Authors : Dasari Raghavendra Kumari; Katike Subhani; Syeda Juveria Qadri; Dr. Kamma Ramanjaneyulu; Omkaram Ravisankar

Volume/Issue : Volume 10 - 2025, Issue 11 - November

Google Scholar : https://tinyurl.com/2zfvemr4

Scribd : https://tinyurl.com/272f3htt

DOI : https://doi.org/10.38124/ijisrt/25nov640

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Abstract : In today’s globalized business environment, multinational companies (MNCs) place a strong emphasis on performance management systems that ensure accuracy, fairness, and transparency across diverse teams. The 360-degree feedback mechanism, which gathers performance data from multiple sources including peers, subordinates, and supervisors, has become a popular method for holistic evaluation. However, traditional 360-degree systems often encounter challenges such as evaluator bias, data inconsistency, and time-consuming processes. This study aims to analyze how Artificial Intelligence (AI) can be applied to improve the effectiveness and reliability of 360-degree feedback mechanisms in MNCs. AI technologies such as natural language processing, sentiment analysis, and predictive analytics offer innovative solutions to minimize human bias, enhance data interpretation, and support evidence- based decision-making. The research will adopt both primary and secondary data to examine the perceptions of HR professionals and employees working in MNCs regarding AI-driven performance appraisal systems. The findings are expected to reveal that AI integration significantly enhances the accuracy, objectivity, and efficiency of performance appraisals, thereby fostering better employee development and organizational growth in multinational environments.

Keywords : Artificial Intelligence, 360-Degree Feedback, Performance Appraisal, Multinational Companies, Human Resource Management, Machine Learning, Predictive Analytics, Employee Evaluation, Organizational Performance, HR Technology, Sentiment Analysis.

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