Establishes the North Carolina AI Leadership Council to advise on AI strategy and policy. Creates the AI Accelerator for AI governance, research, and training. Requires Cabinet agencies to propose AI use cases. Develops statewide AI literacy and fraud prevention training program.
Good coverage — Comprehensive governance measures or mitigations with clear procedures relating to the risk subdomain are explicitly described.
Minimal coverage — Brief mention but no specific mitigations, recommendations or governance measures relating to the risk subdomain are described.
All other risk subdomains had no coverage in this document.
Risk Coverage Summary
The document has minimal to good coverage of approximately 8 subdomains, with primary focus on governance failure prevention (6.5), transparency (7.4), privacy protection (2.1), environmental impacts (6.6), fraud prevention (4.3), misinformation (3.1), security (2.2), and system failures (7.3). Coverage is concentrated in governance structures, risk management, and public accountability domains.
Good coverage — Comprehensive governance measures or mitigations with clear procedures relating to the sector are explicitly described.
Minimal coverage — Brief mention but no specific mitigations, recommendations or governance measures relating to the sector are described.
All other sectors had no coverage in this document.
Sectors Summary
This executive order primarily governs AI use within Public Administration (state government agencies). While it mentions impacts on education, healthcare, and other sectors, the binding governance measures apply specifically to North Carolina state government operations, Cabinet agencies, and public sector AI deployment.
Hard Law
Legislative Status Summary
This is a binding executive order issued by the Governor of North Carolina under constitutional and statutory authority that creates mandatory obligations for state Cabinet agencies and establishes enforceable governance structures with monitoring and reporting requirements.
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Monitor
Lifecycle stages covered by the documents, as defined in the OECD Framework for the Classification of AI Systems
AI Lifecycle Summary
The document comprehensively covers all stages of the AI lifecycle with particular emphasis on planning and design (governance frameworks, risk assessment), deployment (use case implementation), and operation and monitoring (ongoing oversight and reporting). It addresses data management, model development through pilot projects, and validation through risk assessment frameworks.
Terms relating to technical scope that are mentioned or implicitly referenced in the document
Technical Scope Summary
The document explicitly mentions AI, artificial intelligence, and Generative AI, requiring standardized definitions. It does not reference frontier AI, general purpose AI, foundation models, compute thresholds, or open-weight models. The focus is on applied AI systems and use cases within state government operations.
Document data from AGORA, CSET Emerging Technology Observatory.