How State Agencies Can Accelerate Safe AI Adoption with Innovation Sandboxes

State agencies, such as Departments of Motor Vehicles, Health, or Labor, are under mounting pressure to modernize services, improve efficiency, and manage risk as artificial intelligence (AI) transforms the public sector landscape. Yet, according to Code for America’s July 2025, Government AI Landscape Assessment, more than half of U.S. states are still at an “early” or “developing” stage in their AI journey, lacking the robust frameworks and hands-on experience needed for responsible adoption. For agency leaders, the imperative is clear: structured, safe experimentation is essential to move from aspiration to impact.

Safe experimentation is the cornerstone of responsible AI adoption. As highlighted in a recently Harvard Business Review article, organizations that create structured environments for experimentation are more likely to innovate successfully while managing risk. Equally important is the idea that learning without doing is like trying to build muscle watching someone else exercise. On the other hand, state agencies have stakes for citizen safety, data privacy, and public trust that are exceptionally high, and experimentation without guardrails can be very risky.

Most states are still building foundational AI capabilities. Without structured experimentation, agencies risk falling behind in service delivery and operational efficiency. Safe, hands-on learning accelerates both workforce readiness and organizational confidence.

An innovation sandbox is more than a technical testbed, it’s a governance mechanism that enables rapid, safe, and transparent AI experimentation. Unlike traditional pilots, sandboxes provide:

• • secure, isolated environments for testing AI models and workflows without production system risks;
  • robust data governance and privacy controls to protect sensitive citizen information;
  • real-time monitoring and audit trails for accountability and compliance;
  • clear ethical guidelines and opt-in participation frameworks; and
  • integration capabilities with existing IT infrastructure and business processes.

The NIST AI Risk Management Framework offers a structured approach for sandbox governance, emphasizing four core functions of Govern, Map, Measure, and Manage.

State agencies can operationalize AI sandboxes in twelve to eighteen weeks through focused, cross-functional execution.

The state’s generative AI pilot, launched under Governor Shapiro’s executive order, delivered measurable productivity gains and high employee satisfaction. The program emphasized human oversight, robust training, and a commitment to fairness and transparency.

The NJ AI Assistant provides a secure sandbox for state employees, with strong privacy protections and government-friendly terms of service. Its launch was paired with a comprehensive AI training program, and early results include a 50% increase in call center resolution rates.

The Impact Makers Secure Research Environment, implemented for Virginia Tech, delivered a secure, cloud-based platform for researchers to work with sensitive data, collaborate, and deploy dedicated workspaces with built-in security and compliance. The solution was launched rapidly using agile methods and included features such as elastic infrastructure, automated monitoring, and HIPAA/NIH-compliant storage.

Tying sandbox availability for innovation hack-a-thons creates immediate momentum. Hack-a-thons surface real world use cases, foster cross-departmental collaboration, and provide rapid feedback on technical and governance challenges. This approach has been validated across multiple government implementations and academic institutions. 

Case in Point: The U.S. Congressional Hackathon united lawmakers, staff, and civic technologists to co-create tools that boost transparency, constituent engagement, and legislative workflows. Innovations included real-time bill comparison, AI-powered transcript search, and improved public access to budget data. These efforts have directly led to new tools like the centralized House calendar and enhanced social media tracking, helping modernize Congress’s digital infrastructure.

• • Secure executive sponsorship to signal commitment
  • Design for safety and transparency from day one
  • Plan a launch hack-a-thon to drive engagement and use case generation
  • Accelerate training with targeted, role-based programs
  • Iterate and scale based on early feedback and lessons learned

By leveraging innovation sandboxes, state agencies can foster a culture of safe, rapid experimentation, accelerating AI adoption while managing risk and building public trust. The evidence is clear. Those who experiment safely and learn fastest deliver the greatest value to their communities.

For more practical insights, proven examples, and actionable strategies tailored for state agency leaders, check out the rest of our AI Adoption series below.

• Developing Your Agency’s AI Roadmap: Identify where AI can deliver the greatest value in your agency.
• Unlocking AI: A Critical Moment for State Agencies: Real World Value for State Agencies
• Change Management, Training, and Re-Skilling: Prepare your workforce for the future of AI-powered government.
• How ready does your data need to be for AI Success?: Assess and strengthen your data foundation for successful AI adoption.

1. Code for America. “Government AI Landscape Assessment.”
2. Harvard Business Review. “Want Your Company to Get Better at Experimentation?”
3.  NIST. “AI Risk Management Framework.”
4. Pennsylvania Office of Administration. “Shapiro Administration’s Generative AI Pilot for State Workers.”
5. New Jersey Office of Innovation. “AI Assistant.”