5th OECD Roundtable on Smart Cities and Inclusive Growth

Cities worldwide are integrating Artificial Intelligence (AI) into essential services – such as transport, energy, and waste management - to address the complex and evolving challenges of urbanisation. By transforming vast data volumes into actionable insights, AI enhances decision-making, efficiency, and sustainability - helping smart cities to become more resilient and better prepared for current and future challenges. In an era of limited resources, rising demands, and growing uncertainty, AI offers cities the potential optimise operations and improving outcomes despite fiscal and capacity constraints. Compared to traditional AI, Generative AI brings a new dimension to urban planning by not only analysing data but also creating and simulating multiple planning scenarios in real time. This dynamic capability can help accelerate decision-making and enable more integrated, adaptive and forward-looking smart city development, while demanding a vast amount of good quality data.

AI adoption remains uneven across cities. Those with greater resources and advanced infrastructure are piloting cutting-edge AI in areas such as predictive mobility, energy optimisation, and waste management. In contrast, less-resourced cities often rely on simplified versions delivered through cloud-based services. Despite these differences, cities face common barriers including funding limitations, skills shortages, outdated infrastructure, weak data governance, and public scepticism. Concerns around data privacy, algorithmic bias, lack of transparency, and unequal access to digital infrastructure slow down AI deployment. This requires strategic planning, investment in capacity-building, robust ethical and regulatory frameworks, and sustained efforts to build public trust.   

Questions for discussion:

• What is the current state of AI adoption in cities of different contexts, sizes and capabilities? 
• How can local governments align AI initiatives with broader smart city goals and sustainability targets? 
• What strategies have proven most effective for cities seeking to scale AI across different municipal departments and services?

Cities across the globe are harnessing Artificial Intelligence (AI) to drive sustainable urban development across multiple sectors. For example, AI applications are optimising public transport routes, enhancing energy efficiency in buildings, managing traffic flows to reduce congestion and emissions, and supporting predictive maintenance of infrastructure. Smart waste systems use AI to forecast collection needs, while real-time environmental monitoring allows for more responsive action to air and water pollution, as well as climate-related hazards. These innovations can create more resilient, low-carbon and resource-efficient cities, supporting progress towards the Sustainable Development Goals. 

Further opportunities to apply AI for sustainable urban development remain untapped. For example, AI models that integrate real-time urban data with citizens input could help drive localised climate action and improve heat resilience. There is also potential in applying AI for adaptive infrastructure in underserved areas. To fully realise these benefits, AI strategies must embed sustainability at their core but also equity and transparency, beyond technological deployment.

Questions for discussion:

• What opportunities remain untapped in AI solutions designed to enhance sustainability, inclusiveness, and quality of life?
• What are the main challenges that cities face when deploying AI for sustainable urban development? How can cities manage the environmental impact of AI use and ensure AI solutions engage citizens while preventing the aggravation of existing urban inequalities? 
• How could the most promising AI applications for sustainable urban development be scaled across cities with varying capacities and resources?

Successful AI adoption in cities depends on several factors such as local conditions, institutions, and capacities. For successful AI deployment, cities need a shared strategic vision, leadership, and cross-sector collaboration. It is also essential to build AI expertise and capacity in urban planning and public service teams through training, communication, and clear ethical guidelines and accountability frameworks to ensure a more effective and responsible implementation. Moreover, funding from regional and international sources is critical to help bridge financial gaps and provide technical support, including through partnerships with universities and tech firms. Finally, effective governance and risk management frameworks are needed to ensure AI benefits urban development while safeguarding transparency and trust. 

Questions for discussion:

• How can cities build the institutional and human capacity needed to implement and manage AI systems effectively?
• What strategies can help local governments secure the necessary financial and technological resources to support long-term, sustainable AI adoption?
• What regulatory and governance frameworks, including data governance, are most effective in ensuring an ethical and inclusive use of AI in urban settings?

An AI-shaped city could feature intelligent infrastructure, adaptive transport systems, and responsive public services that continuously learn from real-time data to optimise urban life. From traffic lights reducing congestion to predictive maintenance of utilities and personalised health or education services, AI can make city operations more efficient and citizen-focused. However, retaining human agency is essential to ensure these technologies reflect public values and serve the common good. This requires transparent design processes, inclusive civic engagement, and robust governance frameworks that prioritise accountability, privacy, and equity. Human oversight must remain central, with urban planners, communities, and policymakers shaping AI deployment, setting clear boundaries, and ensuring it complements rather than overrides democratic decision-making. 

An AI-shaped city should not only be smart, but also just, participatory, and adaptable — where technology enhances, rather than diminishes, people’s role in shaping their shared urban future. Strategic foresight can enhance the uptake of AI in cities by helping policymakers anticipate emerging trends, risks, and opportunities, enabling informed, future-ready decisions. It encourages long-term thinking, scenario planning, and the exploration of alternative futures. 

Questions for discussion:

• What does an AI-shaped city look like in different geographical contexts, and how can human agency be retained in its development?
• What potential unintended consequences could arise from the integration of AI into urban development including for vulnerable groups?
• What kinds of urban futures might emerge as AI becomes more embedded in city systems?