Abstract: This article presents a critical review of empirical studies conducted between 2020 and 2024, examining the impact of Artificial Intelligence (AI) on performance management practices within organizations. Grounded in the theoretical frameworks of Systems Theory and the Technology Acceptance Model (TAM), this review highlights how AI technologies are integrated into performance management systems to enhance efficiency, reduce biases, and improve employee engagement. A systematic literature review methodology was employed, analyzing various empirical studies that focus on AI applications in performance management. Key findings reveal that AI facilitates continuous feedback mechanisms, enables data-driven insights, reduces biases in evaluations, and allows for the creation of personalized development plans. Moreover, predictive analytics play a crucial role in forecasting employee performance and identifying potential leaders. The intertwined nature of performance management and artificial intelligence in this work serves to highlight two points. First, continuous feedback mechanisms and a plethora of data are intertwined with performance management improvement. Second, AI can assist in personalizing the development opportunities provided to employees. Together, this discussion suggests there is a ripe opportunity to integrate AI into existing best practices on performance management. The review underscores the transformative potential of AI in Human Resource Management while also addressing challenges such as data privacy concerns and the need for cultural change within organizations.
Keywords: Artificial Intelligence(AI) Performance Management, Continuous Feedback, Data-Driven Decision Making, Personalized Development.
Title: PERFORMANCE MANAGEMENT AND ARTIFICIAL INTELLIGENCE (AI): ENHANCING PERSONALIZED DEVELOPMENT WITH CONTINUOUS FEEDBACK AND DATA-DRIVEN DECISIONS
Author: Beatrice Chuchu, Dr. Joanes Kyongo
International Journal of Computer Science and Information Technology Research
ISSN 2348-1196 (print), ISSN 2348-120X (online)
Vol. 13, Issue 1, January 2025 - March 2025
Page No: 13-22
Research Publish Journals
Website: www.researchpublish.com
Published Date: 14-January-2025
