Cities, the pulsating hubs of human civilization, face poly-crises: growing population pressures, emissions, waste, traffic and noise, aging obsolete infrastructure, chronic housing affordability, employment and the ever-present need for climate resiliency (more than 40% of the world’s urban population lives on the coasts) .
Most of the urban policies, tools, planning and engineering ideas of the mid-20th century that scaled globally have failed and sent virtually every city on an unsustainable and vulnerable path. More than half the world’s population now live in cities, and that number jumps to 80% in the next 25 years necessitating billions of tons of new material and expanded urban footprints. The needed changes to avert accelerating the crisis is immense and urgent. Cities are not buildings, streets or energy systems, cities are about people, culture, behavior, power and politics- the very word comes from Ancient Greek πολιτικά (politiká) ‘affairs of the cities. We can’t keep using the same tools expecting different results- something has to to give.
In comes generative urban AI, an emerging and transformative technology poised to radically change urban planning, design, and city management. Imagine generating optimized city layouts, built form, energy, water, transport, waste and community systems. Imagine integrated systems offering personalized public services in one stop shop fashion – the possibilities are truly mind-boggling because they are data driven and they’re being developed in adjacent industries as we speak.
From AI dreams to real-time urban design and decision making
Just like the latest text to video tools like Open AI’s Sora, you can now describe and generate your ideal urban environment – walkable streets, green spaces, and a vibrant mix of shops and homes. New urban generative AI platforms can move from vision into reality in seconds with dozens, if not hundreds, of iterations and scenarios to review and choose from. Specifically generative AI allows a major shift in how cities plan, decide and design:
- From reactive to proactive: Shift from fixing problems to predicting and preventing them.
- Data-driven insights: Uncover hidden patterns and trends for smarter decision-making,
- Personalized experiences: Tailor offerings to individual city stakeholder needs and preferences simultaneously.
- Augmenting city staff expertise: AI empowers staff capabilities for more rapid piloting, knowledge transfer and accuracy.
Proactive Data-Driven Decisions
Cities are treasure troves of data, reflecting development and travel patterns, energy consumption, and citizen needs. However, they are usually siloed, not connected and in different formats. The saying “without data there is no AI” holds very true for cities. Generative AI can only optimize and analyze data that is in a usable format. In my work, I’ve personally seen what AI is capable of and the ability to optimize the urban fabric, the movement of people and goods, predict congestion hotspots, and suggest infrastructure improvements is just the beginning. Several companies are offering urban AI-powered solutions for predicting the probability of weather related impacts on city infrastructure, severity of vehicle collisions, infrastructure maintenance optimization, and localized urban planning simulations. This data-driven approach allows for proactive planning, permitting and mitigating issues before they arise by creating more responsive, transparent and inclusive urban governance.
Empowering Citizens Democratizing City Processes
Traditionally, urban planning has been a top-down affair. Generative AI is changing that, democratizing the often labyrinthian bureaucracy by opening doors for citizen engagement, transparency and participation from the ground up. From deciphering complex zoning and building codes, to finding often contradictory engineering rules and planning regulations, residents can leverage AI-powered tools including conversational chatbots to answer their questions on their schedules, while city staff gather feedback on proposed plans, increasing transparency and inclusivity. Several companies are utilizing immersive VR and AI to visualize future virtual urban environments allowing citizens to understand and contribute to the planning process in a meaningful way.
Global Cities Leading the Urban AI Transition
Most cities are at the beginning of their generative AI journey and in my work I;ve ben speaking with several sharing the best practices from adjacent and relevant industries. Several cities are starting to test and pilot AI concepts. They have been utilizing various forms of AI from computer vision to machine learning and some have started applications using generative AI. Here are just a few city AI examples by region:
- Americas: Los Angeles, Seattle and Boston trialing AI in public transport, public spaces and traffic management, Pittsburgh prioritizing green development, Toronto and Curitiba managing traffic flow with AI systems, Buenos Aires streamlines waste collection with AI prediction, and Santiago pilots AI for noise control and urban simulations.
- Europe And Middle East: Copenhagen and Amsterdam leverages AI to optimize building and district energy use, Helsinki spearheads the future of mobility with AI-powered solutions, Oslo embraces AI to predict and optimize waste collection routes, and Barcelona, Dubai and Tel-Aviv are utilizing AI for their transport and sustainable energy management.
- Africa: Cape Town tackles traffic and crime with AI-powered management and surveillance, Lagos pilots AI tools for smarter land use and infrastructure development and in Kigali, AI-powered drones deliver and drive smart city and medical initiatives, aiming to streamline efficiency and leapfrog 20th century legacy infrastructure.
- Asia Pacific: Singapore has a comprehensive AI policy for all their services, training and investments, Tokyo tackles traffic, disasters, and personalized public transport with AI, while Beijing utilizes it for air quality, building energy optimization, and smart city infrastructure. Seoul, Melbourne, Sydney and Brisbane utilizing AI for traffic management, public safety, demand prediction and route optimization.
Challenges and Considerations
In my work I’m witnessing a wave of generative AI adoption in every industry and vertical that I’m currently working with and urban planning is no exception. I’ve been conducting workshops and initiating conversations on this topic with business, city leaders and AI startups to help them understand the enormous opportunities and to be aware of the potential pitfalls and lessons learned from other sectors. While the potential of generative AI is immense, challenges remain. Data bias can lead to discriminatory outputs, highlighting the need for responsible development and ethical considerations. Human oversight and transparency in model development are crucial. Additionally, the social and economic implications of urban AI adoption need careful consideration as it can exacerbate inequities if left unchecked.
Generative urban AI is here, are urban planners ready?
The tide is turning, and generative urban AI is surging. While its potential to optimize urban form, streets, energy, emissions, waste, communications and public services is undeniable, are urban planners, engineers and administrators prepared to navigate this revolutionary wave? From my recent experience and conversations in this space the skillsets are in need of an upgrade: from story telling, data governance, urban analysis, coding fluency, and an ethical framework for AI. Universities are just beginning to teach the next generation of city planners and communities need engagement and training with these tools to build trust.
It has to be better than what they have today which is a fragmented mosaic of siloed data sets, policy, bureaucracy and departments at various local, state and federal levels that at times work at cross purposes. And then there is the politics. But it is not insurmountable. In my experience planners and engineers are brilliant problem solvers, just get the politics out of the way (or at least hold it back) and watch them deliver amazing projects, polices and programs. I’ve seen that first hand and when it happens it’s incredible.
Preparing for generative urban AI demands a three-pronged approach: upskilling the workforce with AI company partnerships, genuine community engagement, and establishing ethical AI and data governance frameworks. So what it is the starting point? Build awareness among the staff. Focus on the problem to solve. Explore key city problems that relevant AI enabled projects could help with, engage with the private sector for their partnership and proceed with care. Develop robust AI policy frameworks making it clear what staff can and cannot use AI for, how communities will have their privacy protected, link to you cyber security framework, and how you will tackle ethics, bias and fairness.
By embracing these challenges and navigating them responsibly, planners can unlock AI’s potential to build inclusive, resilient, and truly smart cities for the future. Let’s co-create a future where responsible generative AI shapes a better urban landscape for all. Billions of people are counting on us to get it right. We owe them that.