02291nam a22001577a 4500999001900000008004100019100002300060245007700083260005400160300003100214520159300245650012801838773005401966942000702020952010602027 c533705d533705260611b ||||| |||| 00| 0 eng d aBist, Devaj961200 aThe use of artificial intelligence in capacity building in public sector aISTM Journal of Training Research and Governance  a6(1&2), Jan, 2026: p.69-77 aAs governments globally accelerate their transition toward Digital Era Governance (DEG), the integration of Artificial Intelligence (AI) has emerged as a critical lever for administrative efficiency. However, a significant dichotomy exists between the procurement of advanced AI tools and the readiness of the public workforce to utilize them effectively—a phenomenon termed the "Enablement Gap. " This study investigates the current state of AI capacity building within the public sector, moving beyond infrastructure analysis to focus on human capital readiness. Grounded in the Unified Theory of Acceptance and Use of Technology (UTAUT), this research employs a quantitative, descriptive-correlational design to assess the "Performance Expectancy" and "Facilitating Conditions" among public servants. Data was collected via a structured survey instrument targeting a stratified sample of experienced government officials (N=26). Findings indicate a "Paradox of Readiness": while 76.9% of respondents believe AI would improve productivity, nearly 50% report receiving no formal training. Consequently, 58.3% cite "lack of time" rather than fear as their primary barrier to adoption. This disconnect has fostered an environment of "Shadow AI, " where unauthorized tools are used without oversight. This paper proposes a "Human-in-the-Loop" competency framework, arguing that sustainable capacity building requires a shift from sporadic technical workshops to continuous, ethics-centred algorithmic literacy. –Reproduced https://www.istm.gov.in/library/information_bulletin/journal  aPublic administration, Artificial intelligence, Capacity building, Digital governance, UTAUT, AI Llteracy, Shadow AI961201 aISTM Journal of Training Research and Governance  cAR 00102ddc40709408884aIIPAbIIPAd2026-06-11h6(1&2), Jan, 2026: p.69-77pAR139177r2026-06-11yAR