The State of AI in Public Health: New Data from the 2025 ASTHO Profile

April 28, 2026

Since 2007, the Association of State and Territorial Health Officials (ASTHO) State and Territorial Public Health Profile (ASTHO Profile) has served as an authoritative source of data on the activities, structure, and workforce of state and territorial public health agencies. In anticipation of the release of the 2025 ASTHO Profile later this year, we are pleased to provide an early look at how state and territory health agencies are addressing the rise of artificial intelligence. (AI). Data based on responses from 41 state and territorial health departments (n=32-44, depending on question) reveal that the public health landscape is in transition and there are significant differences in how agencies approach and utilize these new tools.

AI policy and monitoring

Although the origins of these policies vary, the majority of government agencies have established some form of policy framework regarding AI.

• Policy adoption: 52% of agents Statewide policy11% Agency-specific policies.
• under development: 9% of agencies are currently developing a policy, but 25% have not yet adopted one.
• Priority policy: Of the 28 agencies with policies; Data governance, privacy and security It is the most commonly covered topic (81%).
• Other topics: Policies also frequently address: Evaluation and accountability (59%) and Identifying use cases (53%), but only 34% address it Leadership and employee readiness.

Current AI usage and tools

Government agencies typically use AI for administrative tasks rather than specialized public health functions.

• Main usage examples: The most common applications are: Streamline management and operations (30%) and Content reporting (30%).
• specialized tasks: Only 14% of agencies report using AI to: Disease surveillance, anomaly detection, or emergency response.
• Software type: 23% of agencies use consumer-generated AI tools; 32% use consumer-generated AI tools; Enterprise AI environment.
• non-user: Approximately 34% of agents report doing so. Not using AI It doesn’t matter if it’s a system or software. How is AI being implemented?

How is AI being implemented?

Public health is now using AI for extensive administrative support and highly specialized technical efforts. At the federal level, CDC successfully saved more than 5,500 labor hours by using enterprise AI solutions for a variety of use cases, including analyzing unstructured grant reports. Similarly, a handful of states, such as Minnesota and California, are leveraging AI to conduct real-time disease surveillance, which can identify outbreaks weeks earlier than traditional systems. However, this level of integration is rare at the state and territory level. A large gap exists between companies using consumer products and companies using enterprise systems. While 23% of government agencies use consumer tools for non-sensitive tasks, 32% have invested in enterprise environments that can securely process electronic health records for surveillance and outbreak response.

path to integration

The 2025 ASTHO Profile highlights an area in flux where policy development is outpacing actual implementation. While one-third of government agencies report no use of AI at all, the majority are experimenting with administrative use cases while facing significant barriers in employee skills and resource constraints. Closing this gap requires a shift from individual best efforts to shared infrastructure and expanded AI literacy across the public health workforce.

ASTHO Data Modernization and AI Support

ASTHO views AI as a critical component of a modern, responsive data ecosystem and actively supports jurisdictions through a wide range of data modernization initiatives. AI helps government agencies process the growing volume and velocity of public health data more efficiently by moving from manual to automated processes. At a time when physical labor is constrained, solutions that streamline tasks and save time are a significant opportunity. To support jurisdictions in their AI efforts, ASTHO provides direct technical assistance and provides hands-on implementation support. Government agencies can also leverage the Informatics Director Peer Network to share promising practices and navigate the ethical use of these tools.

2025 ASTHO Profile Survey Questions and Answers

Table 1: Has your public health agency adopted artificial intelligence (AI) policies? (N=44)

Yes, as part of a statewide policy	twenty three	52%
Yes, this is an agency-specific policy	5	11%
No, but there is a policy in development	4	9%
No, we do not have an AI policy	11	twenty five%
I don’t know	1	2%
Please specify other details.	2	5%

Table 2: Which of the following topics are covered in your agency’s AI policy? (N=32)

Data governance, privacy and security	26	81%
bias	11	34%
Leadership and employee readiness	11	34%
Identify and test use cases	17	53%
Evaluation and accountability	19	59%
Transparency and “explainability”	16	50%
technical preparation	11	34%
other	4	13%

Table 3: How is your health organization using AI? (N=44)

Management and operational efficiency	13	30%
Create content and reports	13	30%
Chatbots and conversational agents	9	20%
other	8	18%
Generate or modify code	8	18%
Communication campaigns and community engagement	7	16%
Anomaly detection, disease surveillance, or predictive modeling (combination)	6	14%
HR support	4	9%
No AI used	14	32%

Table 4: Which AI systems/software are used within public health organizations? (N=44)

Consumer-generated AI tools (e.g., OpenAI’s ChatGPT, Google’s Gemini, Anthropic’s Claude)	10	twenty three%
Enterprise AI tools (including vendor-developed or in-house developed)	16	32%
We do not use AI systems/software within public health agencies	15	34%
Other (e.g. CoPilot included in your Microsoft 365 subscription)	6	14%

Table 5: What challenges have you encountered when integrating AI into your work? (N=44)

Lack of established guidance on the use of AI in public health	28	64%
Lack of employee skills and knowledge	twenty four	55%
Concerns about AI-based data accuracy	20	45%
Lack of resources (funding, staff, partners, etc.)	17	39%
Legal or policy barriers	17	39%
Concerns about data fairness and representativeness	13	30%
Lack of evaluation data on tested use cases	12	27%
Other efforts are more important	11	twenty five%
Technical challenges (platform integration or interoperability)	9	20%
other	7	16%
Lack of coordination within the health sector	6	14%
Lack of public trust in AI technology	6	14%
Lack of leadership or staff support/buy-in	4	9%
we have not encountered any challenges	4	9%

Key ASTHO AI and data resources