Copyright © 2025 Authors retain the copyright of this article. This article is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

@article{189724,
        author = {Shashikala B G},
        title = {Predictive AI Models for Employee Mental Health: A Framework for Corporate Wellness},
        journal = {International Journal of Innovative Research in Technology},
        year = {2025},
        volume = {12},
        number = {8},
        pages = {320-322},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=189724},
        abstract = {The rising prevalence of mental health challenges in the workplace necessitates proactive approaches to employee well-being. Predictive artificial intelligence (AI) provides the potential to identify early warning signs of stress, burnout, and other psychological risks by analysing multimodal data, including psychometric assessments, digital behaviour patterns, physiological signals, and organizational metrics. This conceptual paper presents a framework for the integration of predictive AI within corporate wellness programs, emphasizing organizational, psychological, and ethical dimensions. The framework outlines critical components such as principled data acquisition, predictive modelling, human-in-the-loop interventions, ethical governance, and continuous evaluation. By synthesizing recent literature (2023–2025), this study highlights the importance of trust, autonomy, transparency, and fairness in implementing AI-driven mental health solutions. The proposed framework offers guidance for organizations, HR practitioners, and policymakers to design AI-enabled wellness initiatives that are both effective and ethically responsible. Recommendations for future empirical validation are discussed to facilitate iterative refinement and alignment with employee well-being objectives.},
        keywords = {Predictive AI, Employee Mental Health, Corporate Wellness, Organizational Trust, Ethical AI},
        month = {December},
        }