AI in Government and Public Sector
Government agencies using AI for benefits administration, law enforcement, border control, welfare eligibility, and public service delivery face some of the most stringent governance obligations globally. The EU AI Act prohibits several government AI applications outright and classifies others as high-risk with mandatory conformity requirements. Public sector AI also carries heightened civil rights, transparency, and accountability expectations that exceed those applied to comparable private sector deployments.
Key board-level questions
- 1.Which of our AI systems are classified as high-risk or prohibited under applicable law, and what is our compliance timeline?
- 2.Do affected individuals have meaningful recourse when AI systems make or inform decisions about them?
- 3.How do we document and publish AI systems in line with government transparency and accountability obligations?
- 4.Are our AI vendors under contractual obligations consistent with public sector data protection and procurement requirements?
Regulatory frameworks
EU AI Act: AI Literacy and Prohibited AI Systems Provisions (Applicable 2 February 2026)
This entry lists February 2, 2026 as the EU AI Act’s first major compliance deadline. It requires AI developers and deployers in the EU to establish workforce literacy measures. It also describes enforceable prohibitions on unacceptable-risk practices. Organizations must cease prohibited practices and demonstrate adequate staff competency by that date.
America's AI Action Plan
America’s AI Action Plan sets the White House’s priorities for advancing and governing AI. It directs federal work on AI security infrastructure, agency coordination, and cybersecurity readiness. The plan primarily covers federal agencies and their AI operators. Federal AI contractors and suppliers may also be affected.
Executive Order 14179: Removing Barriers to American Leadership in Artificial Intelligence
Executive Order 14179 directs agencies to develop an AI Action Plan prioritizing US development and deployment leadership. It shapes conditions for private AI businesses operating in the US. The order revokes earlier safety-focused directives and emphasizes deregulation and competitiveness.
NIST Artificial Intelligence Risk Management Framework Playbook
The voluntary NIST AI RMF Playbook provides implementation guidance, suggested actions, and example outputs across AI use cases. It supports GOVERN, MAP, MEASURE, and MANAGE throughout the system lifecycle.
OWASP Top 10 for Large Language Model Applications
OWASP’s LLM Top 10 identifies application security risks. These include prompt injection, insecure output handling, training-data poisoning, denial of service, and supply-chain vulnerabilities. Development and security teams use it to prioritize controls.
Playbook guidance
What does meaningful human oversight look like for high-risk AI decisions?
How do we detect and mitigate algorithmic bias?
What are our obligations under emerging AI regulations?
What does audit-ready AI documentation look like in practice?
How do we ensure human-in-the-loop review is actually effective?