Smart Cities in the Agentic AI Era: Three Vectors of Urban Transformation
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Fecha de publicación
2026-04ISSN
2076-3417
Resumen
Agentic artificial intelligence—systems that reason, plan, and act autonomously within governed workflows—is converging with autonomous electric mobility and urban robotics to reshape how cities govern, move, and manage physical space. We argue that the simultaneous arrival of these three vectors is triggering a transformation comparable in scope to the Industrial Revolution. Cities that deploy across all three domains are becoming the new hubs of innovation: they concentrate talent, accelerate knowledge circulation, enable cross-fertilisation, and generate hybrid proposals that no single vector could produce alone. Just as Manchester, Birmingham, and the Ruhr became the defining centres of industrialisation because steam, textiles, iron, and coal recombined through the proximity of the engineers and entrepreneurs who moved between them, a small number of cities today are pulling ahead because they host the shared talent pool around which agentic governance, autonomous mobility, and urban robotics co-evolve. Conceptually, we extend the mirroring hypothesis in two directions: dynamically, arguing that organisations and urban ecosystems converge toward the configurations new technologies make possible; and ontologically, arguing that agentic AI introduces non-human agents into organisational architectures, requiring hybrid human–AI coordination. We formalise this dynamic as five propositions (P1–P5) of cumulative recursive hybridisation (CRH), operating through four reinforcing feedback loops—data, regulation, infrastructure, and talent. Together, these loops explain why the emerging urban order is path-dependent: early movers accumulate compounding advantages, while latecomers face exponentially rising costs of entry. We demarcate CRH from adjacent frameworks—general-purpose technologies, organisational complementarities, and complex adaptive systems—and test it against counterfactual evidence from failed, stalled, and Global South trajectories (Sidewalk Toronto, the Cruise rollback, Songdo, Bengaluru). We also examine its political-economy, equity, and surveillance limits. Drawing on comparative evidence from public-sector chatbot deployments, autonomous mobility ecosystems in the United States and China, and emerging urban robotics cases, we conclude that what is at stake is not incremental modernisation but the construction of a new urban order. The cities that act as innovation hubs for the agentic AI era will shape global standards, attract global talent, and define the institutional templates that others eventually adopt—much as the industrial cities of the eighteenth and nineteenth centuries did.
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36 p.
Publicado por
MDPI
Publicado en
Applied Sciences, Vol. 16(8), 3847. Special Issue: The Application of Generative AI and Machine Learning in the Public Sector and Smart Cities
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