Artificial Intelligence in Occupational Mental Health Assessment: Applications, Predictive Potential, Methodological Challenges, and Responsible Implementation

Authors

• Julio Suárez Albanchez, University of Castilla-La Mancha, Paseo de la Universidad, 4, 13071, Ciudad Real, SpainFollow

Abstract

Background: Occupational mental health disorders represent a growing challenge for organizations worldwide. Artificial intelligence (AI) has emerged as a potential tool for improving the assessment and surveillance of psychosocial risks.
Methods: A critical narrative review of the literature on AI applications in occupational mental health was conducted, focusing on predictive models, methodological limitations, ethical risks, and governance challenges.
Results: Current evidence suggests that AI systems can support the prediction of burnout, stress, anxiety, and other mental health outcomes through machine learning, natural language processing, and behavioral analytics. However, important limitations remain regarding data quality, external validation, explainability, privacy, algorithmic bias, and workplace surveillance.
Conclusions: AI may enhance occupational mental health assessment when implemented as a decision-support tool under appropriate ethical and regulatory safeguards. Human oversight, transparency, and rigorous validation are essential prerequisites for responsible adoption.

Recommended Citation

Albanchez, Julio Suárez (2026) "Artificial Intelligence in Occupational Mental Health Assessment: Applications, Predictive Potential, Methodological Challenges, and Responsible Implementation," Mesopotamian Journal of Artificial Intelligence in Healthcare: Vol. 4: Iss. 1, Article 6.