HHS AI audit reviews to scrutinise state health funding oversight and reduce fraud risk
The US Department of Health and Human Services is expanding AI use to analyse audit reports from all 50 states, aiming to identify fraud risks and save public money. Assistant Secretary Gustav Chiarello said tools including ChatGPT will help spot patterns in large documents. Critics urge caution over AI errors and bias in government oversight.
The US Department of Health and Human Services said it is increasing artificial intelligence use. The department said it will review how states and other recipients check programmes. Officials said the plan aims to reduce fraud risks. The department also said it could lower costs tied to federal health spending.

Gustav Chiarello, the assistant secretary for financial resources, said the effort uses ChatGPT. Other AI tools will also support the work. Chiarello said the system will read audit reports from all 50 states. The reviews will run continuously, instead of as one-time checks.
HHS AI tools for audit reports and federal health dollars
States and other groups must submit audits if they spend at least USD 1 million yearly. The rule covers local governments, nonprofits, and higher education institutions. Chiarello said the AI will focus on HHS-funded programmes. These include state Medicaid programmes and federal grants in research and addiction services.
Chiarello said many audits arrive and then get little follow-up. "Its classic big government: Everyone files an audit and it lands with a thud and no one does anything about it,\" Chiarello said in an interview. \"Here, with AI, were able to dig into it.\"
The department said funding could be at risk for some recipients. That could happen if required reports are not filed. It could also happen if issues listed in reports stay unresolved. Officials described the plan as a way to improve oversight of federal health dollars.
HHS AI tools amid wider anti-fraud push and criticism
The move sits alongside a broader anti-fraud focus by the Trump administration. Vice President JD Vances anti-fraud task force has promoted checks in Medicaid. It has also backed checks in Medicare and student loan applications. Federal Trade Commission Chairman Andrew Ferguson said on Fox News that AI is used to flag likely fraud.
Critics said AI can miss key facts and may reflect biases. They also warned that officials should apply extra care. Some critics said the administrations fraud efforts have often focused on Democratic states. They also said actions sometimes come before full fact checks.
The administration has also faced scrutiny over past data use. On one occasion, the administration told The Associated Press it made a major mistake. The data had been used to help justify a New York Medicaid fraud investigation. That episode added to concerns about accuracy in enforcement work.
HHS AI tools safeguards, letters to states, and agency coordination
Asked about errors, Chiarello pointed to the source materials. Chiarello said officials were reviewing public reports, not creating new facts. Chiarello said the goal is improved stewardship of federal dollars. Officials said AI can help spot patterns across long documents.
Rob Weissman, co-president of Public Citizen, questioned the intent behind the initiative. \"The AI is kind of beside the point when you assess what their actual objectives are, rather than what they pretend they are,\" he said. Weissman also said he does not trust fair and nonpartisan use.
HHS said it sent letters to governors and treasurers in all 50 states. The letters said a new AI-based review effort was starting. The program was first reported by The Wall Street Journal. Chiarello said other federal departments could adopt similar tools.
Chiarello said the same technology could be used across agencies. \"It would be fairly easy for the other agencies to use our technology and jump on it,\" Chiarello said. HHS said the continuing reviews will aim to spot risks sooner. Officials said they will press recipients to fix issues found in audits.
With inputs from PTI


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