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Artificial Intelligence in urban design: A systematic review.

Tianchen Huang¹, Xinyue Ye², Tan Yigitcanlar³

¹Department of Landscape Architecture and Urban Planning & Center for Geospatial Sciences, Applications and Technology, Texas A&M University, College Station, TX 77840, USA.

Cities (London, England)

|July 8, 2026

Summary

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Artificial Intelligence (AI) transforms urban design by improving efficiency and adaptability in the design phase. Challenges like integration and bias require structured workflows and human-AI collaboration for sustainable cities.

Area of Science:

Urban Planning and Design
Computer Science
Architecture

Background:

Artificial Intelligence (AI) is increasingly vital in urban design, enhancing efficiency, scalability, and adaptability.
Conventional urban design workflows are often manual and time-consuming, presenting limitations AI can address.

Purpose of the Study:

To systematically review AI applications in urban design, focusing on the design generation phase.
To identify AI's role in data analysis, scheme generation, optimization, and visualization within urban design.

Main Methods:

Systematic literature review of AI applications in urban design.
Analysis of AI methodologies for data processing, automated iterations, and visualization.

Main Results:

Keywords:

AI-human collaboration Artificial Intelligence Design generation Generative AI Urban Design

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AI significantly enhances efficiency in urban design through rapid data processing and automated iterations.
AI tools offer advanced visualizations, improving the understanding of design schemes.
Challenges include fragmented integration, incomplete automation, and potential algorithmic bias.

Conclusions:

Structured AI workflows and effective human-AI collaboration are crucial for overcoming current limitations.
Developing diverse datasets is essential for equitable and context-sensitive AI-driven urban design.
AI-enhanced urban design can foster more sustainable, efficient, and resilient cities.