The Agentic City maps the answer in public — capturing tangible signals of agentic AI arriving in cities, and clustering them into the trends and forecasts that set the research agenda.
Signals orbit the trends they evidence. Search, filter by domain, and tap any node to read it — orphan signals are still looking for their cluster.
Tangible examples of the future taking shape today — products, services, behaviors or events that hint at what's coming.
Clusters of signals synthesized into a direction of travel, with a time frame, a level of certainty, and an estimated impact.
Trends woven into a strategic outlook — a horizon view of how the city could change, and what to do about it now.
Every signal is a real product, behavior or event spotted by the crowd — tagged, discussed, and waiting to be clustered into a trend.
Corner pharmacies mount street-level air monitors and show a simple daily score in the window, nudging residents with asthma and pairing bad-air days with free inhaler checks.
A water utility threads low-cost acoustic nodes through aging mains; a model flags the hiss of a forming leak weeks ahead of failure, routing crews to fix pipes before the street floods.
A participatory-budgeting platform adds an assistant that turns plain-language wishes into costed, code-compliant project proposals — and flags trade-offs between competing neighborhood asks.
Ahead of summer, a municipality hires year-round workers to run cooling centers, check on isolated residents, and map hot blocks with handheld sensors — treating extreme heat like a standing hazard, not a seasonal surprise.
Architects release a parametric toolkit that tests whether a given office floorplate can become apartments — light wells, plumbing cores, egress — in an afternoon instead of a six-month study.
A pilot meters loading-zone access dynamically — delivery vans bid for curb space in real time, and prices rise with demand. Double parking on the corridor fell by a third in the first month.
Based at Cornell Tech's Urban Tech Hub in New York City, The Agentic City bridges the gap between high-level AI governance vision and on-the-ground municipal implementation. We help cities envision, specify, and build capabilities to address strategic AI opportunities and challenges on the horizon.
Responsible AI means AI that is Secure, Accountable, Fair, and Effective (SAFE). Signals is the initiative's foresight engine: a crowdsourced map of agentic AI arriving in cities, clustered into the trends and forecasts that set our research agenda.
Define the 2–3 year agentic AI agenda for cities by identifying the most important questions for strategic planning — translating global and national AI governance to the city level.
Leverage university expertise to define and support prototyping and pilots by participating cities — turning promising ideas into working demonstrations.
Define the frameworks, standards, and accountability mechanisms needed for responsible deployment of urban AI over the 2–3 year horizon.
Identify pathways from early experiments toward robust, extensible frameworks — turning isolated successes into scalable municipal capability.
See the future taking shape on a page you're reading? Catch it in one click. Drag this button to your bookmarks bar — then hit it on any site to open a pre-filled signal, with the page's URL, title and your highlighted text already in.
Contribute signals, get invited to curate trends, or just get the Hub's latest forecasts in your inbox.