25, May 2026

Generative AI Adoption and Employee Engagement in AI-Driven Organizations: An Integrated HRM and I/O Psychology Perspective

VOLUME-12; ISSUE-5; MAY-2026

Author(s): Dr. Chandra Babu Jangam

Authors Affiliations:

Superintendent, Internal Quality Assurance Cell (IQAC), Sri Krishnadevaraya University, Ananthapuramu, Andhra Pradesh, INDIA

DOIs:10.2015/IJIRMF/202605019     |     Paper ID: IJIRMF202605019


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The rapid integration of Generative Artificial Intelligence (AI) into organizational systems has significantly transformed contemporary workplace practices, employee roles and human resource management functions. As organizations increasingly adopt AI-driven technologies to enhance operational efficiency, innovation and decision-making, understanding their influence on employee engagement has emerged as a critical area of research within Human Resource Management and Industrial and Organizational Psychology. The present study developed an integrated HRM and I/O Psychology framework to examine the relationship between Generative AI adoption and employee engagement in AI-driven organizations.

The study explores how Generative AI-enabled work environments influence employees’ psychological experiences, behavioural outcomes and workplace engagement levels. Specifically, the research investigates the mediating role of psychological empowerment and the influence of organizational support, digital trust and human–AI collaboration in shaping employee engagement. The study is grounded in Social Exchange Theory and Job Demands–Resources Theory, which provide a theoretical foundation for understanding employees’ adaptive behaviours and motivational responses within technologically transformed workplaces.

A quantitative research design was adopted using structured questionnaires administered to employees working in AI-integrated organizations across multiple sectors. Data were collected from 356 employees working in AI-enabled organizations across IT, banking and healthcare sectors and analyzed using SPSS and Structural Equation Modelling (SEM). Statistical techniques such as correlation analysis, regression analysis and SEM were employed to examine the direct and indirect relationships among the study variables. The findings indicate that effective Generative AI adoption, when supported by employee-centric HRM practices and psychologically supportive organizational climates, positively contributes to employee engagement, workforce adaptability and organizational sustainability.

The study contributes to the emerging literature on AI-enabled organizational behaviour by integrating HRM and I/O Psychology perspectives into a unified conceptual framework. The findings provide valuable implications for managers, HR practitioners and policymakers in designing ethical, inclusive and human-centric AI strategies that promote employee well-being, engagement and long-term organizational effectiveness in the digital era.

Generative Artificial Intelligence (AI), Employee Engagement, AI-Driven Organizations, Human Resource Management (HRM), Industrial and Organizational Psychology, Psychological Empowerment, Human–AI Collaboration, Digital Trust, Organizational Support and Behavioural HRM.

Dr. Chandra Babu Jangam (2026); Generative AI Adoption and Employee Engagement in AI-Driven Organizations: An Integrated HRM and I/O Psychology Perspective, International Journal for Innovative Research in Multidisciplinary Field, ISSN(O): 2455-0620, Vol-12, Issue-5, Available on –   https://www.ijirmf.com/

  1. Dixit, A. (2024). The impact of artificial intelligence on digital employee engagement: The role of job autonomy and digital learning orientation. Prabandhan: Indian Journal of Management. https://doi.org/10.17010/pijom/2024/v17i5/173940
  2. Wang, Z., & Siau, K. (2024). Artificial intelligence, employee trust and workplace transformation: Emerging perspectives in organizational behaviour. Journal of Organizational Change Management, 37(2), 210–225. https://doi.org/10.1108/JOCM-08-2023-0251
  3. Zirar, A., Ali, S. I., & Islam, N. (2023). Worker and workplace artificial intelligence adoption: Review and research agenda. Technovation, 124, 102747. https://doi.org/10.1016/j.technovation.2023.102747
  4. Gayathiri, G., & Prabu, G. (2025). Artificial intelligence-driven human resource practices and employee well-being: Examining the mediating effect of employee engagement. Problems and Perspectives in Management, 23(4), 245–258. https://doi.org/10.21511/ppm.23(4).2025.18
  5. Jiang, Y. (2025). Leverage generative AI for human resource management: Opportunities and ethical challenges. The International Journal of Human Resource Management. https://doi.org/10.1080/09585192.2025.2544972
  6. Liu, Y. (2025). Generative AI adoption and employee outcomes: The role of job crafting and career commitment. Humanities and Social Sciences Communications, 12(1), 1–12. https://doi.org/10.1057/s41599-025-05656-4
  7. Melão, N., Oliveira, T., & Ferreira, J. (2026). Generative artificial intelligence in HRM practice: Patterns, opportunities and challenges. Administrative Sciences, 16(3), 113. https://doi.org/10.3390/admsci16030113
  8. Prasad, K. D. V., Vaidya, R., & Mangipudi, M. R. (2024). Generative AI as a catalyst for HRM practices, employee engagement and organizational commitment. Humanities and Social Sciences Communications, 11(1), 1–15. https://doi.org/10.1057/s41599-024-03842-4
  9. Valtonen, A., Kallio, T., & Salmela, H. (2025). AI and employee wellbeing in the workplace: An empirical investigation. Journal of Business Research, 182, 115113. https://doi.org/10.1016/j.jbusres.2025.115113
  10. Vrontis, D., Christofi, M., Pereira, V., Tarba, S., Makrides, A., & Trichina, E. (2022). Artificial intelligence, robotics, advanced technologies and human resource management: A systematic review. The International Journal of Human Resource Management, 33(6), 1237–1266. https://doi.org/10.1080/09585192.2020.1871398
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