The Role of Generative AI in Human Capital Performance Evaluation: A Systematic Review and Conceptual Framework for Public Institutions

Abstract

This research examines the implications of generative artificial intelligence (GenAI) for evaluating human capital performance in public institutions. The study investigates how GenAI technologies can transform traditional evaluation methods, offering structured insights into measuring and enhancing employee performance in the public sector. Utilizing a systematic review of the literature from 2015 to 2025, guided by the PRISMA methodology, the study analyzes 78 peer-reviewed sources to identify the potential benefits, implementation challenges, and ethical concerns associated with GenAI in public human resource management (HRM). The findings indicate that GenAI can enhance the objectivity, efficiency, and personalization of evaluation processes. However, successful implementation requires adaptations tailored to the unique administrative and cultural contexts of public institutions. The paper also proposes a five-step conceptual framework for the responsible implementation of generative AI solutions in performance evaluation. This framework includes the following steps: organizational readiness assessment, human-centered design, gradual implementation with controlled pilots, developing organizational capacity, and continuous monitoring and improvement. The emphasis is placed on the importance of a human-centered approach when adopting these emerging technologies.