ARTIFICIAL INTELLIGENCE AND PUBLIC SECTOR ORGANIZATIONAL PERFORMANCE: A SYSTEMATIC LITERATURE REVIEW
DOI:
https://doi.org/10.36563/aja8rz76Keywords:
Artificial Intelligence, Organizational Performance, Public Sector, Systematic Literature ReviewAbstract
This study aims to systematically map the Scopus-indexed literature on artificial intelligence and organizational performance in the public sector and to identify the mechanisms that explain the relationship between AI and organizational performance. A systematic literature review approach based on the PRISMA guidelines was used to identify, select, and synthesize relevant articles. The thematic synthesis indicates that the relationship between AI and organizational performance can be understood through several interrelated themes, including AI-based organizational capabilities, good governance, public values and the governance of automated systems, human resources and leadership, as well as innovation and knowledge management. The results of the synthesis indicate that the benefits of AI on performance are not universal but depend on organizational capabilities, the quality of governance, and the readiness of data and systems. Empirical evidence also remains concentrated in specific national contexts, while evidence regarding the context of local government in Indonesia remains limited. Based on these findings, this study formulates theoretical propositions grounded in Dynamic Capability Theory, which positions organizational capabilities as a key mechanism and governance and institutional context as conditions that can influence the relationship between AI and performance. These findings provide direction for the development of empirical models of AI and organizational performance in the public sector, particularly in Indonesian local governments.
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