Artificial Intelligence in Employee Evaluations: Fairness and Effectiveness in Nagpur’s IT Sector

Abstract

By automating the review process, providing data-driven insights, and improving decision-making, artificial intelligence (AI) has transformed conventional performance evaluation methods.  But there are still serious worries about prejudice, lack of transparency, and unfairness in performance rating systems powered by AI.  This research takes a look at the IT sector in Nagpur to see how well and fairly AI-based performance assessment methods work.  In order to gauge how IT workers and HR managers feel about AI-driven performance reviews, this study uses a mixed-methods strategy, using both survey and interview data.  Critical aspects including precision, impartiality, reducing prejudice, trust among employees, and organisational buy-in are examined.  The results show that AI-powered assessments are more efficient and consistent, which are great advantages, but they also address problems like algorithmic bias and a lack of human empathy.  The report wraps up with suggestions for improving AI-based evaluation systems to make sure they're fair, transparent, and make employees happy.  This study adds to the current conversation on the moral implications of using AI in HRM by shedding light on the topic for politicians, businesses, and IT engineers.