AI Adoption Rapidly Growing in Public Sector

New AI adoption statistics show AI use is rising in the public sector. In Q4 2025, 43% of public-sector employees report using AI at least a few times a year, including 21% who use it daily or multiple times per week. That figure is up from 17% in Q2 2023 and 28% in Q2 2024.

A similar rate of 41% of private-sector employees report using AI in Q4 2025. Private-sector use is more concentrated among frequent users: 25% use AI frequently and 16% use it occasionally. In the public sector, occasional use is more common at 22%.

In other words, the private sector still leads in frequent use by four percentage points (25% vs. 21%), while the public sector leads in occasional use by six points (22% vs. 16%), putting government slightly ahead on any AI use (43% vs. 41%).

Although these gains reflect a lower concentration of white-collar work in the private sector, they are nonetheless notable because federal AI use, until recently, faced stricter governance and risk controls.

The U.S. public sector has historically struggled to recruit and retain technical talent. In a 2023 report, the Government Accountability Office warned of a “severe shortage of digital expertise, including in the field of AI,” and it has listed strategic human capital management as a high-risk area for government since 2001. Moreover, data from Lightcast on the proportion of job postings that are treated as AI related is under 0.3% in the public sector and under 2% overall. However, new data on employees’ AI use suggests a more optimistic trajectory for the public sector. Even though AI-specific jobs have remained rare in the public sector, AI in public-sector workplaces has tracked much closer to the private sector, especially in 2025.

While these public-sector adoption levels may surprise some observers, they still vary when compared with AI adoption in business across other industries. Use of AI in the workplace is most prevalent in knowledge-based industries and least common in production and service-based sectors. As of Q4 2025, for instance, 40% of employees in finance use AI frequently, compared with 19% in retail. This context places government workers in the middle of the AI adoption curve. Public-sector employees trail industries with the largest concentration of desk- and office-based roles, where AI use is highest. Differences in adoption often reflect role type, especially whether jobs are remote-capable, at least as much as broad-sector technological sophistication.

One reason for this transformation in government could be the nature of today’s AI tools. Unlike earlier waves of digital innovation, generative AI tools are inexpensive, widely accessible and require little specialized training to use. A federal analyst can use an AI chatbot to help draft a report, or a state administrator can use an AI assistant to automate emails, without extensive IT support. The low barrier to entry means employees can experiment with AI on their own, driving up usage even in organizations that lack formal AI programs.

However, another major factor influencing AI adoption is internal leadership and whether managers support the use of AI through experimentation. In particular, prior to Memorandum M-25-21, many federal AI initiatives approached the technology through a risk-management lens — prioritizing privacy, security, procurement compliance, and bias/fairness safeguards — sometimes at the expense of faster, organizationwide adoption and experimentation.

Managerial support is strongly associated with whether AI use becomes routine rather than occasional. In the public sector, 65% of employees in high-support environments use AI frequently, compared with 37% in low-support environments — a 28-point gap. Total use is also slightly higher under high support (88% vs. 78%), while low-support public-sector workers are far more likely to remain “sometimes” users (41% vs. 23%).

The pattern is even more pronounced in the private sector. Where managers actively support AI, 80% of employees are frequent users, versus 44% where support is low, a 36-point difference. Overall use rises from 76% in low-support settings to 94% in high-support settings, and low-support environments contain a much larger “sometimes” share (33%).

These variations are also influenced by differences in the proportion of workers who report whether their organization has a clear AI strategy. In Q4 2025, 37% in the public sector and 53% in the private sector say their organization has a clear AI strategy. Having an AI strategy alone is not enough for digital transformation: Leaders must incorporate clear AI strategies into daily management practices and organizational workflows if they want to shape employee behavior. That begins with conducting task inventories to understand what employees are currently doing, and whether there are opportunities for improvement or potential experimentation.

The absence of clear direction and manager support may help explain the historically lower AI adoption rates in the public sector. Recent findings also highlight one of the more proximate AI adoption challenges: Many employees who have access to AI still don’t use it because they don’t see how the tools apply to their work. Closing this gap requires more than expanding access to technology. Organizations must explain why AI is useful, where it fits in day-to-day work and how employees should use it responsibly. Organizational leaders can accelerate adoption by communicating a clear AI adoption strategy, including guardrails and priorities that build trust and reduce uncertainty.

Managers often serve as the decisive link between strategy and behavior. When managers encourage and model AI use in familiar workflows, employees see how it applies to their work. Examples include drafting routine communications, summarizing lengthy documents or streamlining recurring administrative tasks. These demonstrations help employees view AI as relevant, feel prepared to try it and incorporate it into their daily routines. Stronger managerial guidance in the public sector could turn early experimentation into sustained, higher-frequency use and extend the gains already underway.

Challenges remain for AI in government. Public-sector adoption still lags behind leading private industries, and ongoing concerns about data privacy, security and ethics also remain prominent. Gallup’s research shows that a key part of not only whether employees use AI, but also how they use AI, depends on a broader assortment of management practices, including trust in leadership.

Still, the upward trend in AI usage is clear. During the past two years, federal and state workers have rapidly incorporated AI tools into their daily work, closing what many had assumed was a wide technology gap. Government institutions are not standing still — they are learning, adapting and increasingly taking part in the technological future.