Agencies warming up to AI
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As artificial intelligence demonstrates savings and manpower efficiencies, agencies are moving from experimentation to wider implementation.
Federal agencies are riding a rising tide artificial intelligence-driven data and applications and moving from experimentation to wider implementation, according to a recent study on federal AI adoption released by the Professional Services Council Foundation.
As the technology demonstrates savings and manpower efficiencies, "AI isn't optional" for federal agencies any longer, PSC Executive Vice President and Counsel Alan Chvotkin said.
Researchers interviewed over a dozen senior technology and IT officials at agencies such as the Department of Treasury, the U.S. Postal Service, HHS, the National Institutes of Health and others about their AI implementations.
They found several common themes related to handling, steering or combining massive amounts of data throughout an agency. Agencies primarily look to AI to take over routine, data-oriented tasks; ease access to data in diverse databases and systems; assist in prioritizing work by showing which tasks would yield the maximum benefit; and help keep track of the ever-rising stream of incoming data.
It's not all smooth sailing, though.
"Agencies struggle with who owns the data," PSC President and CEO David Berteau said. AI encourages data sharing to produce maximum efficiencies, but ownership of that data can be a sticking point for agencies that silo their data and are reluctant to share, he said.
"Agencies that have a chief data officer have moved out a little farther" with AI implementation, according to Dominic Delmolino, managing director and CTO at Accenture Federal Services, which underwrote the study with the PSC Foundation. The CDO can determine what data is shareable to give it the maximum impact across agency operations.
According to Chvotkin, even though the AI genie appears to be out of the bottle for government implementation, agencies must ensure they've laid the groundwork before moving ahead.
That foundation includes developing a business case that lays out how the technology will return its investment, building AI competency in the workforce and setting ethical boundaries. One of the most important things agencies can do to maximize the effects of AI, according to Chvotkin and the study, is to build an internal "analytics culture" with leadership that embraces the technology, employees who develop new skills and a commitment to open communication about the changes and challenges in adopting AI.
This article was first posted to FCW, a sibling site to GCN.
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