A Study on AI and Automation for Reducing Employee Workload and Improving Operational Efficiency in Access Management and Organizational Processes in MNC’s

The study concludes that traditional manual processes continue to create operational inefficiencies and increase employee workload within multinational corporations. Repetitive tasks consume significant time and reduce overall productivity. The findings clearly indicate that AI and automation technologies have strong potential to streamline access management processes, reduce manual effort, minimize errors, and improve operational efficiency. Employees also demonstrate a positive attitude toward adopting automation-driven solutions within organizational operations. Therefore, multinational corporations should focus on implementing AI-driven automation and Lean process improvement approaches to enhance workflow efficiency, reduce operational costs, and improve overall organizational performance.

1.     Chen, L., & Zhang, Y. (2020). AI-enabled automated access control in cloud environments. IEEE Transactions on Cloud Computing, 8(4), 1125–1138. https://doi.org/10.1109/TCC.2020.29874 15 2.     Davenport, T. H., & Ronanki, R. (2018). Artificial intelligence for the real world. Harvard Business Review, 96(1), 108– 116. 3.     Deloitte. (2020). AI in identity and access management: Transforming enterprise security.  Deloitte     Insights. https://www2.deloitte.com 4.     Forrester. (2021). The Forrester Wave™: Identity and access management for enterprise applications. Forrester Research. https://www.forrester.com 5.     Gartner. (2022). Magic Quadrant for access management. Gartner Research Publications. https://www.gartner.com 6.     IBM Security. (2019). Cost of a data breach report. IBM     Corporation. https://www.ibm.com/security/data-breach 7.     Jarrahi, M. H. (2018). Artificial intelligence and the future of work: Human-AI symbiosis in organizational decision making. Business Horizons, 61(4),        577–586. https://doi.org/10.1016/j.bushor.2018.03. 007 8.     Li, J., Wang, H., & Chen, X. (2023). Machine learning for intelligent access management in multinational enterprises. Journal of Information Security and Applications,       72,       103415. https://doi.org/10.1016/j.jisa.2023.10341 5 9.     Manyika, J., Chui, M., & Miremadi, M. (2016). Where machines could replace humans—and where they can’t (yet). McKinsey          Global Institute. https://www.mckinsey.com 10.  Microsoft. (2021). Azure AD identity governance: Automation and AI innovations. Microsoft Documentation. https://learn.microsoft.com