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The Role of AI in Predictive Modelling for Sustainable Urban Development: Challenges and Opportunities

Author

Listed:
  • Elda Cina

    (College of Engineering and Technology, American University of the Middle East, Egaila 54200, Kuwait)

  • Ersin Elbasi

    (College of Engineering and Technology, American University of the Middle East, Egaila 54200, Kuwait)

  • Gremina Elmazi

    (College of Engineering and Technology, American University of the Middle East, Egaila 54200, Kuwait)

  • Zakwan AlArnaout

    (College of Engineering and Technology, American University of the Middle East, Egaila 54200, Kuwait)

Abstract

As urban populations continue to rise, cities face mounting challenges related to infrastructure strain, resource management, and environmental degradation. Sustainable urban development has emerged as a crucial strategy to balance economic growth, social equity, and environmental preservation. In this context, artificial intelligence offers transformative potential, particularly through predictive modeling, which enables data-driven decision making for more efficient and resilient urban planning. This paper explores the role of AI-powered predictive models in supporting sustainable urban development, focusing on key applications such as infrastructure optimization, energy management, environmental monitoring, and climate adaptation. The study reviews current practices and real-world examples, highlighting the benefits of predictive analytics in anticipating urban needs and mitigating future risks. It also discusses significant challenges, including data limitations, algorithmic bias, ethical concerns, and governance issues. The discussion emphasizes the importance of transparent, inclusive, and accountable AI frameworks to ensure equitable outcomes. In addition, the paper presents comparative insights from global smart city initiatives, illustrating how AI and IoT-based strategies are being applied in diverse urban contexts. By examining both the opportunities and limitations of AI in this domain, the paper offers insights into how cities can responsibly harness AI to advance sustainability goals. The findings underscore the need for interdisciplinary collaboration, ethical safeguards, and policy support to unlock AI’s full potential in shaping sustainable, smart cities.

Suggested Citation

  • Elda Cina & Ersin Elbasi & Gremina Elmazi & Zakwan AlArnaout, 2025. "The Role of AI in Predictive Modelling for Sustainable Urban Development: Challenges and Opportunities," Sustainability, MDPI, vol. 17(11), pages 1-39, June.
    • Handle: RePEc:gam:jsusta:v:17:y:2025:i:11:p:5148-:d:1671322
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    References listed on IDEAS

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    1. Diego Canquil & Daniel San Martín & Irene Inoquio-Renteria & Paul Leger, 2026. "A Systematic Literature Review on Machine Learning Techniques for Predicting Household Water Consumption," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 40(2), pages 1-30, January.
    2. Enrico Ivaldi & Tiziano Pavanini & Tommaso Filì & Enrico Musso, 2025. "National Models of Smart City Development: A Multivariate Perspective on Urban Innovation and Sustainability," Sustainability, MDPI, vol. 17(16), pages 1-16, August.
    3. Kang, Hyuna & Jung, Dahyun & Choi, Jinwoo & Hong, Taehoon, 2026. "Scaling and integrating digital twin applications for battery energy storage systems from building to city," Renewable and Sustainable Energy Reviews, Elsevier, vol. 229(C).

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