GovLoop research, conducted with Granicus and Carahsoft, finds state and local government is more confident managing AI risk than the national average but faces bigger procurement hurdles and more resident pressure.
The challenge for US government workers is not understanding AI’s potential. It’s lacking the staff, infrastructure and internal policies needed to turn that potential into results.
GovLoop research, conducted with Granicus and Carahsoft, surveyed 121 state, local and federal government workers to show nearly 60% cited a lack of staff capacity as a top barrier to progress. Separately, 65% named security of the AI model and the underlying data as a top concern, the single most cited worry in the survey.
Just over half said their systems don’t talk to each other well enough to make AI work as intended. Only 17% see a lack of good use cases as a real problem.
Where state and local diverges from the national picture
A closer look at 63 respondents from state, city and county government shows the same basic story but with real differences worth noting, some encouraging and some less so.
On the positive side, state and local workers report more confidence in managing AI risk than the national average. Nearly 70% describe themselves as at least moderately confident their organization can manage AI-related risks, compared with just over 60% nationally.
State and local respondents are also less likely to say unclear leadership direction is holding them back, at 32% compared with 39% nationally and less likely to say a lack of proven results is a barrier, at 30% compared with 37% nationally.
On the less positive side, state and local government reports significantly higher friction from procurement. Procurement hurdles are cited as a barrier to modernizing services by 43% of state and local respondents, compared with 35% nationally.
State and local workers also report feeling more pressure to keep pace with what residents expect. Nearly 73% describe moderate to high pressure to deliver faster, simpler services, compared with roughly 62% nationally.
Just 8% of state, city and county respondents describe their agency’s AI governance as centralized and mature. Nearly 43% say governance rules are still being written and 38% describe their approach as informal or ad hoc.
What happens if agencies don’t act
State, city and county respondents were also asked what happens if their agency fails to modernize resident service access over the next two years and the answers point to operational cost, not just missed opportunity.
Over 52% expect rising operational costs. Just over 50% expect increased backlogs and slower response times for residents and the same share expect higher staff burnout and turnover.
Nearly 48% expect difficulty meeting mandates or compliance requirements. Only 36.5% believe there would be no significant consequences at all.
“People at the state and local level aren’t wondering if AI can help them. They already know it can,” said Karthik Anbalagan, General Manager of Emerging Technologies, Granicus. “What’s interesting is they’re more confident managing the risk than their federal counterparts. What’s holding them back isn’t confidence. It’s procurement friction and governance rules that haven’t caught up yet. And the survey is clear that standing still isn’t free. Agencies that wait are telling us they expect additional costs, longer waits for residents and burned out staff.”
The trust problem
Anbalagan said much of the concern around AI comes down to a simple question people can’t yet answer: where is this information coming from?
“If you don’t know where the answer came from, you don’t trust it,” he said. “Agencies need to know their AI is only using information they’ve approved, not pulling from wherever it finds something online. If the information behind it is out of date or messy to begin with, AI just repeats those same mistakes faster.”
What this means
The data points to a government AI conversation that has moved past ideas and into execution. Agencies that invest in staff capacity, clean data and clear governance are positioned to move faster. Agencies that wait are telling researchers, in their own words, what that wait is likely to cost them.
“You can’t fix a people problem with just technology alone,” Anbalagan said. “The agencies getting ahead are training their staff, cleaning up their data and being clear about who owns what. That’s where it starts, and right now state and local government has the confidence to do it. What it needs is fewer procurement roadblocks and clearer governance to match.”
