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AI Accelerator Program (Subnational: North Carolina)


Added by:   OECD analyst
Added on:   28 Oct 2026
Updated by:   OECD analyst
Updated on:   28 Oct 2026

The AI Accelerator connects state agencies with vendors to rapidly prototype AI solutions. It provides a structured platform for agencies to submit unresolved challenges and collaborate with vendors on rapid prototyping through 60-day sprints. This programme enhances operational efficiency, decision-making and problem-solving for agencies by fostering collaboration to leverage advanced AI technologies tailored to their specific needs.

Initiative overview

The AI Accelerator programme promotes responsible use of artificial intelligence within government agencies by identifying urgent needs and demonstrating how AI can improve daily operations. Established by the Office of Artificial Intelligence and Policy at the North Carolina Department of Information Technology through an Executive Order issued by Governor Josh Stein on 2 September 2025, the programme has collected use cases from 15 state entities to explore AI-driven solutions. Its goal is to foster innovation, streamline processes, and enhance public service delivery.

Each use case undergoes rigorous evaluation for feasibility, impact, and ethics using 32 criteria focused on public value, technical viability, and risk mitigation. The Office of Artificial Intelligence and Policy ensures data carries minimal risk and excludes personal citizen information. After initial review, submissions are vetted by two boards: one within the North Carolina Department of Information Technology (including Enterprise Security and Risk Management Office, Enterprise Architecture Office, Enterprise Collaboration Services Office, Legal Office, and Communications Office) and the AI Executive Leadership Committee, which includes the State Chief Information Officer and the Chief Operating Officer for the Office of the Governor. This multi-tiered process guarantees alignment with state objectives and ethical standards.

Approved projects often involve vendor collaboration under a no-cost participation agreement that mandates responsible data handling and compliance. Once a vendor is selected, agencies engage in a 60-day sprint where problems are defined, data shared, and prototypes developed. Vendors provide hands-on testing opportunities, while the Office of Artificial Intelligence and Policy tracks success metrics and ensures compliance. At the end of the engagement, stakeholders review outcomes and decide on full-scale implementation.

Vendor partnerships are central to success, offering technical expertise and innovative solutions that agencies might not otherwise access. In just a few months, the programme received 47 use cases, approved six, and has 17 under review. Twelve vendors have signed participation agreements, with six actively engaged. The programme will continue indefinitely, enabling agencies to explore AI technologies that improve efficiency, decision-making, and service delivery.

Other relevant details

Results, outcomes and impacts: 47 use cases were submitted by 15 agencies; six were approved and launched with vendor partnerships. Early pilots (e.g. an HR chatbot) show measurable benefits: 146 interactions, a 65.22% inquiry resolution rate, and a 3.98/5 satisfaction score. Agencies report faster turnaround times and improved efficiency in tasks like HR inquiries and content creation. Success is tracked via predefined metrics (e.g. handle rate, satisfaction scores, turnaround time), stakeholder feedback, and prototype performance during 60-day engagements. Expected future outcomes include expanded adoption across agencies, broader vendor participation, and increased operational efficiency. Anticipated impacts include reduced processing times, improved decision-making, and enhanced public service delivery. Challenges and lessons learned: The AI Accelerator faced challenges such as high submission volume, complex evaluations, and ensuring ethical, low-risk data use. Vendor co-ordination under zero-cost agreements and legacy IT constraints added complexity. These were addressed through a structured intake process, multi-level approvals, strict risk protocols, and formalised vendor agreements. Lessons learned include the importance of strong governance, cross-agency collaboration, and pilot-first approaches for feasibility. Success requires executive sponsorship, robust risk management, a skilled workforce, modern infrastructure, and clear vendor engagement models.

About the policy initiative


Category:

  • AI policy initiatives, programmes and projects

Initiative type:

  • Public procurement programmes

Status:

  • Active

Start Year:

  • 2025

OECD AI Principles:

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Other relevant urls:

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