Local governments across the United States are among some of the first organizations to embrace AI and transition into a whole new era of delivering citizen services and supporting community growth and development. While it might seem counterintuitive for local governments that are chronically short staffed and underfunded to embrace an expensive and novel technology, the benefits that AI in its predictive, generative, and agentic forms can bring to counties and localities are immense. However, to optimize the benefits of AI in service delivery and other applications, localities and counties need to plan wisely.
The Promise of AI for Local Governments
The importance of AI to city government and other localities can never be overestimated. With budgets funded from property, sales, and other taxes, as well as the transfer of funds from state and federal government agencies, local government funding has never been robust. And today, with little appetite to raise taxes on an inflation-weary population and as uncertainty about the continuation of federal funding for many programs, these fiscal pressures are felt keenly.
One of the inevitable outcomes of a tight fiscal base is staffing shortages. While no one ever accepted a public service job with the intention of getting rich, the disparity between pay in the public and private sectors has never been more stark, or more impactful. With burnout at an all-time high since the pandemic and an aging workforce, city and local governments are having a challenging time hiring workers to replace retirees, let alone build back their employee base to pre-pandemic levels. According to the National League of Cities, between 2020 and 2022 more than 300,000 Americans left local government jobs, affecting “municipalities’ abilities to perform essential functions and deliver services to residents.”
Considering these twin downward pressures, AI seems to hold great promise for local governments to deliver more services to citizens, more effectively, and at a lower cost. This sentiment has certainly been reflected in what a recent Bloomberg Cities Network initiative – City AI Connect – has reported. While only two percent of cities are in the application phase for AI, 71 percent of cities have started their AI journey. Moreover, 81 percent of cities surveyed intend to use generative AI to optimize delivery of services to citizens.
AI Use Cases for Local Governments
Clark County, Nevada, a long-time leader in using technology to improve the lives of its constituents, is one of the pioneers of AI for local government. “We have implemented a self-service password reset solution, that will expand with additional services in the near future,” shared CIO Bob Leek in a conversation with Government Technology Insider. “We’re also working on several other use cases to support both our workers and businesses in Clark County. For our developers, we’ve supported the use of AI-enabled code tools to write better code more quickly for our custom development projects. And we’re currently working on an AI engine for event promoters to fill out and find out which permits they need for the over 450 events that run in Clark County each year.”
Similarly, The City of San Jose, California has begun to integrate AI into its constituent-facing services in an effort to streamline service delivery and improve service quality. “The next frontier is really automation and personalization, using artificial intelligence to better understand who the requester is, where they live, what they need and be even more intuitive and responsive,” shared Mayor Matt Mahan in conversation with Jenn White on 1a. “We can use sensors on city vehicles to actually proactively identify where the potholes are just as they’re forming and automatically create a service request for our Department of Transportation to go fix it. So, I think there’s a really exciting new frontier of automation that artificial intelligence is making possible.”
AI Readiness is More Than Governance and Data
While typically thought of as a state of federal-level role, several local governments, including Gilbert, Arizona and Luzerne County, Pennsylvania, have taken the appointment of a Chief AI Officer as their next actionable step. Other localities are taking a different approach. Tempe, Arizona, for example, has incorporated the role of Chief AI Officer into the role of Chief Data and Analytics Officer and Long Beach, California is appointing a temporary AI fellow to ensure strategy alignment and technology readiness.
For the National League of Cities’ Christopher Jordan, the appointment of an AI lead is “important to ensure the agency is ready to adopt AI … They can oversee the key aspects like data governance, and privacy, and security measures, and policy development,” he shared in a recent conversation with Government Technology. While data governance – and especially data privacy and security – along with upskilling workers and the development of use cases and applications that will positively impact municipal employees and constituent service delivery are all important parts of a city’s AI journey, IT infrastructure readiness is often omitted from these discussions of AI readiness.
“Most of the AI tools we are evaluating today can operate on our existing infrastructure,” explained Clarke County CIO, Bob Leek. “However, we will invest in infrastructure – including our network – when we need to match infrastructure needs to the AI tools, we invest in.” For Leek and other city and county CIOs, this need to invest in the network will come quickly as they move from predictive analytics use cases, such as fraud detection, to generative AI use cases, like those that improve customer experience, agentic AI, and the AI use cases that are yet to be imagined.
A traditional network’s bandwidth will be quickly consumed by the data demands of AI applications resulting in sluggish performance or even network outages as data struggles to get from the data center to the cloud and from the cloud to applications. “To meet the growing demands of AI-driven networks, it’s essential for agencies to upgrade to high-capacity fiber infrastructure,” shared Dave Ward, Chief Technology and Product Officer at Lumen. “Current network protocols and architectures are outdated for AI and multi-cloud environments. Supporting these advanced technologies with more bandwidth and a robust ultra-low latency fiber infrastructure is no longer an option but a necessity. For local governments this means investing in high-speed, low-latency networks must be a priority to build a strong backbone for successful AI implementation so that they can scale, operate securely, and facilitate real-time processing of even the largest and most complex data sets.
Conclusion
America’s cities and counties are leading the way as early adopters of AI in government and are also in many respects, the first experience many people will have with AI. These frontline organizations are in a unique position to build trust both in government and in the transformative power of AI if the implementation is done right. While the inclination is to focus on data governance at the beginning of an AI implementation, local government IT leaders would be well served to give equal priority to network readiness. Focusing on bandwidth, scalability, and latency, government IT leaders can be prepared to harness the power of AI today and long into the future.