Electronic Governance Controls for AI-Enabled Agentic Large Language Models in Digital Government (Compliance-by-Design and Evidence-Linked Evaluation)
By:
Dr. Maram Abdulrahman Almaghrabi
Assistant professor, Data Science Department, College of Computing, Umm Al-Qura University, Makkah, Saudi Arabia
Abstract:
Artificial intelligence (AI), particularly large language models (LLMs) and agentic AI systems, is increasingly used to modernize digital government, yet public-sector deployment must satisfy accountability, privacy, and auditability requirements. This paper aims to propose an electronic-governance framework that enables governed use of LLM-enabled agentic systems under binding constraints. Through qualitative documentary analysis, the study examines policy and governance evidence across digital-government strategies, data-governance and privacy instruments, and public-sector AI initiatives. Empirical grounding is strengthened through triangulation with official digital-government maturity indicators, a flagship platform vignette illustrating operational scalability, and a reproducible open-data key performance indicator (KPI) baseline derived from a government complaint-escalation series. The study concludes that scalable public value depends on bounded autonomy implemented through allowlisted tools, controlled state and memory, verification and feedback loops, role-based access control, audit logging, and human-in-the-loop gating. The paper contributes an evaluation-ready input–process–output framework to assess productivity, decision quality, and auditable compliance aligned with Vision 2030 and SDAIA-led transformation, The paper further strengthens feasibility claims through official maturity indicators and flagship implementation evidence, showing advanced service-experience maturity and institutional transformation readiness that support scaling LLM-enabled service augmentation and governance-constrained agentic execution under regulated constraints.
Keywords:
Electronic Governance; Digital Government; Artificial Intelligence Governance; Large Language Models; Agentic AI; Accountability; Auditability; Compliance
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