Leveraging Artificial Intelligence for Effective Change Management and Technology Changes in Chennai's IT Sector: An Employee-Centric Approach
Keywords:
Artificial Intelligence (AI), Change Management practices, Employee Engagement, Organizational Transitions, Efficiency Improvement.Abstract
The purpose of this study is to investigate the possibility that artificial intelligence (AI) could strengthen the efficiency of change management techniques within the information technology (IT) industry in Chennai, with a particular emphasis on an employee-centric approach. The study investigates how artificial intelligence may promote more seamless transitions, boost employee adaptability, and improve overall happiness during organizational changes. This is accomplished through the incorporation of various tools and technology related to AI. In order to provide a thorough knowledge of the impact that artificial intelligence has on the efficiency of change management techniques and employee engagement, the research makes use of a mixed-methods approach, which includes carrying out surveys, conducting interviews, and conducting case studies from a variety of information technology organizations located in Chennai.
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References
Armenakis, A. A., & Harris, S. G. (2019). Reflections: Our journey in organizational change research and practice. Journal of Change Management, 19(2), 93-107.
Bapna, R., Das, S., & Dayal, S. (2019). AI-driven decision support systems: Foundations, challenges, and future directions. MIS Quarterly, 43(3), 845-864.
Cocca, P., Guerrero, L. A., & Cocca, A. (2019). The role of artificial intelligence in achieving sustainable development goals. Sustainability, 11(9), 2626.
Jiang, F., Jiang, Y., Zhi, H., Dong, Y., Li, H., Ma, S., ... & Wang, Y. (2020). Artificial intelligence in healthcare: past, present and future. Stroke and Vascular Neurology, 5(2), 230-243.
Niederman, F., Leger, P. M., & Shultz, G. (2019). Chatbot adoption in organizations: A two-phase model. Journal of Computer Information Systems, 59(3), 287-296.
Shah, N., Khan, Z. H., & Bhat, J. A. (2021). Artificial intelligence in organizational change management: A systematic review. Computers in Human Behavior, 117, 106701.
Smith, B., Vasudevan, R., & Tan, K. H. (2018). Artificial intelligence in retailing: A review and research agenda. Expert Systems with Applications, 94, 430-445.
Wang, Y., Kung, L., & Byrd, T. A. (2020). Big data analytics: Understanding its capabilities and potential benefits for healthcare organizations. Technological Forecasting and Social Change, 144, 179-189.
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