Linking artificial intelligence and organizational change
Estherita, S. Anisha and Kotteeswaran, M (2026) Linking artificial intelligence and organizational change. Linking Artificial Intelligence and Organizational Change: 3345. 020050-1-020050-8. ISSN 1551-7616
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Abstract
Adoption of Artificial Intelligence is becoming increasingly prevalent in organizations, due to which
organizations are experiencing profound shift in their processes and practices. Artificial Intelligence has the potential to
drive significant changes within the organization. It automates the routine tasks and improves decision making thereby
enhancing the customer interactions and innovative culture within the organization. Organizational changes are becoming
necessary in organizations for them to cope up with a variety of environmental, societal and technological changes.
Artificial Intelligence has made managing changes easier by providing various data-driven insights, personalized training
and feedback analysis for the change initiators which in turn acts as a basis for the entire change process. It ultimately
results in more successful and effective change management by empowering change managers to make well-informed
decisions, monitor its progress, assess the impact, manage risks and analyse the success of change initiatives. This article
employs a qualitative method of research by analyzing existing literatures to explore the multifaceted influences of
Artificial Intelligence on organizational change. The key findings of this article highlight how Artificial Intelligence
helps for a successful implementation of organizational change by providing support in various aspects within the
organization.
Keywords. Artificial Intelligence, Data Driven, Leadership, Organizational Change, Process Automation.
| Item Type: | Article |
|---|---|
| Subjects: | Management Studies > Business Environment |
| Domains: | Management Studies |
| Depositing User: | Mr IR Admin |
| Date Deposited: | 10 May 2026 16:48 |
| Last Modified: | 10 May 2026 17:37 |
| URI: | https://ir.vistas.ac.in/id/eprint/15365 |
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