From Smart Cities to Smart Governance: Professor Philip Allmendinger on How AI Is Changing Urban Policy

On July 16, ASI Global successfully hosted the July session of the LUMINAI Lecture Series, featuring Professor Philip Allmendinger, a distinguished scholar in land economy and urban planning from the University of Cambridge. Professor Allmendinger has also served as Deputy Vice-Chancellor of the University of Bath and as Dean of the School of Humanities and Social Sciences at Cambridge. His research spans urban planning theory and practice, regional development, and policy frameworks that shape how cities evolve.

This online lecture, titled “Smart Cities, Smarter Policies: How AI Is Reshaping Urban Life”, marked Professor Allmendinger’s third appearance with ASI Global. In his earlier sessions, he discussed sustainable urban development and introduced students to the intellectual foundations and professional pathways of Land Economy. Returning now for a new conversation, he shifted focus to how artificial intelligence and digital technologies are transforming urban life, and how cities can respond through smarter, more inclusive policies.

Lecture Topic: Smart Cities, Smarter Policies: How AI Is Reshaping Urban Life

Drawing on insights from his recent book The Forgotten City, Professor Allmendinger traced the evolution of the smart-city concept, noting that it has become a dominant ideal in global urban planning but also one surrounded by hype and uneven implementation. A “smart city”, he explained, uses digital and AI-based technologies, real-time data, and digital networks to optimize systems such as traffic, energy, and public safety. He further distinguished between two dimensions of the smart city: the public systems managed through sensors and analytics, and the private layer created by everyday citizens through their digital interactions.

Definition of Smart City

Building on this conceptual framework, Professor Allmendinger turned to real-world examples to illustrate both the promise and the pitfalls of AI-driven urbanism. Cases such as Singapore’s AI-based congestion pricing and Barcelona’s open-data initiatives demonstrate how technology can improve efficiency, transparency, and sustainability. However, he also noted that the same innovations can produce unintended consequences, from data privacy risks to widening social inequality. Cities like San Francisco and Toronto’s Sidewalk Labs Project reveal the paradox of progress, where digital transformation has fueled housing crises, gentrification, and public resistance.

Global Case Examples of Smart Cities

A central part of the lecture examined the structural challenges of AI-enabled urbanism. Platforms such as Airbnb and Uber, while convenient, have disrupted housing markets and local labor systems. Predictive-policing models risk reinforcing bias and stigmatizing communities. Automation and the “gig economy” are altering employment patterns, with lower- and mid-skill urban jobs most at risk. These patterns, Professor Allmendinger argued, are intensifying divides not only within cities but also between cities, creating a hierarchy of “superstar” and lagging urban centers.

Structural Challenges of AI-Enabled Urbanism

Looking ahead, he discussed how emerging tools, such as digital twins, autonomous mobility, and smart buildings, are likely to redefine city design and planning. Real-time simulation now allows planners to test environmental and infrastructural scenarios instantly, while self-driving systems and drones could reshape urban land use. Yet these advances come with energy and governance implications: smart cities consume vast resources and often centralize control in large corporations.

Future Trends of Smart City Development

To counter these trends, Professor Allmendinger urged a shift toward inclusive, sustainable, and transparent urban governance. Cities must ensure that technological development serves public interests, prioritizing equity, climate action, and citizen participation. He emphasized that digital innovation should follow urban policy and that local governments must retain control over data ownership and accountability.

How AI Could Build Better Cities

In the Q&A session, audience questions centered on data bias, citizen participation, and employment trends. Professor Allmendinger highlighted participatory digital-planning tools that allow residents to engage directly in city design and stressed that planners must reach both digital and non-digital communities to ensure representation. He noted that while automation may eliminate certain jobs, it will also create new ones. He underscored the importance of education and policy in managing this transition.

Concluding the lecture, Professor Allmendinger reminded participants that the future of cities is still open to choice. AI will continue to reshape urban life, but its direction depends on how societies balance innovation with fairness, sustainability, and policies.