Unlocking AI: A Critical Moment for State Agencies

The strategic imperative for government transformation in the age of artificial intelligence

Artificial intelligence (AI) is no longer a distant prospect for state agencies—it is a present and pressing reality. Yet, despite AI’s transformative potential, most state governments are not keeping pace. According to Code for America’s 2025 Government AI Landscape Assessment, the majority of U.S. states are still in the “early” or “developing” stages of AI adoption across critical dimensions such as leadership, workforce capacity, and technical infrastructure. Most states need robust frameworks, dedicated executive leadership, and hands-on experience needed to realize AI’s full value.

The majority of U.S. states are still in the “early” or “developing” stages of AI adoption, lacking the robust frameworks, executive leadership, and hands-on experience needed to realize AI’s full value.

While a handful of states are setting up dedicated AI offices, launching sophisticated pilots, and investing in workforce training, most are still building basic capabilities, leaving them at risk of falling further behind as AI accelerates in both the public and private sectors.

AI in Action: Real-World Value for State Agencies

AI’s promise for state agencies is multifaceted, with proven results across the public and private sectors.

Core Value Drivers

• Improved Citizen Experience: AI-powered chatbots in states like Texas and Georgia now handle millions of resident inquiries, from driver’s license renewals to unemployment claims. These solutions provide faster, 24/7 service, and significantly reduce wait times, enhancing the overall citizen experience.
• Cost Savings and Resource Optimization: The U.S. Treasury’s use of AI for fraud detection led to the recovery of $1 billion in check fraud in a single year, while the IRS uses machine learning to detect tax fraud and optimize audit selection, resulting in billions of dollars in prevented fraudulent payments.
• Data-Driven Decision-Making: AI enables agencies to analyze vast datasets for insights, supporting better policy and operational decisions, and driving more effective public service delivery.
• IT Modernization: AI is changing IT organizations in ways never seen before. As an example, AI is accelerating the modernization of legacy IT systems in both government and the private sector. Morgan Stanley leveraged AI to process and document nine million lines of legacy code, saving 280,000 developer hours and enabling faster, more secure modernization of critical systems.
• Operational Efficiency: Pennsylvania’s generative AI pilot enabled 175 employees across fourteen agencies to save an average of 95 minutes per day, freeing staff to focus on higher-value work.

Transformative Efficiency: Morgan Stanley’s AI implementation saved 280,000 developer hours while processing and documenting nine million lines of legacy code, demonstrating the potential for large-scale modernization efforts.

Addressing Challenges and Building Trust

The value of AI is clear, and we’re seeing individual champions experimenting with AI (e.g., an HR analyst using chatGPT for drafting position descriptions, a software engineer using Claude for software development), these promising sparks are likely to result in flames unless agencies take a systematic approach to adoption. The challenge is how to encourage individual agency and innovation we are already seeing, while setting up appropriate governance and a roadmap for future growth.

“AI is quietly rewriting the rules of teamwork—and most organizations haven’t even noticed.”

Shiva Kommareddi, CEO Impact Makers Inc.

Key Challenges

• Data Privacy and Security: Ensuring sensitive citizen data is protected through robust governance and compliance frameworks is paramount. Agencies must implement strong data management practices and adhere to evolving regulatory standards to maintain public trust, answering the question, “How do you create secure infrastructure for enabling AI usage?”
• Workforce Empowerment and Enablement: Supporting staff through training and change management is essential. While organizations are seeing improvements in personal productivity, creating enterprise-wide measurable impacts will remain elusive. The key challenge here is ensuring that everyone gets a chance to be a part of the new future, while laying a foundation of trust for the ensuring change management.
• Hands-On Experimentation: The only way to truly identify what moves the needle for your agency is through hands-on experimentation. Piloting real-world use cases allows teams to learn, adapt, and discover high-impact applications that theory alone cannot reveal.
• Data Readiness: The effectiveness of AI initiatives depends on the quality and accessibility of your agency’s data. Data is never fully ready, so how do you actually get started with AI?

Read the Entire AI Adoption Series for State Agencies

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

• A Framework for AI Opportunity Assessment: Identify where AI can deliver the greatest value in your agency.
• Experimentation and the Role of an Innovation Sandbox: Learn how to safely pilot and scale AI solutions.
• 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.

References

Code for America. “ Government AI Landscape Assessment.“ Pennsylvania Office of Administration. “ Shapiro Administration’s Generative AI Pilot for State Workers.” StateScoop. “Government AI Chatbots on State and Local Websites.” Slashdot. “Morgan Stanley’s AI Tool Processed 9 Million Lines of Legacy Code.” ACT IAC. “Leveraging AI to Modernize Legacy Code in Federal Civilian Agencies.”