Scaling Smart Technology Audits for Digital Government

<jats:p>Digital government transformation creates integrated public service ecosystems but simultaneously generates system fragmentation, application duplication, and systemic technological risks. Traditional periodic, sample-based, organization-oriented technology audits are inadequate for addressing these challenges. This chapter proposes a layered smart technology audit framework for national digital government ecosystems combining regulations, standardized audit tools, artificial intelligence, and continuous auditing principles. Within the Indonesian policy context (SPBE and BRIN technology audit regulations), this framework positions auditing as knowledge infrastructure and governance intelligence supporting regulatory assurance, predictive risk management, and strategic public service interoperability strengthening. AI techniques—machine learning, predictive analytics, natural language processing, and explainable AI—enable full population analysis, near real-time risk detection, and evidence-based policy insights at national scales.</jats:p>