Federal Manager's Daily Report

Common usage included enhanced anomaly detection, streamlined business processes, and improved decision-making. Image: Tada Images/Shutterstock.com

Federal agencies more than doubled their publicly reportable uses of AI in 2024 to more than 1,700, according to the CIO Council, with agencies “predominantly leveraging AI to assist with administrative and IT functions; however, AI use cases in health and medical applications closely follow.”

“Roughly 46% of AI use cases across the federal government are categorized as mission-enabling, which includes management of finances, human resources, and facilities and properties. This category also captures agency cybersecurity, IT, procurement, and other administrative functions,” says a posting on cio.gov.

“While agencies cite a host of expected benefits from their AI use, some common themes include: enhanced anomaly detection, streamlined business processes, and improved decision-making,” it adds.

The report covers 37 agencies outside Defense, the intelligence community and R&D; of those, HHS, VA, DHS and Interior account for more than half, with 13 percent categorized under health and medical and 9 percent categorized as supporting government services or benefits delivery. “Other areas of application include law and justice, education and workforce, transportation, science and space, and energy and the environment,” it said.

Other key points, it said, include that about half of use cases are developed in-house; 40 percent involve custom-developed code, much of which is publicly available; more than a third are developed on existing enterprise data and analytics platforms within an agency or re-use production-level code and/or data from a different use case.

It added that 13 percent meet standards under OMB guidance of potentially impacting the public’s rights or safety. Of those, agencies have completed the required impact assessments on more than 80 percent, and more than half “have an established process in place to appeal or contest an AI system’s outcome and/or opt-out from the AI functionality in favor of a human alternative.”

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