As they gain data maturity, state and local agencies are increasingly putting their information to work.
In Washington, D.C., a real-time information dashboard helps first responders manage blood used for field transfusions. It captures data from computer-aided dispatch and automated vehicle location systems, as well as status and temperature information from storage facilities to ensure blood supplies used by city emergency crews are adequate and viable.
In Ohio, data and predictive analytics power the RecoveryOhio Overdose Early Warning Dashboard, which identifies communities where drug overdoses could spike. Drawing on multiple data sources, the dashboard predicts ZIP codes with increased overdose risk up to 30 days in advance, giving local leaders a window to intervene.
In Salt Lake County, Utah, departments are building their own internal dashboards to share real-time budget information and operational metrics across the organization. This effort, along with staff training on data visualization and analysis tools, is creating a data culture within the county workforce.
These examples come from a new Center for Digital Government* (CDG) report that examines how states and localities are building the policy and technology foundation to use data more effectively — to address complex issues, improve efficiency and performance of important programs, and fuel the growth of artificial intelligence.
Drawn from a daylong live conversation at CDG’s live Future of Data Summit earlier this year and supplemented by follow-up interviews with key contributors, the report identifies fundamentals for advancing the effective use of data in government.
Strengthening, Standardizing and Simplifying Data Governance
Concepts like data-informed decision-making and personalized public services rely on good data — and that requires effective data governance. But governance practices vary widely across jurisdictions.
Most states lack data quality programs, according to a 2024 National Association of State Chief Information Officers survey, and only about half of states have appointed chief data officers to lead data initiatives. Data governance is getting more attention, however, as states address issues such as rising privacy expectations and the need for reliable data to fuel artificial intelligence.
The CDG report shows how multiple jurisdictions are strengthening governance policies. For example, Utah Chief Privacy Officer Christopher Bramwell is leading an effort to establish a cohesive data governance strategy across all levels of government in his state. One goal is to identify data sets commonly used by state and local agencies and establish standard rules to govern how that information is managed and protected.
In addition, the report breaks down important components of data governance, such as data catalogs, data quality, master data management and data models. It also looks at crucial concepts like identifying high-impact data sets and understanding their business value.
Defining Data Ethics and Privacy in the AI Era
States and localities must take the lead on developing data ethics and privacy rules as they increase their AI use. Most data governance frameworks are developed for the private sector, so they may not address unique government ethics, privacy and security responsibilities. States and localities need to fill that gap with comprehensive yet agile AI rules and guidelines, the report says.
One example comes from Ohio, where the state’s data program has adapted to changing technology since its formal launch in 2017. The program initially focused on data sharing to improve services, inform policy, and reduce waste and abuse. A 2019 executive order created InnovateOhio, a unified digital data and analytics platform that lets agencies securely share and use data to improve the constituent experience. Additional state policy, issued earlier this year, seeks to support AI innovation while protecting data privacy and security.
Strong yet nimble data policies — including privacy and security safeguards — are crucial to encourage data sharing, support AI innovation and build public trust.
Modernizing and Scaling Data Infrastructure
More states and localities are upgrading data architectures and platforms to support future needs, according to the report. Again, these efforts are typically driven by interest in AI, and they include creating data lakes to integrate data in legacy systems, using the cloud to modernize old technologies and setting the architectural vision for future data infrastructure.
Raleigh, N.C., is making a range of moves to strengthen its data maturity — from rethinking the amount of data collected by city departments to implementing a new platform to manage data security. In addition, the city recently created a road map for using autonomous AI agents and is gauging departments’ interest in incorporating agentic AI.
Marina Kelly, Raleigh’s chief information security officer, says organizations must approach data policy and technology with much greater agility.
“It used to be that you set your data management, and you held to your policies, and you’d review those once every year or two,” she said. “That has completely changed with generative AI. Data management has to be much more dynamic, equitable and secure — but it also has to be deeply integrated into the organization itself.”
Download the full report.
*The Center for Digital Government is part of e.Republic, Government Technology’s parent company.
