The Role of Generative AI in Human Capital Performance Evaluation: A Systematic Review and Conceptual Framework for Public Institutions
Ciprian THIRA
Technical University of Cluj-Napoca – Doctoral School, Engineering and Management, 15 Constantin Daicoviciu Str., 40020, Cluj-Napoca, Romania.
Bogdan-Vasile CIORUȚA *
Technical University of Cluj-Napoca - Northern University Center of Baia Mare, Office of Informatics, 62A Victor Babeș Str., 430083, Baia Mare, Romania, Technical University of Cluj-Napoca - Department of Specialization with Psychopedagogical Profile, 76 Victoriei Str., 430122, Baia Mare, Romania and Technical University of Cluj-Napoca - Northern University Center of Baia Mare, Faculty of Sciences, 76 Victoriei Street, 4300122, Baia Mare, Romania.
Laura BACALI
Technical University of Cluj-Napoca – Doctoral School, Engineering and Management, 15 Constantin Daicoviciu Str., 40020, Cluj-Napoca, Romania.
Ioana-Elisabeta CIORUȚA
Technical University of Cluj-Napoca - Department of Specialization with Psychopedagogical Profile, 76 Victoriei Str., 430122, Baia Mare, Romania.
Alexandru Leonard POP
Technical University of Cluj-Napoca - Northern University Center of Baia Mare, Office of Informatics, 62A Victor Babeș Str., 430083, Baia Mare, Romania and Technical University of Cluj-Napoca - Department of Specialization with Psychopedagogical Profile, 76 Victoriei Str., 430122, Baia Mare, Romania.
*Author to whom correspondence should be addressed.
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.
Keywords: Human resource management, performance evaluation, GenAI resources, organizational readiness assessment