02176nam a22001457a 4500 533705 533705 260611b ||||| |||| 00| 0 eng d Bist, Devaj 61200 The use of artificial intelligence in capacity building in public sector ISTM Journal of Training Research and Governance 6(1&2), Jan, 2026: p.69-77 As 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 Public administration, Artificial intelligence, Capacity building, Digital governance, UTAUT, AI Llteracy, Shadow AI 61201 ISTM Journal of Training Research and Governance AR 0 0 ddc 0 0 408884 IIPA IIPA 2026-06-11 6(1&2), Jan, 2026: p.69-77 AR139177 2026-06-11 AR