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AI IN OH: HYPE, HOPE, OR HERE TO STAY? NAVIGATING THE ETHICAL AND PRACTICAL CHALLENGES OF AI INTEGRATION IN OCCUPATIONAL HEALTH

1. Black¹, M. W. Johnson², J. O’Neill³, M. Healey⁴

¹Buckinghamshire Healthcare NHS Trust, UK

²University of Manchester, UK

³Deputy Head of National School of Occupational Health NHSE WT&E, UK

⁴GSK, London, UK

Background

Artificial Intelligence (AI) is rapidly emerging in occupational health (OH), promising efficiencies in administrative workflows, predictive analytics, and clinical decision-making. However, AI adoption in OH remains fragmented, with professionals expressing both enthusiasm and scepticism. While some see AI as a transformative tool, others fear its implications for professional roles, ethical decision-making, and patient safety. This presentation explores whether AI in OH is an overhyped trend, a promising innovation, or an inevitable shift in practice, with survey data.

Aim

This study aimed to assess the real-world engagement of OH professionals with AI, distinguishing between current usage, future aspirations, and perceived barriers.

Methods

A national survey was conducted among OH professionals, including physicians, nurses, physiotherapists, and occupational therapists. The survey captured:

• Current AI use in OH (e.g., documentation, automation, clinical applications).
• Perceived opportunities and risks.
• Readiness for AI-driven transformation.
• Expectations for regulation, training, and ethical oversight.

Quantitative data were analyzed using descriptive statistics, while qualitative responses were thematically examined.

Results

Findings indicate that AI’s role in OH is evolving but remains underdeveloped:

• AI is Here, but Not Yet Transformative
• The Biggest Barriers are Human, Not Technical:
• Skepticism Over ‘AI-Driven Care’
• Training & Governance are Essential

Conclusions

AI is no longer a futuristic concept in OH—it is already influencing practice. However, for AI to move beyond automation and into clinical decision-making, the profession must address significant ethical, regulatory, and practical concerns. Without clear governance and practitioner training, AI in OH risks remaining a hyped technology with limited real-world value.

References:

1. Floridi, L. & Cowls, J. (2019) ‘A unified framework of five principles for AI in society’, Harvard Data Science Review, 1(1). Available at: https://doi.org/10.1162/99608f92.8cd550d1
2. Morley, J., Floridi, L., Kinsey, L. & Elhalal, A. (2020) ‘From what to how: An initial review of publicly available AI ethics policies’, Science and Engineering Ethics, 26, pp. 2141–2178. Available at: https://doi.org/10.1007/s11948-020-00213-5
3. Royal Society (2023) The AI Revolution in Healthcare: Opportunities and Challenges for the NHS. London: The Royal Society. Available at: https://royalsociety.org/ai-healthcare
4. Topol, E. (2019) Deep Medicine: How Artificial Intelligence Can Make Healthcare Human Again. New York: Basic Books.
5. UK Government (Office for AI & NHS AI Lab) (2021) Artificial Intelligence in Healthcare: Policy, Regulation & Implementation Strategies. London: HM Government. Available at: https://www.gov.uk/government/publications/ai-in-healthcare