Digital Competency and Artificial Intelligence Integration in Modern Administration: Current Demands, Gaps, and Strategic Pathways

Modern administrative governance is undergoing a systemic socio-technical reconfiguration, transitioning rapidly from manual, paper-bound ledgers and legacy e-governance architectures to integrated digital public infrastructure and Generative Artificial Intelligence (AI) co-pilot environments. This evolution demands an expanded conceptualization of workforce digital readiness. Grounded in the Technology Acceptance Model (TAM) and the Unified Theory of Acceptance and Use of Technology (UTAUT), this study systematically examines the operational demands, capacity deficits, and governance challenges confronting administrative personnel across public sector and higher education institutions, particularly within resource-constrained regional environments. Evaluating an integrated dual-layer competency framework—encompassing core computing proficiencies (advanced spreadsheet manipulation, relational database taxonomy, cloud-based records management, and virtual collaboration) alongside emerging Generative AI capabilities (contextual prompt engineering, automated text summarization, cross-linguistic translation, and critical output verification across platforms such as ChatGPT, Claude, and Copilot)—this paper articulates the comparative operational advantages and structural friction points defining modern public administration. Systemic capacity gaps are identified, including technological anxiety, shallow digital literacy, cybersecurity hygiene vulnerabilities, acute geographical infrastructure disparities (exemplified by power grid instability and bandwidth limitations in regional campus settings), and administrative risks surrounding AI hallucinations and data privacy. To bridge the divide between top-down digital governance policies and ground-level workplace execution, we articulate a multi-tiered strategic roadmap incorporating task-oriented contextual training, robust institutional AI governance frameworks, peer-mentorship coaching networks, and sustained capital infrastructure investments, paired with individual lifelong learning pathways. Ultimately, this research demonstrates that while automated tools and AI engines serve as powerful efficiency enablers, rigorous human oversight, procedural discretion, and ethical boundary-setting remain mandatory to safeguard due process, institutional accountability, and transparent governance.