THE USE OF GENERATIVE AI AND CHANGES IN WORK PRACTICES AMONG PUBLIC SECTOR PERSONNEL

Abstract

This study examined the acceptance and use of Generative AI, perceived organizational support, and changes in work practices among public sector personnel. A qualitative descriptive and interpretive approach was employed. Data were collected through semi-structured in-depth interviews with 12 participants, including civil servants, state enterprise employees, public organization employees, and university personnel who had experience using Generative AI in their work. The data were analyzed using thematic analysis, informed by the Unified Theory of Acceptance and Use of Technology (UTAUT), Perceived Organizational Support (POS), and the Job Demands-Resources (JD-R) Model. The findings showed that Generative AI was applied to a range of tasks, including information searching and summarization, document preparation, work planning, content creation, and programming. Participants perceived that Generative AI reduced the time required for certain tasks, enabled faster task initiation, and helped organize information more systematically. Its acceptance and use were associated with perceived usefulness, ease of use, influence from supervisors and colleagues, as well as the availability of tools, training, and organizational policies. The findings also indicated a shift from completing all stages of work independently toward working collaboratively with AI, with greater emphasis on defining tasks, reviewing outputs, refining results, and making final decisions. Nevertheless, concerns remained regarding accuracy, reliability, data security, and differences in users’ digital capabilities. The study suggests that the effective adoption of Generative AI should therefore be accompanied by the development of AI literacy, clear policies and data governance guidelines, appropriate access to AI tools, and continued human oversight.

Keywords: Generative AI, Technology Acceptance, Perceived Organizational Support, Work Practices, Public Sector Personnel