AI in Performance Management: Automating Feedback, Goal Setting, and Appraisals for Improved Productivity

When AI supports performance management, it integrates a transition from episodic subjective evaluations to continuous objective, individualized processes. This paper introduces a framework of AI-based systems that automate a core set of functions - feedback, goal setting, and appraisals and improve employee engagement and productivity. AIenabled systems change performance management by utilizing machine learning, natural language processing, and predictive analytics to map individual and organizational goals in real time, provide feedback in real-time, and provide appraisal without human bias. Furthermore, the AI-enabled performance management system reduces the managerial burden of conducting performance management, increases transparency and minimizes bias in evaluations. The paper outlines potential implementation challenges such as data privacy, ethics of AI accountability, algorithmic accountability, and organizational readiness. The paper includes three case studies from industries in the technology, education, and manufacturing sectors with evidence of significant improvements in employee satisfaction, accurate performance, and operational alignment. The paper concludes by positioning AI systems in an organization as an enabler of agile and responsible human capital management and offers recommendations for policy and future research concerning ethical uses of AI.