Generative Urban AI is here. Are the cities ready?

Cities, the pulsating hubs of human civilization, face multiple crises: increasing population pressures, emissions, waste, traffic and noise, aging and obsolete infrastructure, chronically affordable housing, employment and the ever-present need for climate resilience (over 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 spread globally failed and led almost every city down an unsustainable and vulnerable path. More than half of the world’s population now lives in cities, and that number is set to jump to 80% in the next 25 years, requiring billions of tons of new materials and expanded urban footprints. The changes needed to prevent the crisis from accelerating are huge and urgent. Cities are not buildings, roads or energy systems, cities are about people, culture, behaviour, power and politics – the word itself comes from the ancient Greek politika (politika) ‘city affairs’. We can’t keep using the same tools expecting different results – something has to give.

Here comes genetic urban AI, an emerging and transformative technology poised to fundamentally change urban design, planning and city management. Imagine creating optimized city layouts, built form, energy, water, transportation, waste and community systems. Imagine integrated systems that deliver personalized public services in a unified way – the possibilities are truly mind-blowing because they are data-driven and are developing in adjacent industries as we speak.

From AI dreams to urban planning and real-time decision making

Just like the latest text to video tools like Open AI’s Sora, you can now describe and create your ideal urban environment – walkable streets, green spaces and a vibrant mix of shops and houses. New urban AI platforms can move from vision to reality in seconds with dozens, if not hundreds, of iterations and scenarios to test and select. In particular, genetic AI enables a significant change in the way cities plan, decide and design:

• From reactive to proactive: Moving from fixing problems to predicting and preventing them.
• Data-driven insights: Discover hidden patterns and trends for smarter decision making,
• Personalized experiences: Tailor offers to the individual needs and preferences of city stakeholders at the same time.
• Increasing city staff expertise: AI enhances staff capabilities for faster piloting, knowledge transfer and accuracy.

Proactive data-driven decisions

Cities are treasure troves of data, reflecting growth and travel patterns, energy consumption and citizen needs. However, they are usually siloed, not connected and in different formats. The saying “no data no AI” is very true for cities. Generative AI can only optimize and analyze data that is in a usable form. In my work, I have seen firsthand what AI can do, and the ability to optimize the urban fabric, the movement of people and goods, predict bottlenecks and suggest infrastructure improvements is just the beginning. Several companies offer AI-powered urban solutions for predicting the likelihood of weather-related impacts on city infrastructure, severity of vehicle collisions, optimizing infrastructure maintenance, and local urban planning simulations. This data-driven approach enables proactive planning, permitting and mitigation of issues before they arise, creating a more responsive, transparent and inclusive urban governance.

Empowering citizens who democratize city processes

Traditionally, urban planning has been a top-down affair. Genetic AI is changing this, democratizing the often labyrinthine bureaucracy by opening doors to 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 tap into AI-powered tools, including chatbots to answer their questions about their schedules, while city staff collect feedback on proposed plans, increasing transparency and inclusion. Several companies are using immersive virtual reality and artificial intelligence to visualize future virtual urban environments that allow citizens to understand and contribute to the design process in a meaningful way.

Global cities leading the transition to urban artificial intelligence

Most cities are at the beginning of their AI journey, and in my work I have spoken with several who share best practices from adjacent and related industries. Several cities are starting to test and pilot AI ideas. They have used various forms of artificial intelligence from computer vision to machine learning and some have launched applications using genetic artificial intelligence. Here are just a few examples of city AI by region:

• America: Los Angeles, Seattle and Boston are testing AI in public transportation, public spaces and traffic management, Pittsburgh is prioritizing green growth, Toronto and Curitiba are managing traffic flow with AI systems, the Buenos Aires modernizes garbage collection with predictive AI and Santiago pilots AI for noise control and urban simulations.
• Europe and the Middle East: Copenhagen and Amsterdam harness AI to optimize energy use in buildings and areas, Helsinki leads the future of mobility with AI-based solutions, Oslo embraces AI to predict and optimize routes waste collection and Barcelona, ​​Dubai and Tel-Aviv are using artificial intelligence for their transport and sustainable energy management.
• Africa: Cape Town tackles traffic and crime with AI management and surveillance, Lagos pilots AI tools for smarter land use and infrastructure development, and in Kigali, AI-powered drones deliver and drive smart cities and medical initiatives, aimed at streamlining efficiency and leapfrogging 20th century legacy infrastructures.
• Asia Pacific: Singapore has a comprehensive AI policy for all its services, education and investment, Tokyo tackles traffic, disasters and personalized public transport with AI, while Beijing uses it for air quality, optimization of building energy and smart city infrastructure. Seoul, Melbourne, Sydney and Brisbane use AI for traffic management, public safety, demand forecasting and route optimization.

Challenges and concerns

In my work, I’m watching a wave of AI adoption in every industry and industry I’m currently working with, and urban planning is no exception. I run workshops and initiate discussions on this topic with businesses, city leaders and AI startups to help them understand the huge opportunities and know the potential pitfalls and lessons learned from other sectors. While the potential of genetic AI is enormous, challenges remain. Data bias can lead to discriminatory results, underscoring the need for responsible development and ethical considerations. Human oversight and transparency in model development is crucial. Additionally, the social and economic implications of urban AI adoption need careful consideration, as it may exacerbate inequalities if left unchecked.

Genetic urban AI is here, are urban planners ready?

The tide is turning and genetic urban AI is on the rise. While its potential to optimize urban form, roads, energy, emissions, waste, communications and public services is undeniable, are urban planners, engineers and managers ready to navigate this revolutionary wave? From my recent experience and discussions in this space, skills need upgrading: from storytelling, data governance, urban analytics, coding fluency and an ethical framework for AI. Universities are just beginning to teach the next generation of urban 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 patchwork of fragmented data sets, policy, bureaucracy, and departments at various local, state, and federal levels that at times operate at cross purposes. And then there’s politics. But it is not insurmountable. In my experience, designers and engineers are great problem solvers, just put the politics out of the way (or at least keep it down) and watch them deliver amazing projects, policies and programs. I’ve seen it firsthand and when it happens it’s incredible.

Preparing for productive urban AI requires a three-pronged approach: upscaling the workforce with corporate AI partnerships, genuine community engagement, and establishing ethical AI and data governance frameworks. So what is the starting point? Create awareness among staff. Focus on the problem to be solved. Explore key city problems that relevant AI-enabled projects could help with, work with the private sector for their cooperation, and proceed with caution. Develop strong AI policy frameworks, making it clear what staff can and cannot use AI for, how communities will protect their privacy, linked to the cyber security framework and how you will address ethics, prejudice and justice.

By embracing these challenges and navigating them responsibly, designers can unlock the potential of AI to build inclusive, resilient and truly smart cities for the future. Let’s co-create a future where responsible genetic AI shapes a better urban landscape for all. Billions of people rely on us to get it right. We owe it to them.