Kesiapan dan Kompetensi Kecerdasan Buatan Kontekstual ASN: Kerangka Konseptual Integratif dalam Manajemen SDM Sektor Publik

Abstract

Although the adoption of artificial intelligence (AI) in public administration has been widely studied, the integration of AI readiness and competency frameworks for Indonesia’s Aparatur Sipil Negara (ASN) remains limited, while the contextualization of competencies remains normative and has yet to be operationalized. Indonesia ranks 42nd among 193 countries in the Government AI Readiness Index 2023. This study aims to explain the separation between AI readiness and competency frameworks, specify how structural contextualization can be operationalized, and develop an integrative framework for ASN. The study employed a narrative literature review approach involving 26 iterative search queries, with inclusion and exclusion criteria for publications from 2022–2026. The initial search yielded 17 verified sources, while targeted follow-up searches added 19 journal articles, resulting in a total of 36 sources analyzed through synthesis at five levels: findings, concepts, theory, methodology, and policy. The synthesis results indicated that individual competencies and attitudes were more influential in determining AI readiness than technical infrastructure. The competency frameworks of UNESCO, AI4Gov Canvas, and the European Commission have also yet to be integrated with readiness models or the human resource development cycle. Based on these findings, the study formulated a framework integrating Technology–Organization–Environment (TOE), Unified Theory of Acceptance and Use of Technology (UTAUT), and Ability–Motivation–Opportunity (AMO). Contextualization is positioned as a structural moderator shaped by digital maturity, service risk, and employee characteristics. No direct precedent for this pattern of integration was found in the reviewed literature. This framework makes a conceptual contribution to public sector human resource management by bridging the literature on AI readiness and competencies. Its practical implications include preliminary guidance for BKN and Kementerian PANRB in designing AI competencies suited to the characteristics of organizational units to support the operationalization of Law No. 20 of 2023 on ASN. This framework remains conceptual and requires empirical validation of its structural weights.