Sustaining AI in Local Government

As cities and municipalities explore Artificial Intelligence's (AI) potential, there is increasing optimism about using this technology to bolster their local governance. City governments are some of the most feasible and impactful environments for change within the public sector, making them ripe for reaping the benefits of emerging tech. Innovations in AI for local public services are already underway: Barcelona is using the tech to optimize public transportation speeds, Long Beach, CA, is piloting an AI chatbot to help constituents navigate the city’s website, Buenos Aires is applying AI to streamline waste collection, and Amsterdam is using AI tools to reduce district energy use. Community pilots demonstrate AI’s capacity to bridge gaps between governments and their communities, enabling more responsive services that prioritize their constituents’ unique needs.

To successfully integrate AI in local governments, it’s important to not only focus on the technology’s potential but to also recognize and navigate the unique challenges of applying AI to the public sector’s local levels. While the U.S. maintains low unemployment nationally, state and local governments disproportionately face significant workforce shortages, with over 500,000 positions remaining unfilled since early 2020. Implementing AI in this context requires thoughtful strategies to ensure that the technology is used effectively, responsibly, and perhaps—most importantly—with longevity. To do so, we must consider a key question: How can we implement AI when local governments already lack capacity while centering communities?

The answer lies in intentionality. Investment in AI alone will not bring long-term success for using AI in governance. Instead, there are three guiding principles—three Ts—that would lay the conditions for AI to be responsibly integrated into local governments: Transition, Transfer, and Trust.

Transition: Streamlining Bureaucratic Processes

To maximize AI's impact in public service, an openness to transition toward automating repetitive tasks is essential. This shift can reduce burdens on often strained civil services and frees up government employees’ time so they can focus on areas in which human judgment and human interaction are essential.

One of the most significant advantages technology offers is its ability to automate repetitive and time-consuming tasks. Civil servants notoriously have overwhelming administrative burdens, and these burdens can be lessened by delegating AI tools for tasks like form processing and data entry. In doing so, government employees can be freed to focus on more complex, specialized tasks. Ultimately, city governments can demonstrate how institutions are able to actively choose to incorporate AI in ways that improve performance without contributing to job displacement.

This moment in AI technology is not the first time an innovation has been posed to evolve the workforce. Throughout history, the introduction and adoption of technology—from the printing press to the tractor—has led to a changing workforce with more time to develop specialized skills rather than focusing on monotonous tasks, such as scribing copy or harvesting crops. AI presents a similar opportunity to stimulate the growth of more specialized skills in civil servants, like emerging IT management or focused community engagement. A recent report from the World Bank outlined how AI has helped with tasks such as synthesizing public opinion to relieve civil servants of manually sorting tens of thousands of individual comments, automating the otherwise time-intensive manual bid rigging auditing process, and rapidly detecting tax evasion amid extensive government forms.

To implement this transition effectively, city governments must comprehensively audit their existing processes to identify opportunities for automation while, more importantly, creating and prioritizing job skills training for more specialized human roles. Building pathways for civil servants to develop the skills for newly-identified roles will protect job security in the face of automation.

Transfer: Building Cross-Government Data Interoperability

Effectively applying AI to local governance relies on seamless data integration across agencies. Without interoperable systems, AI's insights remain limited, undermining its potential to improve decision-making and service delivery.

Data interoperability is the ability to securely exchange data across systems. Artificial intelligence is only as good as the data it uses; local governments possess vast amounts of data housed in different systems or offices that cannot be used by one AI system, rendering its analysis less constructive. Without effective data collaboration, AI struggles to provide comprehensive insights that can drive informed decision-making. To maximize the utility of AI, city governments must prioritize developing interoperable infrastructures that enable seamless data sharing across agencies.

The City of Los Angeles’s GeoHub platform is a leading precedent for the utility of interoperable systems, providing real-time sharing of over 500 datasets across 20 city departments for valuable information like traffic patterns, public health metrics, or environmental data. Such data sharing supports cross-agency collaboration in areas like emergency response, urban planning, and traffic management. GeoHub opens opportunities for city staff to spend less time searching for existing data and more time using location-based data for Los Angeles’s leading initiatives in keeping streets clean, climate resilience, or improving pedestrian safety.

Establishing these interoperability systems requires initial investments in technology and infrastructure, but the long-term benefits—including enhanced decision-making capabilities and improved service delivery—far outweigh those initial costs. A failure to invest in technology can be devastating in the long run, as we’ve seen with cybersecurity and how data breaches have been estimated to cost governments $26 billion in the past eight years.

Trust: Building Public Confidence

Trust in government is essential for any new government initiative, especially something as novel as AI. Establishing transparent, ethical practices in using AI in local governments is crucial to fostering public confidence and engagement.

Public trust is not only about technical execution, it requires a cultural shift away from opaque bureaucracy toward open engagement with constituents. Nowadays, trust in government institutions is at an all-time low. There are also concerns about how AI intensifies data collection, strains privacy, amplifies bias, and operates via “black-box” decision-making; these issues amplify the skepticism toward government. That being said, municipal governments must face these obstacles to trust head-on. Successful AI integration must prioritize meaningful community engagement and individuals’ agency.

This presents an opportunity for governments to set a new standard in transparency by openly communicating when, how, and why AI might be used. For example, California’s proposed CPPA rules on automated decision-making require pre-use notices, opt-out options, and clear access rights, opening public conversation about AI to address concerns early and foster a collaborative approach to governance.

Governments of all sizes have different ways of garnering public trust, including oversight bodies, ethics committees, and even informal public forums. Both technical transparency and community engagement are critical for building trust, as is consistency with ensuring residents are meaningfully involved in local governance. Take, for instance, New York City’s pilot model of participatory budgeting that invites citizens to propose and vote on ways to spend a portion of the city’s budget through their Online Idea Map. This type of participatory process could benefit from AI’s ability to increase capacity by helping anonymize citizen ideas, transparently clustering inputs by theme, or providing live updates on existing projects. AI opens pathways to prioritize privacy, transparency, and fairness, and to truly build public confidence, city governments must lead by example.

Moving Forward

City governments are one of the most promising arenas for the thoughtful implementation of AI due to their manageable scale, hyper-localized specificity of challenges, and potential for bureaucratic innovation. However, success in this endeavor hinges on thoughtfully transitioning to automating bureaucratic processes, creating transfer systems for data interoperability across departments, and building trust through ethical guidelines and community pilots.

Moving forward, city governments can take the lead in bolstering local governance with AI. They can do so through thoughtful adaptation, structured data sharing, and community-centered approaches. One such example emerging out of New America’s Technology and Democracy programs is RethinkAI, a cross-sector collective of institutions, scholars, and practitioners working to catalyze safe, effective, and equitable AI efforts that transform how local government operates. RethinkAI’s pilot method focuses on how informed decisions get made, who has access to the information necessary to make those decisions, and how people and institutions are held accountable after that. Through research, ambitious pilots, and a robust community of practice, RethinkAI aims to have cities across the U.S. adopt a common framework—coupled with extensive computational infrastructure—that will facilitate developing and scaling responsible and effective AI solutions across locales.

The opportunity at hand, as cities responsibly embrace AI technology, is not just adopting new tools but transforming local governance itself—making it more efficient, inclusive, and responsive to citizens’ needs.