Journals / Kent Akademisi / 2026 / Cilt: 19 Sayı: 2

Artificial Intelligence, Architecture, and Urban Sustainability: A Systematic Review with a Speculative Design Approach

Yapay Zeka, Mimarlık ve Kentsel Sürdürülebilirlik: Spekülatif Tasarım Yaklaşımıyla Sistematik Bir İnceleme

Fazıl Akdağ(ERCİYES ÜNİVERSİTESİ, MİMARLIK FAKÜLTESİ, MİMARLIK BÖLÜMÜ, BİNA BİLGİSİ ANABİLİM DALI)0000-0002-3316-8104
Fatma Betül Künyeli(ERCİYES ÜNİVERSİTESİ, FEN BİLİMLERİ ENSTİTÜSÜ)0000-0002-6189-5966
Pages
1–21
Publication Date
2026-03-03
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AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

The findings contribute to both academia and practice by highlighting how AI-driven approaches can enhance sustainable city planning and by identifying areas where further innovation is needed, thereby informing future design strategies.

📌 3 Key Takeaways

🎯
Objective & Hypothesis:This study presents a systematic literature review that examines the integration of artificial intelligence (AI) technologies into the disciplines of architecture and urban planning, within the context of sustainable cities.
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Key Findings & Data:In this review conducted in accordance with the PRISMA protocol, 11 academic publications were evaluated through keywords identified in the Web of Science and Scopus databases.
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Conclusion & Impact:The findings contribute to both academia and practice by highlighting how AI-driven approaches can enhance sustainable city planning and by identifying areas where further innovation is needed, thereby informing future design strategies.
🔬Design:Review & Systematic Survey
📍Scope:Comprehensive Sample
⚙️Variables:Mimarlıkta Yapay Zeka · Sürdürülebilir Kentsel Planlama · Akıllı Şehirler ve Etik

Abstract

This study presents a systematic literature review that examines the integration of artificial intelligence (AI) technologies into the disciplines of architecture and urban planning, within the context of sustainable cities. In this review conducted in accordance with the PRISMA protocol, 11 academic publications were evaluated through keywords identified in the Web of Science and Scopus databases. The literature has been examined under five thematic headings: AI applications in urban planning processes, Decision support systems and scenario development, Social participation and governance, Conceptual- speculative approaches, and the Sustainability perspective. Methodologically, the study has focused on both technical applications and social and ethical dimensions with an interdisciplinary approach. The literature shows that AI is effective in areas such as data-intensive decision-making, multi-scenario analysis, and performance optimization in planning and design processes. However, significant gaps still exist in the areas of social engagement, ethical responsibility, and stakeholder diversity. The speculative design approach, on the other hand, has the potential to go beyond current practices by combining possible future scenarios shaped by AI with architectural and urban visions. In this context, the study poses the following fundamental research questions: (1) How are AI technologies integrated into the fields of architecture and urban planning? (2) What themes are prominent at the intersection of AI and speculative design? (3) How are AI applications evaluated in terms of social participation and ethical governance with respect to sustainable city goals? These questions provide an essential framework for forward-looking creative and critical urban design approaches. This review addresses a notable gap in the literature by examining the role of AI in sustainable urban design, providing insights into underexplored areas such as participatory governance and ethical AI practices. The findings contribute to both academia and practice by highlighting how AI-driven approaches can enhance sustainable city planning and by identifying areas where further innovation is needed, thereby informing future design strategies.

Özet

ÖZ Bu çalışma, yapay zekâ (YZ) teknolojilerinin sürdürülebilir şehirler bağlamında mimarlık ve şehir planlama disiplinlerine entegrasyonunu inceleyen sistematik bir literatür taraması sunmaktadır. PRISMA protokolüne uygun olarak yürütülen bu taramada, Web of Science ve Scopus veritabanlarında belirlenen anahtar kelimeler aracılığıyla 11 akademik yayın değerlendirilmiştir. Literatür beş tematik başlık altında incelenmiştir: Kentsel planlama süreçlerinde YZ uygulamaları, Karar destek sistemleri ve senaryo geliştirme, Sosyal katılım ve yönetişim, Kavramsal-spekülatif yaklaşımlar ve Sürdürülebilirlik perspektifi. Yöntemsel olarak çalışma, disiplinlerarası yaklaşımla hem teknik uygulamalara hem de sosyal ve etik boyutlara odaklanmıştır. Literatür, YZ’nin planlama ve tasarım süreçlerinde veri yoğun karar alma, çoklu senaryo analizi ve performans optimizasyonu gibi alanlarda etkili olduğunu göstermektedir. Bununla birlikte, sosyal katılım, etik sorumluluk ve paydaş çeşitliliği konularında hâlen önemli boşluklar bulunduğu görülmektedir. Spekülatif tasarım yaklaşımı ise, mevcut uygulamaların ötesine geçerek YZ ile şekillenen olası gelecek senaryolarını mimari ve kentsel vizyonlarla birleştirme potansiyeli taşımaktadır. Bu bağlamda çalışma, şu temel araştırma sorularını yöneltmektedir: (1) YZ teknolojileri mimarlık ve şehir planlama alanlarında hangi yöntemlerle entegre edilmektedir? (2) YZ ve spekülatif tasarım kesişiminde hangi temalar ön plana çıkmaktadır? (3) YZ uygulamaları sürdürülebilir şehir hedefleri açısından sosyal katılım ve etik yönetişim ekseninde nasıl değerlendirilmektedir? Bu sorular, geleceğe dönük yaratıcı ve eleştirel şehir tasarımı yaklaşımları için önemli bir çerçeve sunmaktadır. Bu inceleme, sürdürülebilir kentsel tasarımda yapay zekânın rolünü inceleyerek literatürdeki önemli bir boşluğu ele almakta, katılımcı yönetişim ve etik yapay zekâ uygulamaları gibi az araştırılmış alanlara dair içgörüler sunmaktadır. Bulgular, yapay zekâ destekli yaklaşımların sürdürülebilir şehir planlamasını nasıl geliştirebileceğini vurgulayarak hem akademiye hem de uygulamaya katkıda bulunmakta ve daha fazla yeniliğe ihtiyaç duyulan alanları belirleyerek gelecekteki tasarım stratejilerine öneriler sunmaktadır.

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Cite This Article

Akdağ, F., Künyeli, F. B. (2026). Artificial Intelligence, Architecture, and Urban Sustainability: A Systematic Review with a Speculative Design Approach. Kent Akademisi, Cilt: 19 Sayı: 2, 1–21. https://doi.org/10.35674/kent.1681393

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References (34)

  1. Alsabt, R., Alkhaldi, W., Adenle, Y. A., & Alshuwaikhat, H. M. (2024). Optimizing waste management strategies through artificial intelligence and machine learning - An economic and environmental impact study. Cleaner Waste Systems, 8, 100158. https://doi.org/10.1016/j.clwas.2024.100158
  2. Berigüete, F. E., Santos, J. S., & Rodríguez Cantalapiedra, I. (2024). Digital Revolution: Emerging Technologies for Enhancing Citizen Engagement in Urban and Environmental Management. Land, 13(11), 1921. https://doi.org/10.3390/land13111921
  3. Chaillou, S. (2019). Space Layouts & GANs: GAN-enabled Floor Plan Generation. Space¬maker Research Blog. Medium. Retrieved April 20, 2025, from https://medium.com/spacemaker-research-blog/space-layouts-gans-2329c8f85fe8
  4. Cheng, W., Chu, Y., Xia, C., Zhang, B., Chen, J., Jia, M., & Wang, W. (2023). UrbanGenoGAN: Pioneering urban spatial planning using the synergistic integration of GAN, GA, and GIS. Frontiers in Environmental Science, 11, 1287858. https://doi.org/10.3389/fenvs.2023.1287858
  5. Das, D. K. (2025). Digital Technology and AI for Smart Sustainable Cities in the Global South: A Critical Review of Literature and Case Studies. Urban Science, 9(3), 72. https://doi.org/10.3390/urbansci9030072
  6. Degbelo, A., Granell, C., Trilles, S., Bhattacharya, D., Casteleyn, S., & Kray, C. (2016). Opening up Smart Cities: Citizen-Centric Challenges and Opportunities from GIScience. ISPRS International Journal of Geo-Information, 5(2), 16. https://doi.org/10.3390/ijgi5020016.
  7. Designing Buildings Wiki. (2019). File: Archigram [Image]. Retrieved April 20, 2025, from https://www.designingbuildings.co.uk/wiki/File:Archigram.jpg
  8. Dunne, A., & Raby, F. (2013). Speculative Everything: Design, Fiction, and Social Dreaming. The MIT Press.
  9. Edwards, F., & Pettersen, I. N. (2023). Speculative design for envisioning more-than-human futures in desirable counter-cities. Cities, 142, 104553. https://doi.org/10.1016/j.cities.2023.104553
  10. Ferreira, J. C., Francisco, B., Elvas, L., Nunes, M., & Afonso, J. A. (2023). Predicting People’s Concentration and Movements in a Smart City. Electronics, 13(1), 96. https://doi.org/10.3390/electronics13010096
  11. Ghahramani, M., Zhou, M., Molter, A., & Pilla, F. (2021). IoT-based Route Recommendation for an Intelligent Waste Management System. ArXiv. https://doi.org/10.1109/JIOT.2021.3132126
  12. Gilman, E., Bugiotti, F., Khalid, A., Mehmood, H., Kostakos, P., Tuovinen, L., Ylipulli, J., Su, X., & Ferreira, D. (2024). Addressing Data Challenges to Drive the Transformation of Smart Cities. ACM Transactions on Intelligent Systems and Technology, 15(5), 1-65. https://doi.org/10.1145/3663482
  13. Gupta, S., & Degbelo, A. (2022). An Empirical Analysis of AI Contributions to Sustainable Cities (SDG11). In F. Mazzi & L. Floridi (Eds.), The Ethics of Artificial Intelligence for the Sustainable Development Goals (pp. 461-484). Springer. https://doi.org/10.1007/978-3-031-21147-8_25
  14. Haraguchi, M., Funahashi, T., & Biljecki, F. (2024). Assessing governance implications of city digital twin technology: A maturity model approach. Technological Forecasting and Social Change, 204, 123409. https://doi.org/10.1016/j.techfore.2024.123409
  15. Jang, S., & Lee, G. (2023). Interactive Design by Integrating a Large Pre Trained Language Model and Building Information Modeling. arXiv. https://doi.org/10.48550/arXiv.2306.14165
  16. Lombardi P, Ferretti V (2015). "New spatial decision support systems for sustainable urban and regional development". Smart and Sustainable Built Environment, Vol. 4 No. 1 pp. 45–66, doi: https://doi.org/10.1108/SASBE-07-2014-0039
  17. Li, Y., Chen, H., Yu, P., & Yang, L. (2024). A Review of Artificial Intelligence in Enhancing Architectural Design Efficiency. Applied Sciences, 15(3), 1476. https://doi.org/10.3390/app15031476
  18. Liang, C. J., Le, T. H., Ham, Y., Mantha, B. R. K., Cheng, M. H., & Lin, J. J. (2023). Ethics of artificial intelligence and robotics in the architecture, engineering, and construction industry. arXiv. https://doi.org/10.48550/arXiv.2310.05414
  19. Lukens, J., & DiSalvo, C. (2011). Speculative Design and Technological Fluency. International Journal of Learning and Media, 3, 23-40. https://doi.org/10.1162/IJLM_a_00080
  20. Marasinghe, R., Yigitcanlar, T., Mayere, S., Washington, T., & Limb, M. (2023). Computer vision applications for urban planning: A systematic review of opportunities and constraints. Sustainable Cities and Society, 100, 105047. https://doi.org/10.1016/j.scs.2023.105047
  21. Nyaaba, A. A., & Ayamga, M. (2021). Intricacies of medical drones in healthcare delivery: Implications for Africa. Technology in Society, 66, 101624. https://doi.org/10.1016/j.techsoc.2021.101624
  22. Othengrafen, F., Sievers, L., & Reinecke, E. (2025). From Vision to Reality: The Use of Artificial Intelligence in Different Urban Planning Phases. Urban Planning, 10, Article 8576. https://doi.org/10.17645/up.8576
  23. Østvold, M. Ø., Paulsen, M. P., & Trondsen, J. K. (2024). Speculative design through the lens of AI. In Proceedings of the 26th International Conference on Engineering and Product Design Education (EPDE 2024). Aston University, Birmingham, United Kingdom.
  24. Quan, S. J., Park, J., Economou, A., & Lee, S. (2019). Artificial intelligence-aided design: Smart Design for sustainable city development. Environment and Planning B: Urban Analytics and City Science. https://doi.org/10.1177/2399808319867946
  25. Qian, K., Mao, L., Liang, X., Ding, Y., Gao, J., Wei, X., Guo, Z., & Li, J. (2023). AI Agent as Urban Planner: Steering Stakeholder Dynamics in Urban Planning via Consensus-based Multi-Agent Reinforcement Learning. arXiv. https://arxiv.org/abs/2310.16772
  26. Sepehri, B., Almulhim, A., Adibhesami, M. A., Makaremi, S., & Ejazi, F. (2024). Artificial Intelligence Role in Promoting Saudi Arabia’s Smart Cities: Addressing SDGs for Socio-Cultural Challenges. Sotsiologicheskoe Obozrenie / Russian Sociological Review, 24(4), 20–47. https://doi.org/10.17323/1728-192x-2024-4-20-47
  27. Sherman, S. The Polyopticon: a diagram for urban artificial intelligences. AI & Soc 38, 1209–1222 (2023). https://doi.org/10.1007/s00146-022-01501-3
  28. Son, T. H., Weedon, Z., Yigitcanlar, T., Sanchez, T., Corchado, J. M., & Mehmood, R. (2023). Algorithmic urban planning for smart and sustainable development: Systematic review of the literature. Sustainable Cities and Society, 94, 104562. https://doi.org/10.1016/j.scs.2023.104562
  29. SPACE10. (n.d.). Regenerative Futures. Retrieved April 20, 2025, from https://space10.com/projects/regenerative-futures
  30. United Nations. (2015). Transforming our world: The 2030 Agenda for Sustainable Development. United Nations. https://sdgs.un.org/2030agenda
  31. United Nations. (2018). Department of Economic and Social Affairs, Population Division. World Urbanization Prospects: The 2018 Revision. https://population.un.org/wup/
  32. United Nations. (2022). World Cities Report 2022: Envisaging the Future of Cities. UN-Habitat. https://unhabitat.org/wcr/
  33. Wang, D., Lu, C.-T., & Fu, Y. (2023). Towards Automated Urban Planning: When Generative and ChatGPT-like AI Meets Urban Planning. arXiv. https://arxiv.org/abs/2304.03892
  34. Willems, J., Van Den Bergh, J., & Viaene, S. (2016). Smart City Projects and Citizen Participation: the Case of London. In Springer eBooks (pp. 249-266). https://doi.org/10.1007/978-3-658-16112-5_12