AI in Governance: Beyond the Hype
Exploring how artificial intelligence can transform public sector decision-making, improve transparency, and address ethical challenges.
Executive Summary
While global debate has focused heavily on governments' regulatory role in AI, their responsibilities as direct users of AI systems deserve greater attention. Governments function across multiple dimensions: as regulators, enablers, funders, investors, developers, and users. AI deployment in the public sector can increase productivity, improve responsiveness of public services, and strengthen government accountabilityâbut critical policy challenges around risk mitigation, data governance, and human-centered design must be addressed.
Government's Multiple Roles in AI
Governments operate across six overlapping dimensions. As regulators, they set rules for private sector AI deployment. As enablers, they create ecosystems for innovation. As funders and investors, they allocate R&D and procurement budgets. As developers and users, they build and deploy AI systems within their own agencies.
The latter rolesâdirect development and useâhave received less scrutiny than regulation, yet they carry significant implications for efficiency, equity, and democratic accountability. Public sector AI systems process citizen data, automate benefits decisions, and inform policy formulation. Getting governance right at the point of use is essential.
In Vietnam and ASEAN, the trend is clear: national digital transformation strategies increasingly reference AI as a productivity lever. Resolution 57 targets 30% digital economy share of GDP by 2030, with a 500 trillion VND credit package for digital infrastructure. GovTech procurementâAI-enabled citizen services, administrative automation, and fraud detectionâwill grow as governments move from pilots to scaled deployment.
Benefits and Applications
Three core benefits stand out for AI deployment in the public sector: productivity gains, improved service responsiveness, and enhanced accountability. Applications span broad policy areasâfrom tax administration and healthcare triage to environmental monitoring and fraud detection. The opportunity is not merely incremental efficiency; it is reimagining how citizens interact with the state.
Productivity
Automation of routine tasks frees public servants for higher-value workâlicensing, permits, document processing, and case management
Responsiveness
Faster, more personalized citizen services, 24/7 availability, and reduced wait times for essential transactions
Accountability
Audit trails, explainability, and performance tracking improve transparency and enable redress when systems err
Key Policy Challenges
Critical issues governments must address when deploying AI include mitigating risks, building enabling environments for trustworthy systems, and managing data governance.
Mitigating Risks
Public sector AI use carries risks of bias, error, and opacity. Governments need incident monitoring and redress mechanisms. When an algorithm denies benefits or flags a citizen for review, there must be a human in the loop and a clear appeal path.
Enabling Trustworthy AI
Building environments for responsible developmentâhuman oversight, fairness audits, and alignment with democratic values. Trustworthy AI is not a checklist; it is an ongoing practice of testing, monitoring, and iterating.
Data Governance and Privacy
Balancing open data for innovation with protection of citizen privacy and sensitive information. Public sector datasets are valuable for training and improving AI; they are also high-value targets and must be governed accordingly.
Human-Centered Design
Ensuring AI augments rather than replaces human judgment, with clear accountability for decisions. The goal is decision support, not decision replacementâparticularly in domains involving rights, benefits, or sanctions.
Incident Tracking
Global tracking of AI incidents informs policy and improves system safety. When systems fail or produce harmful outputs, transparency about what happened and why is essential for public trust.
Emerging Frameworks and Standards
International standards for trustworthy, human-centered AI are coalescing. Adaptable frameworks are needed to navigate rapid AI advancements. Key instruments include international AI principles emphasizing human oversight and transparency, reporting frameworks for accountability, and incident monitoring systems that track failures and hazards globally.
Implications for Investors and Enterprises
For investors in digital infrastructure, GovTech, and public-private partnerships, the market is maturing. Governments are moving from pilots to scaled deploymentâcreating demand for AI-enabled services in procurement, citizen engagement, and administrative automation. Alignment with national AI strategies will increasingly determine contract eligibility and stakeholder acceptance. Corvus tracks regulatory developments in Vietnam and ASEAN to inform our digital infrastructure and GovTech investment thesis.
Vietnam's Resolution 57 and Digital Economy