) 2024/1689 (AI Act) imposes strict obligations on providers of high-risk AI systems, while employers fall within the scope of deployers.
This approach aligns with the organizational model of the Occupational Health and Safety Management System (OHSMS).
In Italy, Article 2087 of the Civil Code links the obligation of safety to technological progress, potentially requiring the use of AI if it becomes widespread and beneficial for improving working conditions. Legislative Decree no. 81/2008, with its focus on work organization, also provides a solid foundation for integrating AI into risk assessments.
AI can support the drafting of the Risk Assessment Document (DVR) by cross-referencing data on tasks, equipment, substances, and environments with statistical data (e.g., past accidents). However, a fully automated process remains inadequate: active involvement of the H&S Officer (RSPP), properly trained, is essential.
Occupational Medicine must also take into account, in addition to physical risks, the psychosocial risks arising from AI use, in line with the extended definition of health in Legislative Decree 81/2008.
Opportunities of AI for Prevention and Occupational Medicine
Artificial Intelligence can become a valuable ally for OSH and prevention. Key opportunities include:
Replacement in hazardous tasks: sensors and automation in dangerous or physically demanding environments.
Access and equipment control: biometric recognition and skill verification for machinery use.
Risk assessment support: predictive analytics and improvement of the DVR quality.
Monitoring of procedures and PPE: checking the correct and continuous use of protective equipment.
Ergonomics: physical strain detection through smart clothing.
Immersive training: virtual/augmented reality for safety training, also effective for foreign or young workers.
Workplace accessibility: technologies that facilitate employment of elderly or disabled workers.
Support for inspections: data analysis to optimize inspections and supervision.
Risks and Challenges Arising from AI Use
Alongside the benefits, AI introduces new risks, especially of a psychosocial nature:
Mental health risks: increased anxiety, stress, and workplace discomfort.
Increased work pressure: loss of autonomy, algorithm-imposed work pace.
Surveillance and loss of autonomy: continuous monitoring, erosion of trust.
Social isolation: reduced peer interaction.
Uncertainty and stress: constant monitoring and unpredictable schedules.
Blurred boundaries between private life and work: greater intrusiveness of technologies.
Physical risks: dangers related to malfunctioning intelligent machines.
The combination of these factors can have a greater overall impact than each individual risk alone.
The Involvement of Workers and Their Representatives
Active involvement of workers and their representatives (e.g., H&S representatives – RLS) is crucial for participatory prevention, as established by Legislative Decree no. 81/2008.
Participation can occur through information, consultation, and negotiation. However, the AI context introduces new difficulties:
Invisibility of AI technologies: hard to detect their impact on OSH.
Algorithm opacity ("Black Box"): technical complexity and lack of transparency.
Continuous AI evolution: constantly changing work environments.
Power and skill imbalance: difficulties for representatives to intervene effectively.
Nevertheless, there are virtuous experiences at company and contractual levels, where bilateral commissions assess the AI–OSH relationship to promote ethical and human-centered use.
Accountability and Future Perspectives in AI and Occupational Health
The issue of accountability for damage caused by AI is complex. In labor law, the employer remains responsible for any work accidents or occupational diseases caused by AI systems, even non-deterministic ones.
The AI system is part of the company organization: it is not a third party. The user – the human being – retains legal and managerial responsibility.
Innovation Must Be Human-Centered
To ensure that AI benefits outweigh the risks, a human-centered approach focused on worker health and well-being is essential.
This requires:
Adaptation of legislation
Specific training for workers and RLS
Internal systems for feedback and near-miss detection
Constant updates in Occupational Medicine with new skills
Conclusion
Artificial Intelligence is a powerful lever for preventive innovation in occupational health and safety.
But to avoid becoming a tool of control or dehumanization, a proactive, participatory, and human-centered approach is essential.
Only through the active involvement of all stakeholders – workers, employers, representatives, technology providers – and the continuous updating of regulatory and training frameworks, can we ensure that innovation truly serves workers’ health.
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Sources:
EU-OSHA (2024) Worker management through AI technology: development impacts workers and their safety and health
EU-OSHA (2022) Artificial intelligence for worker management: an overview
Regulation (EU) 2024/1689 (the so-called A.I. Act)
Legislative Decree no. 81/2008 and subsequent amendments (various articles, e.g., art. 2, 17, 28, 73, 69 ff., 23, 57, 71, 44, 20)
