Artificial Intelligence in Performance Evaluation (Case Study of PT. Pos Indonesia Employees) - Agung Dwianto; Sitta Kusuma; Junengsih (Komunitas Dosen Indonesia, 2024)
The development of artificial intelligence (AI) has revolutionized various aspects of human resource management, including employee performance evaluation. While existing studies have extensively explored the potential of AI in improving efficiency and objectivity, they often overlook the nuanced employee experiences and organizational dynamics that influence its successful implementation. This research bridges this gap by examining the perceptions and experiences of PT Pos Indonesia employees regarding the use of an AI-based performance evaluation system. Using a qualitative approach with a phenomenological design, data was collected through in-depth interviews with employees who have used the system for at least six months. The findings reveal that AI contributes significantly to enhancing efficiency and reducing subjectivity in evaluations. However, challenges such as algorithm bias, the relevance of performance metrics, and system transparency remain prevalent. Importantly, this study identifies critical factors influencing acceptance, including employee understanding, trust, and perceptions of fairness in the evaluation process. Unlike previous research, this study emphasizes the interplay between technological and human factors, highlighting the irreplaceable role of human interaction in providing qualitative context. This research extends the existing literature by offering a deeper understanding of employee-centered factors and organizational practices that facilitate the integration of AI in performance evaluation. Practically, it provides actionable insights for organizations aiming to implement AI-based systems effectively, ethically, and equitably.