You Can't Build AI-Ready Cities without Civic Infrastructure

Cities are rushing to adopt artificial intelligence, digital twins, sensors, and data platforms with the hope that better technology will make government more responsive. But local leaders are running into a basic sequencing problem: how can cities engage residents around complex choices when they do not yet have the data systems, institutional capacity, or shared operating picture needed to explain how services and neighborhoods function in practice? At the same time, how can city leaders build trustworthy digital systems without involving the people who will live with their consequences? 

This is the catch-22 at the heart of building AI-readiness in the public realm. We established the Responsive Cities Network work with the John S. and James L. Knight Foundation to find approaches to address this dilemma – and purposefully design processes that include community organizations so they can help shape how cities adopt this technology. 

Each of the 10 cities in this Network are working to: 

• Build neighborhood-level civic infrastructure that gives local groups like community boards the shared context to advocate for resources and shape city decisions. 
• Make data more usable and accessible for both staff and the public, so decisions and dialogue are grounded in shared information. 
• Learn where AI can help cities listen at scale, synthesize resident concerns, spot service patterns, tailor communication, and close the loop while keeping human judgment, transparency, and accountability at the center. 
• Uncertainty about technology’s impact isn’t new. The speed, complexity, and scale of the AI policy decisions now facing city leaders are. When decisions move this quickly, residents are too often left out of them, and the gap between residents and their government grows. Over the next two years, we will continue working with cities to close that gap. 

On one side is digital infrastructure: the integrated data, interoperable systems, governance rules, security protocols, and accessible information that allow a city to see itself clearly. Without this foundation, public engagement can become frustratingly abstract. Residents are asked what they want without being shown the tradeoffs, constraints, or likely effects of different choices. City officials may gather input they cannot connect to operations or implementation. When government invites participation before it can demonstrate how feedback will inform action, it risks reinforcing the very distrust it hoped to overcome. 

On the other is civic systems: the relationships, trusted intermediaries, community groups, participation pathways, and feedback loops that give residents a meaningful role in shaping public decisions. Without this people-driven groundwork, sophisticated technology can still fail. A city may build a digital twin or launch an open-data portal and find that residents do not use it, do not understand it, or do not believe the institution will act on what they say. Technology can make government more legible, but it cannot by itself create legitimacy, belonging, or civic agency. 

Neither can simply come first. Cities cannot reach effective civic engagement through technology alone, but they also cannot build effective, legitimate digital systems without civic engagement. The answer is not to choose between the two; it is to develop them together as a single form of AI-ready civic infrastructure. 

That combined infrastructure has two mutually reinforcing functions: 

1. Digital systems create shared context. They help officials and residents understand how a problem works, where disparities exist, which constraints are real, and what different scenarios might produce.  
2. Civic systems create shared understanding of problems and accountability to build solutions. Trusted community organizations, frontline staff, deliberative processes, and clear feedback mechanisms help residents interpret that information, contribute lived experience, weigh tradeoffs, and see how their participation shapes a decision.  

The distinction matters because the same technologies that support better engagement can also deepen the distance between government and the public. A data platform is not inherently participatory. A visualization becomes civic infrastructure only when people can use it to ask questions, challenge assumptions, and influence outcomes. AI-generated summaries are valuable only when residents can verify that their views were represented and officials are accountable for what happens next. The technology enables, and the participation provides a level of governance.  

When these reinforce one another, they can create a learning loop. Better data and visualization make public problems easier to understand. Better engagement brings new information, community knowledge, and scrutiny into the system. That input improves the quality of the data, the design of services, and the legitimacy of decisions. As government becomes more responsive and residents see evidence that participation matters, trust and willingness to engage can grow. The result is not merely a more technologically capable city, but a city that can learn with its residents. 

Building that learning loop will require something less glamorous than a new AI tool: bureaucratic reorganization. In most city halls, the people responsible for the technology stack are institutionally separated from the people responsible for neighborhood relationships, service delivery, and public participation. IT leaders may understand data governance, privacy, interoperability, and cybersecurity but have little experience with community organizing or deliberative design. Frontline officials and engagement teams may know how to build relationships and facilitate participation but lack the authority or technical fluency to shape digital procurement and implementation. 

Cities should therefore create cross-functional teams that bring these domains together from the beginning. Decisions about data architecture, AI systems, and digital tools should include the officials and community partners who understand how residents experience government. Engagement processes should be designed with a clear connection to operational data, service delivery, and decision authority. Procurement should test not only whether a tool works technically, but whether residents can understand it, contest it, and use it to exercise a meaningful voice. Tools are co-designed with community groups where data can flow both ways – informing changes in policy and service allocation inside city hall and perception and behavior of community groups and residents. Success should be measured not simply by platform adoption or participation rates, but by whether public input improves decisions, services, and outcomes. 

This reframes the purpose of civic engagement. Engagement is not an end in itself, nor is it a decorative layer added after the technical work is complete. Its purpose is to make public problem-solving more legitimate, collaborative, informed, and effective. Similarly, digital modernization is not simply about automating government or making internal systems more efficient. Its civic purpose is to help government and residents develop a shared understanding of problems and act on that understanding together. 

The central question for city leaders is therefore not whether to invest in technology before civic engagement or civic engagement before technology. It is how to build AI-ready civic infrastructure in which people-driven and technology-driven systems develop in tandem.  

Cities that get this right will be better positioned to use AI not simply to automate government, but to support collaborative, responsive governance: government that can see more clearly, listen more effectively, and act with greater public legitimacy.