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International Journal of Creative and Open Research in Engineering and Management

A Peer-Reviewed, Open-Access International Journal Supporting Multidisciplinary Research, Digital Publishing Standards, DOI Registration, and Academic Indexing.
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ISSN: 3108-1754 (Online)
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Volume 02, Issue 6

Published on: June 2026

IMPACT OF ARTIFICIAL INTELLIGENCE ADOPTION ON ORGANIZATIONAL BEHAVIOUR: CHALLENGES, OPPORTUNITIES AND EMPLOYEE PERSPECTIVES

Lavi Kumari Gaurav Kumar Gaurish Sharma Khushi Agrawal Lovekesh Chaudhary

Dr. Bhuvnesh Kumar

DPBS College, Anupshahr, Distt. Bulandshahr (Uttar Pradesh), India

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Plagiarism Passed Peer Reviewed Open Access

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Abstract

Artificial Intelligence (AI) has emerged as one of the most transformative technologies in the modern business environment. Organizations across various sectors are increasingly adopting AI-based technologies to improve operational efficiency, enhance decision-making, automate routine tasks, and achieve competitive advantage. While AI offers numerous opportunities for organizational growth, it also significantly influences organizational behaviour by changing employee roles, communication patterns, leadership approaches, workplace culture, and decision-making processes. The adoption of AI has created both opportunities and challenges for employees and organizations. On one hand, AI enhances productivity, innovation, accuracy, and strategic planning. On the other hand, employees often experience concerns regarding job security, skill obsolescence, ethical issues, privacy, and resistance to technological change.

The present study aims to examine the impact of Artificial Intelligence adoption on organizational behaviour with special reference to employee perspectives. The study explores how AI affects employee motivation, job satisfaction, organizational commitment, collaboration, adaptability, and workplace relationships. It also identifies the major challenges faced during AI implementation and the opportunities created for organizational development. The research adopts an empirical approach using primary data collected through a structured questionnaire. Statistical tools such as descriptive statistics, correlation, and regression analysis were employed to analyze the relationship between AI adoption and organizational behaviour.

The findings of the study are expected to assist managers, policymakers, and organizational leaders in developing effective AI implementation strategies while maintaining positive employee behaviour and organizational effectiveness. The study also contributes to the growing body of literature on Artificial Intelligence and Organizational Behaviour by providing practical insights for organizations undergoing digital transformation.

Keywords: Artificial Intelligence, Organizational Behaviour, Employee Behaviour, Digital Transformation, Job Satisfaction, Organizational Effectiveness.

How to Cite this Paper

Kumari, L., Kumar, G., Sharma, G., Agrawal, K. & Chaudhary, L. (2026). Impact of Artificial Intelligence Adoption on Organizational Behaviour: Challenges, Opportunities and Employee Perspectives. International Journal of Creative and Open Research in Engineering and Management, <i>02</i>(6). https://doi.org/10.55041/ijcope.v2i6.349

Kumari, Lavi, et al.. "Impact of Artificial Intelligence Adoption on Organizational Behaviour: Challenges, Opportunities and Employee Perspectives." International Journal of Creative and Open Research in Engineering and Management, vol. 02, no. 6, 2026, pp. . doi:https://doi.org/10.55041/ijcope.v2i6.349.

Kumari, Lavi,Gaurav Kumar,Gaurish Sharma,Khushi Agrawal, and Lovekesh Chaudhary. "Impact of Artificial Intelligence Adoption on Organizational Behaviour: Challenges, Opportunities and Employee Perspectives." International Journal of Creative and Open Research in Engineering and Management 02, no. 6 (2026). https://doi.org/https://doi.org/10.55041/ijcope.v2i6.349.

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References


  1. Budhwar, P. S., Malik, A., De Silva, M. T., & Thevisuthan, P. (2023). Artificial intelligence HRM interactions and outcomes: A systematic review and causal configurational explanation. Human Resource Management Review, 33(1), 100893. https://doi.org/10.1016/j.hrmr.2022.100893

  2. Budhwar, P. S., Malik, A., Patel, P., Islam, M., & Gupta, S. (2023). AI-augmented HRM: Literature review and a proposed multilevel framework for future research. Technological Forecasting and Social Change, 193, 122645. https://doi.org/10.1016/j.techfore.2023.122645

  3. Malik, A., Budhwar, P. S., Patel, P., & Srikanth, N. R. (2023). AI-augmented HRM: Antecedents, assimilation and multilevel consequences. Human Resource Management Review, 33(1), 100860. https://doi.org/10.1016/j.hrmr.2021.100860

  4. Malik, A., Pereira, V., & Budhwar, P. S. (2023). Artificial intelligence (AI)-assisted HRM: Towards an extended strategic framework. Human Resource Management Review, 33(1), 100940. https://doi.org/10.1016/j.hrmr.2022.100940

  5. Soulami, M., Benchekroun, S., & Galiulina, A. (2024). Artificial intelligence adoption in the workplace: A bibliometric and systematic literature review. Frontiers in Artificial Intelligence. https://doi.org/10.3389/frai.2024.1473872

  6. Marocco, S., Barbieri, B., & Talamo, A. (2024). Facilitators and barriers to managers' adoption of artificial intelligence: A systematic literature review. AI, 5(4). https://doi.org/10.3390/ai5040123

  7. Lee, M. C. M., Scheepers, H., Lui, A. K. H., & Ngai, E. W. T. (2023). A systematic literature review of organizational artificial intelligence implementation. European Journal of Operational Research.

  8. Wagan, S. M., & Sidra. (2025). Artificial intelligence in human resource management: A systematic review of adoption, impact, and challenges. AYBU Business Journal, 5(2).

  9. Said, O., & Abadi, N. (2026). Adoption of artificial intelligence in human resource management: Systematic review and bibliometric analysis. Multidisciplinary Reviews, 9(10), e2026510.

  10. Durai, K. A., & Anbu, A. (2026). Identification of artificial intelligence adoption determinants affecting human resource management effectiveness in the Indian information technology sector. Eastern European Journal of Enterprise Technologies.

  11. Nguyen, P., Watson, G. P., Barnes, D., Agrawal, S., Schuster, A. M., & Cotten, S. R. (2026). Navigating workplace AI adoption: The influence of perceptions and affective attitudes on employees’ intentions to use AI at work. Journal of Management & Organization.

  12. Verma, P., Islam, M., Patel, P., Malik, A., Budhwar, P. S., & Gupta, S. (2023). Artificial intelligence and organizational outcomes: A multilevel review. Technological Forecasting and Social Change.

  13. Jarrahi, M. H. (2023). Artificial intelligence and the future of work: Human–AI collaboration in organizational decision-making. Business Horizons.

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  • Published on: Jun 27 2026
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