AI is upending business, our personal lives, and much more in between—including the operation of the US government. Totally, The Washington Post reported 2,987 uses of AI across the executive branch last year, hundreds of which are described as “high impact.”
Some agencies have embraced the technology wholeheartedly. NASA has gone from 18 reported AI applications in 2024 to 420 in 2025; the Department of Health and Human Services, overseen by Robert F. Kennedy Jr., now reports 398 uses, up from 255 a year ago. The Department of Energy has seen a fourfold increase in AI usage, with a similar jump at the Commerce Department. Agencies were effectively given the green light in April 2025, when the White House announced it was eliminating barriers to AI adoption across the federal government. They appear to have taken that invitation seriously.
Those numbers may raise eyebrows—or trigger concern among observers worried about bias, hallucinations, and lingering memories of the chaotic AI-enabled government overhaul associated with the quasi-official Department of Government Efficiency during Elon Musk’s brief orbit near the center of power.
“It’s not clear using AI for most government tasks is necessary, or preferable to conventional software,” cautions Chris Schmitz, a researcher at the Hertie School in Berlin. “The digital infrastructure of the US government, like that of many others, is a deeply suboptimal, dated, path-dependent patchwork of legacy systems, and using AI for ‘quick wins’ is frequently more of a Band-Aid than a sustainable modernization.”
Others who have worked at the center of government digital innovation argue that alarmism may be misplaced. In fact, they say, experimenting with AI can be a form of smart governance—if done carefully. “It’s become apparent that we never really properly moved government into the internet era,” says Jennifer Pahlka, cofounder and chair of the board at the Recoding America Fund and former US deputy chief technology officer under the Obama administration. “There have been real problems that have come out of that where government is just not meeting the needs of people in the way that it should.”
Pahlka believes that experimentation with AI in government is “probably somewhat appropriate” given how early we are in the generative AI era. Testing is necessary to understand where—and where not—the technology can improve operations. “What you want, though, is ways of experimenting with this that gives you very clear and effective feedback loops, such that you are catching problems before it’s rolled out to large numbers of people or to have a large impact,” she says.
Still, it is far from certain that AI systems will produce outcomes that serve all Americans equally. Denice Ross, executive fellow in applied technology policy at the University of California, Berkeley, warns that rigorous evaluation is essential. “The way the government would find out if a tool is doing what it’s supposed to for the American people is by collecting and analyzing data about how it performs, and the outcomes for different populations,” says Ross, who served as chief data scientist in the White House from 2023 to 2024.
