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The smart future for sustainable development: Artificial intelligence solutions for sustainable urbanization

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  • Marwan Al‐Raeei

Abstract

Future tools for supporting collaborations between technology and sustainable development include artificial intelligence (AI) applications in sustainable Urbanization roles. This article highlights the various applications of AI in advancing sustainable urbanization. From urban planning to disaster management, AI technology is revolutionizing the way cities are designed and managed. By leveraging data analytics, machine learning, and predictive modeling, AI is helping city officials make informed decisions, optimize resource usage, and improve quality of life for urban residents. Despite the immense potential of AI in sustainable urban development, there are still challenges and limitations to overcome. We show some of the most significant problems related to these issues. These include issues related to data privacy, algorithm bias, and ethical considerations. Continued research and innovation are needed to address these challenges and ensure that AI technology is used responsibly and effectively in shaping sustainable cities. As a result, AI has the power to transform urban environments and create more sustainable, resilient communities. By harnessing the capabilities of AI, cities can become more efficient, environmentally‐friendly, and prepared for the challenges of the future. It is essential for policymakers, urban planners, and technology developers to work together to harness the full potential of AI in sustainable urbanization and create a better future for all. Proactively addressing these challenges can unlock the full potential of AI in combating sustainable cities and building a sustainable future for all.

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  • Marwan Al‐Raeei, 2025. "The smart future for sustainable development: Artificial intelligence solutions for sustainable urbanization," Sustainable Development, John Wiley & Sons, Ltd., vol. 33(1), pages 508-517, February.
    • Handle: RePEc:wly:sustdv:v:33:y:2025:i:1:p:508-517
    DOI: 10.1002/sd.3131
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