Government jobs have always been about service, often guided by mission over profit. But they're also known for process-heavy routines, outdated software and siloed information systems. With AI tools now capable of analyzing data, drafting documents or answering repetitive inquiries, the question facing government leaders isn't just whether to adopt AI, but how to do so in a way that enhances, rather than replaces, the human element of public service.
A common misconception is that AI in government will lead to massive job cuts. But in practice, the trend so far leans toward augmentation. That means helping people do their jobs more effectively, rather than automating them out of existence.
For example, in departments where staff are overwhelmed by paperwork — think benefits processing, licensing or permitting — AI can help flag missing information, route forms correctly or even draft routine correspondence. These tasks take up hours of staff time every week. Offloading them allows employees to focus on more complex or sensitive issues that require human judgment.
Social workers, for instance, aren't being replaced by machines. But they might be supported by systems that identify high-risk cases or suggest resources based on prior outcomes. That kind of assistance doesn't reduce the value of their work. It frees them up to do the work that matters most: listening, supporting and solving problems for real people.
That said, integrating AI into public workflows isn't just about buying software or installing a tool. It touches something deeper: the culture of government work.
Public agencies tend to be cautious, operating under strict rules around fairness, accountability and transparency. Those values don't always align neatly with how AI systems are built or how they behave. If an AI model makes a decision about who receives services or how resources are distributed, who's accountable if it gets something wrong?
This isn't just a technical issue, but it's about trust. Agencies need to take the time to understand the tools they're using, ask hard questions about bias and equity, and include a diverse range of voices in the conversation.
One way to build that trust is through transparency. When AI is used to support decisions, citizens should know how it works, what data it relies on, and what guardrails are in place. Clear communication must be visible and oversight goes a long way toward building public confidence in new technology.
Perhaps the most important piece of this puzzle is the workforce itself. If AI is going to become a fixture in government, then the people working in government need to be ready.
This doesn't mean every employee needs to become a coder. But it does mean rethinking job roles, offering training in data literacy, and creating new career paths for roles like AI governance, digital ethics and human-centered design.
Government has a chance to lead by example here. By investing in employees, not sidelining them, public agencies can show that AI can be part of a more efficient and humane system, one that values experience and judgment while embracing new tools that improve results.
There's no single road map for what AI in government should look like. Different agencies have different needs, and not every problem can or should be solved with technology. But the direction is clear: Change is coming.
What matters now is how that change is managed. If AI is used thoughtfully — with clear purpose, oversight and human input — it can help governments do more with less, while also making jobs more rewarding. If handled poorly, it risks alienating workers and undermining trust.
At its best, AI should serve the public interest. And that means putting people first, not just the people who receive services, but also the people who provide them.
John Matelski is the executive director of the Center for Digital Government, which is part of e.Republic, Government Technology's parent company.
