Public health departments across the United States are about to test generative AI tools from OpenAI and Anthropic in a new pilot programme that could reshape how disease outbreaks are tracked, how emergency responses are coordinated, and how health data is analysed in real time.
What the PULSE programme actually does
The Public Health Use Case and Learning Scaling Engine — PULSE — is a structured initiative that will support trials in 10 state, local, tribal, or territorial public health jurisdictions. The programme is led by the Coalition for Health AI (CHAI), a group focused on responsible AI adoption in healthcare.
OpenAI and Anthropic have each donated 10 enterprise licences with capacity for up to 2,000 public health practitioners. Accenture, the global consulting firm, will manage participant onboarding and help develop playbooks based on what the trials reveal.
Why public health agencies need AI tools now
Public health departments have long struggled with data overload — from hospital reports, lab results, environmental sensors, and community health surveys. During the COVID-19 pandemic, many agencies were overwhelmed by the volume and speed of information. AI tools could help by automating data analysis, flagging anomalies, and generating real-time summaries for decision-makers.
The PULSE programme is designed to test whether generative AI can handle these tasks reliably, ethically, and securely in a public health context.
How the pilot came together
The Coalition for Health AI has been working on frameworks for responsible AI use in healthcare for several years. The PULSE programme emerged from discussions about how to move from theory to practice — giving public health agencies hands-on experience with enterprise-grade AI tools before making large-scale procurement decisions.
OpenAI and Anthropic were approached because of their leading positions in generative AI. Both companies agreed to donate licences and technical support. Accenture was brought in to provide implementation expertise and to ensure the trials produce actionable guidance.
Who will be affected
The 10 participating jurisdictions have not been publicly named yet, but they are expected to include a mix of state health departments, local county health offices, tribal health authorities, and territorial agencies. For the public health practitioners involved, this means access to tools that could reduce administrative burden and improve analytical capacity.
For the broader population, the outcomes of these trials could determine how quickly and accurately future public health threats are detected and communicated.
What CHAI, OpenAI, and Anthropic have said
The Coalition for Health AI has described PULSE as a "learning engine" — meaning the programme is designed to generate insights, not just test technology. OpenAI and Anthropic have emphasised their commitment to responsible deployment. Accenture has stated it will focus on creating playbooks that other agencies can follow.
No specific public health use cases have been detailed yet, but likely applications include disease surveillance, outbreak modelling, emergency communication drafting, and data quality improvement.
What this means for AI in public health
The PULSE programme is significant because it moves generative AI from experimental chat interfaces into mission-critical government functions. Public health agencies have been cautious about adopting AI due to concerns about accuracy, bias, privacy, and accountability. This pilot is designed to test those concerns in a controlled, supervised environment.
If successful, PULSE could become a model for how other government sectors — from environmental protection to transportation safety — evaluate and adopt generative AI tools.
Confirmed facts vs what remains unclear
Confirmed: The PULSE programme involves CHAI, OpenAI, Anthropic, and Accenture. Ten US public health jurisdictions will participate. OpenAI and Anthropic have donated 10 enterprise licences each. Accenture will handle onboarding and playbook development.
Unclear: The specific jurisdictions have not been named. The exact use cases for the AI tools have not been detailed. The timeline for the trials and the criteria for success have not been publicly disclosed. It is also unclear whether the programme includes any independent oversight or audit mechanisms.
Risks and concerns to watch
Generative AI models are known to produce inaccurate or misleading outputs — a risk that is especially serious in public health settings where decisions can affect lives. Privacy is another concern: public health data often includes sensitive personal information. Bias in AI models could lead to unequal treatment of different communities.
Critics have also questioned whether the involvement of commercial AI companies in public health could create conflicts of interest or lock agencies into proprietary systems. The programme's reliance on donated licences raises questions about long-term sustainability and independence.
The bigger trend: AI enters government operations
The PULSE programme is part of a broader shift toward AI adoption in government. The US federal government has issued guidance on AI use, and agencies like the Department of Veterans Affairs and the Centers for Disease Control and Prevention have been exploring AI tools. What makes PULSE different is its focus on local and state-level public health — the front lines of disease response.
Other countries are also watching. The UK's National Health Service and India's Ministry of Health have both signalled interest in AI for public health. The outcomes of PULSE could influence global approaches.
What public health officials should do now
For public health agencies not yet involved in PULSE, the key takeaway is to start preparing. This means understanding what generative AI can and cannot do, assessing data readiness, and developing internal policies for AI use. Agencies should also engage with CHAI's frameworks and follow the playbooks that emerge from the trials.
For practitioners, this is a moment to learn about AI tools and to advocate for transparent, accountable deployment.
What happens next
The PULSE programme is expected to run for several months, with findings and playbooks released publicly. If the trials show clear benefits and manageable risks, more public health agencies could begin adopting generative AI tools. If problems emerge, the programme could slow down or shift direction.
The long-term impact will depend on how well the programme balances innovation with caution — and whether the guidance it produces is practical enough for cash-strapped public health departments to implement.
Our Take
The PULSE programme is a sensible, measured step toward integrating generative AI into public health. It avoids the hype-driven rush that has characterised some AI deployments in other sectors. By focusing on real-world trials, implementation guidance, and multi-stakeholder oversight, CHAI and its partners are doing the hard work that responsible AI adoption requires.
The risks are real — accuracy, privacy, bias, and vendor lock-in — but the potential benefits are also significant. The key will be transparency: the public deserves to know what these tools are being tested on, what the results show, and how decisions are being made. If PULSE delivers on its promise of open playbooks and shared learning, it could set a standard for AI in government that other countries and sectors can follow.
Frequently Asked Questions
What is the PULSE programme?
PULSE stands for Public Health Use Case and Learning Scaling Engine. It is a pilot programme that will let 10 US public health jurisdictions test generative AI tools from OpenAI and Anthropic. The goal is to produce implementation guidance for other agencies.
Which companies are involved in PULSE?
The programme is led by the Coalition for Health AI (CHAI). OpenAI and Anthropic have donated enterprise licences. Accenture is managing participant onboarding and developing playbooks.
How many public health practitioners will have access to AI tools under PULSE?
OpenAI and Anthropic have each donated 10 enterprise licences with capacity for up to 2,000 public health practitioners in total.
Why is this programme important for public health?
Public health agencies face data overload from multiple sources. Generative AI could help with disease surveillance, outbreak modelling, and emergency response. PULSE will test whether these tools work reliably and ethically in real public health settings.
