Timothy S Higgins is Town Administrator in the Town of Lincoln, MA
Timothy S Higgins
Local government is not a technology laggard by accident. Municipal offices operate on constrained budgets, limited staff and a mandate to serve every resident equally well. The default posture has always been to wait for proven tools, not experiment with new ones. AI is changing that calculation faster than most town halls expected.
The work is not being led by large cities with dedicated innovation offices. It is happening in communities like Lincoln, Massachusetts, population 6,000, where a few professionals are discovering that AI delivers outsized returns precisely where resources are tightest.
Timothy S. Higgins, town administrator for Lincoln, oversees daily operations and provides policy guidance to elected leadership. He has worked in municipal management for nearly four decades. His office has become one of the more practical examples of AI adoption in New England local government, and the lessons transfer directly to organizations well beyond the public sector.
Here are five leadership challenges common to small public-sector organizations and how AI is addressing them in Lincoln.
Institutional change in local government rarely starts with a directive from above. It starts with a trusted voice making a credible case. Lincoln's introduction to AI came through a resident with deep expertise in the field and a long history of civic involvement. He ran a workshop for senior staff and offered two ideas that reframed the conversation. First, AI will not replace you, but it will put you behind colleagues who use it well. Second, think of AI as a highly capable, eager-to-please intern.
That framing gave Higgins' team permission to experiment without waiting for a formal policy. Enthusiasm spread organically. Staff who once started the day comparing sports scores now share what they built with an AI tool the night before.
Leadership move: Identify the credible internal voice before you build the program. Peer-driven adoption moves faster and holds longer than top-down mandates.
A town of 6,000 residents does not have a research bureau, a data analytics team or a communications department. For decades, smaller municipalities have accepted that they will always lag behind larger jurisdictions in analytical capacity. AI is removing that assumption.
Lincoln’s staff now uses AI to automate meeting minutes, conduct benchmark analyses across peer communities and compare demographics, financial performance, staffing levels and compensation structures. Work that previously required days of manual research now takes hours. The time recovered flows into higher-value decisions. Higgins believes AI is an especially powerful tool in the public sector where data is largely open and accessible, and where there is a strong culture of collaboration and sharing among local governments.
Higgins describes the effect plainly: AI functions as a research bureau in the basement of Town Hall.
Leadership move: Frame AI adoption around staff leverage, not headcount reduction. In a small organization, an hour recovered per employee per day is a structural advantage.
Municipal policy work involves dense legal source material, including state statutes, local bylaws, zoning regulations and compliance requirements. Staff with generalist backgrounds are frequently asked to interpret specialized language quickly. Errors create downstream problems that are costly to unwind.
Lincoln is using AI to interpret and translate complex laws and regulations, draft and update policy manuals and prepare foundational research for a strategic plan refresh. The tools do not replace legal counsel or expert judgment. They compress the preparation time and improve the quality of the starting point.
Leadership move: Deploy AI at the research and drafting layer, not the approval layer. Accuracy improves when subject matter experts review AI-generated work rather than build from scratch under time pressure.
Lincoln residents are highly engaged. They want to understand how decisions are made, not just what was decided. That expectation places a constant demand on staff to produce clear communications, well-structured surveys and accessible public documents.
AI now supports the design and analysis of resident surveys and accelerates the publication of meeting minutes. Both improvements directly serve transparency. Faster minutes mean residents access information sooner. Better-designed surveys produce more reliable feedback for policy decisions.
Higgins notes a secondary effect worth tracking. Residents are also using AI to research town issues, which increases the sophistication of public input. It also introduces risk when AI-generated conclusions are based on incomplete or unverified data. Staff need to be prepared to address well-informed but occasionally inaccurate claims.
Leadership move: Treat AI-enabled resident engagement as a two-way dynamic. Invest in public communication quality to match the analytical capacity your constituents are acquiring on their own.
The risks in public-sector AI are well documented: privacy exposure, security gaps and the potential for AI-generated inaccuracies to inform official decisions. The instinct in local government is to address risk with process layers, which slows adoption and frustrates staff.
Lincoln's approach is to treat verification as a professional standard rather than a procedural gate. AI outputs require review by staff with relevant subject matter expertise before they inform any formal decision or public communication. The tools used, primarily ChatGPT and Claude, are treated as drafting and research assistants, not authoritative sources.
That posture keeps risk manageable without adding bureaucratic weight. It also reinforces a skill that effective public servants already have: the ability to evaluate the quality of information before acting on it.
Leadership move: Define AI risk governance around verification standards, not tool restrictions. The question is not which tool staff uses. The question is whether staff knows how to evaluate what the tool produces.
Lincoln’s AI program is not a technology project. It is an operating model improvement built around a small team with limited resources and high public accountability.
A: AI tools can be introduced using existing staff and low-cost platforms to automate routine work like meeting minutes, research and reporting. This frees up time for higher-value tasks without adding headcount, effectively expanding capacity within current budget constraints.
A: Early wins typically include faster document drafting, automated summaries of public meetings and quicker policy research. These improvements reduce turnaround times, improve communication with residents and give leadership faster access to decision-ready information.
A: Set a clear expectation that AI supports research and drafting, not final decisions. Require subject matter experts to review outputs before use, and rely on trusted data sources. This keeps accountability with staff while still capturing the efficiency gains AI provides.
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