Integrating Artificial Intelligence and Augmented Reality for Organisational Strategy, Change, and Innovation in Urban Governance
Keywords:
Artificial intelligence, augmented reality, digital transformation, organisational innovation, urban governanceAbstract
Purpose: This research examines how combining Artificial Intelligence and Augmented Reality (AI-AR) changes urban governance. By means of case studies in urban planning and emergency management, it links these changes to UN SDG 11 and measures administrative efficiency and decision-making effects.
Design/methodology/approach: The study employs a comparative multiple-case analysis in conjunction with a systematic literature review (SLR). With clear inclusion and exclusion criteria based on integrated AI-AR applications with quantifiable results pertinent to SDG 11, a PRISMA-informed screening process was implemented. Cross-context comparison was made with six consciously chosen cases.
Findings: AI-AR transforms reactive to prospective systems and emergency response from static 2D methods to immersive, participative, data-driven models in urban planning. Cases show improvements in efficiency, fewer errors, higher participation, and resource optimisation using predictive analytics and immersive overlays.
Implications: AI-AR automates analysis, lowers mistakes, democratises knowledge for people and front-line staff, and encourages inclusive, fair results. It speeds up the move to digital transformation towards people-centred, resilient governance in the face of urbanisation and climate change pressures.
Originality/value: This study bridges the gap between AI-AR applications and governance outcomes by combining theoretical perspectives, comparative case evidence, and measurable administrative outcomes, offering valuable implications for policy and sustainable urban development.
JEL Classification: H83, O3, Q55, R58
References
Abdeen FN, Sepasgozar SM (2022) City digital twin concepts: A vision for community participation. Environ Sci Proc 12(1):19. https://doi.org/10.3390/environsciproc2021012019
Abrishami, S., & Jayaram, R. (2025). Digital twins and augmented reality for humanitarian logistics in urban disasters: Framework development. Logistics, 9(4), 143.
https://doi.org/10.3390/logistics9040143
Ameen, A., & Qadir, J. (2025). Integrating artificial intelligence and augmented reality for geospatial visualization in emergency management and built environment. Future Computer Systems and Informatics Journal, 2(1), 1-15. https://journal.xdgen.com/index.php/FCSI/article/view/337
Alvi, M., Dutta, H., Minerva, R., Crespi, N., Raza, S. M., & Herath, M. (2025). Global perspectives on digital twin smart cities: Innovations, challenges, and pathways to a sustainable urban future. Sustainable Cities and Society, 126, 106356. https://doi.org/10.1016/j.scs.2025.106356
Barsekh-Onji, A., Hernandez, Z. T., & Espinosa, E. O. C. (2025). Advancing smart public administration: Challenges and benefits of artificial intelligence. Urban Governance, 5(3), 279-292. https://doi.org/10.1016/j.ugj.2025.06.003
Baud, I., Jameson, S., Peyroux, E., & Scott, D. (2021). The urban governance configuration: A conceptual framework for understanding complexity and enhancing transitions to greater sustainability in cities. Geography Compass, 15(5), Article e12562. https://doi.org/10.1111/gec3.12562
Bittencourt, J. C. N., & Faccioni Filho, G. (2026). On the role of AI in building generative urban intelligence. Artificial Intelligence Review. https://doi.org/10.1007/s10462-025-11469-3
Chambers, P., Laato, S., Yoshida, H., Yrttimaa, T., Liimatainen, K., Uhlgren, V. V., ... & Nummenmaa, T. (2025). Gamified augmented reality for data collection in urban forests. Urban Forestry & Urban Greening, 129036. https://doi.org/10.1016/j.ufug.2025.129036
Das, D., & Kwek, B. (2024). AI and data-driven urbanism: The Singapore experience. Digital Geography and Society, 7, 100104. https://doi.org/10.1016/j.diggeo.2024.100104
Dcruz, J. G., Zolotas, A., Greenwood, N. R., & Bhadra, P. (2025). Structured AI decision-making in disaster management. Scientific Reports, 15, 32093. https://doi.org/10.1038/s41598-025-15317-w
Dong, L., Duarte, F., Duranton, G., Santi, P., Barthelemy, M., Batty, M., ... & Ratti, C. (2024). Defining a city—delineating urban areas using cell-phone data. Nature Cities, 1(2), 117-125.
https://doi.org/10.1038/s44284-023-00019-z
Elshater, A., & Abusaada, H. (2025). Some early insights into the use of AI tools within urban planning education. Journal of Urbanism, 178(1), 1-20. https://doi.org/10.1108/ARCH-06-2025-0262
Emad, S. (2025). The role of artificial intelligence in developing tall buildings and high-density urbanism: Dubai case insights. Buildings, 15(5), 749. https://doi.org/10.3390/buildings15050749
Fan, C., Zhang, C., Yahja, A., & Mostafavi, A. (2021). Disaster City Digital Twin: A vision for integrating artificial and human intelligence for disaster management. International journal of information management, 56, 102049. https://doi.org/10.1016/j.ijinfomgt.2019.102049
FEMA. (2025). Federal Emergency Management Agency – AI use cases | homeland security. Federal Emergency Management Agency – AI Use Cases. https://www.dhs.gov/ai/use-case-inventory/fema
Fistola, R. (2025). Artificial intelligence for urban planning—A new planning process to envisage the city of the future. Urban Science, 9(9), 336. https://doi.org/10.3390/urbansci9090336
Gupta, S., & Degbelo, A. (2023). An Empirical Analysis of AI Contributions to Sustainable Cities (SDG 11). In F. Mazzi & L. Floridi (Eds.), The Ethics of Artificial Intelligence for the Sustainable Development Goals (Philosophical Studies Series, vol. 152). Springer. https://doi.org/10.1007/978-3-031-21147-8_25
Ishihara, T., Nakanishi, R., & Kawai, N. (2024). Earthquake simulator by augmented substitutional reality. CEUR Workshop Proceedings, 3907. https://ceur-ws.org/Vol-3907/short4.pdf
Janssen, M., & Kuk, G. (2024). Quantifying AI-driven efficiency in urban decision processes. Digital Government: Research and Practice, 5(3), 1–20. https://doi.org/10.1145/3636512
Khanal, K. (2024). Collaborative governance for sustainable development in Nepal: Lessons from large-scale infrastructure projects. Journal of Innovation in Academia, 3(2), 15-32. https://doi.org/10.3126/idjina.v3i2.73200
Kyttä, M., Jaalama, K., & Fagerholm, N. (2023). Prioritizing participatory planning solutions: Developing place-based priority categories based on public participation GIS data. Landscape and Urban Planning, 239, 104868. https://doi.org/10.1016/j.landurbplan.2023.104868
Largest Cities by Population 2026. (2026-03-04). World Population Review. https://worldpopulationreview.com/cities
Larsen, P. X., & Lindström, K. (2024). Exploring the use of a 3D visualisation tool for participatory planning [Master’s thesis, Aalborg University]. https://vbn.aau.dk/ws/files/718505754/Thesis_done.pdf
Lartey, D., & Law, K. M. (2025). Artificial intelligence adoption in urban planning governance: A systematic review of advancements in decision-making, and policy making. Landscape and Urban Planning, 258, 105337. https://doi.org/10.1016/j.landurbplan.2025.105337
Leal Filho, W., Abubakar, I. R., Kotter, R., Grindsted, T. S., Özuyar, P. G., Salvia, A. L., Will, M., & Nagy, G. J. (2024). The role of artificial intelligence in the implementation of the UN Sustainable Development Goal 11: Fostering sustainable cities and communities. Cities, 149, 104937. https://doi.org/10.1016/j.cities.2024.105021
Lei, B., Liang, X., & Biljecki, F. (2024). Integrating human perception in 3D city models and urban digital twins. ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 10, 211-218. https://doi.org/10.5194/isprs-annals-X-4-W5-2024-211-2024
Lei, B., Su, Y., & Biljecki, F. (2023, September). Humans as sensors in urban digital twins. In International 3D GeoInfo Conference (pp. 693-706). Cham: Springer Nature Switzerland
https://doi.org/10.3390/environsciproc2021012019
Luo, J., Liu, P., Xu, W., Zhao, T., & Biljecki, F. (2025). A perception-powered urban digital twin to support human-centered urban planning and sustainable city development. Cities, 156, 105473. https://doi.org/10.1016/j.cities.2024.105473
Mazzetto, S. (2024). A review of urban digital twins’ integration, challenges and opportunities: Singapore and Dubai cases. Sustainability, 16(19), 8337. https://doi.org/10.3390/su16198337
Medaglia, R., Gil-Garcia, J. R., & Pardo, T. A. (2023). Artificial intelligence in government: Taking stock and moving forward. Social Science Computer Review, 41(1), 123-140.
https://doi.org/10.1177/08944393211034087
OECD (2025), Governing with Artificial Intelligence: The State of Play and Way Forward in Core Government Functions, OECD Publishing, Paris, https://doi.org/10.1787/795de142-en
OECD. (2026). Building an AI-ready public workforce: Implications and strategies. OECD Publishing. https://doi.org/10.1787/b89244c7-en
Othengrafen, F., Sievers, L., & Reinecke, E. (2025). From vision to reality: The use of artificial intelligence in different urban planning phases. Urban Planning, 10(1), 8576. https://doi.org/10.17645/up.8576
Pierre, J. (1999). Models of urban governance: The institutional dimension of urban politics. Urban Affairs Review, 34(3), 372–396. https://doi.org/10.1177/10780879922183988
Raymond, C. M., Gottwald, S., Kyttä, M., & Sipilä, M. (2025). Uses, opportunities and risks of artificial intelligence in participatory urban planning. Discover Cities, 1(1), 1-15. https://doi.org/10.1007/s44327-025-00137-4
Saengtabtim, K., Leelawat, N., Tang, J., Suppasri, A., & Imamura, F. (2025). Harnessing generative AI for enhanced disaster management: A systematic review. Big Earth Data, 9(1), 1-26. https://doi.org/10.1080/20964471.2025.2521157
Sanchez, T. W. (2025). The ethical concerns of artificial intelligence in urban planning. Journal of the American Planning Association, 91(1), 140-155. https://doi.org/10.1080/01944363.2024.2355305
Shakibamanesh, A., Ghorbanian, M., Izadi, S., Riahi, A., & Zeifodini, P. (2025). Utilizing Virtual Reality in the participatory urban policy-making process: A step toward facilitating effective citizen engagement. International Journal of Human Capital in Urban Management, 10(2). https://doi.org/10.22034/IJHCUM.2025.02.12
Sharifi, A., Amirzadeh, M., & Khavarian-Garmsir, A. R. (2025). The metaverse as a future form of smart cities: A systematic literature review of co-benefits and trade-offs.
https://doi.org/10.1016/j.cities.2025.105879
Sun, W., Bocchini, P., & Davison, B. D. (2024). Applications of artificial intelligence for disaster management. Natural Hazards, 103, 2631-2689. https://doi.org/10.1007/s11069-020-04124-3
Symeonidis, S., Samaras, S., Stentoumis, C., Plaum, A., Pacelli, M., Grivolla, J., ... & Vrochidis, S. (2023). An extended reality system for situation awareness in flood management and media production planning. Electronics, 12(12), 2569. https://doi.org/10.3390/electronics12122569
Terfurth, L., Heidenreich, A., Glunz, E., Kox, T., & Gerhold, L. (2026). Troubled water: Enhancing flood preparedness with eXtended reality. Computers in Human Behavior Reports, 22, 101004. https://doi.org/10.1016/j.chbr.2026.101004
Tranfield, D., Denyer, D., & Smart, P. (2003). Towards a methodology for developing evidence‐informed management knowledge by means of systematic review. British journal of management, 14(3), 207-222. https://doi.org/10.1111/1467-8551.00375
United Nations. (2024a). The Sustainable Development Goals Report 2024. shttps://unstats.un.org/sdgs/report/2024/The-Sustainable-Development-Goals-Report-2024.pdf
United Nations. (2024b). Extended report on SDG 11: Sustainable cities and communities. United Nations Statistics Division. https://unstats.un.org/sdgs/report/2024/extended-report
United Nations (2025). World Urbanization Prospects 2025: Summary of Results. UN DESA/POP/2025/TR/ NO. 12. New York: United Nations. https://population.un.org/wup/assets/Publications/undesa_pd_2025_wup2025_summary_of_results_final.pdf
Vatamanu, A. F., & Dinu, E. (2025). Integrating artificial intelligence into public administration: Challenges and vulnerabilities. Administrative Sciences, 15(4), 149. https://doi.org/10.3390/admsci15040149
Wirtz, B. W., Weyerer, J. C., & Geyer, C. (2019). Artificial Intelligence and the Public Sector—Applications and Challenges. International Journal of Public Administration, 42(7), 596–615. https://doi.org/10.1080/01900692.2018.1498103
Wirtz, B. W., & Müller, W. M. (2019). An integrated artificial intelligence framework for public management. Public Management Review, 21(7), 1076–1100. https://doi.org/10.1080/14719037.2018.1549268
Yigitcanlar, T., Corchado, J. M., Mehmood, R., Li, R. Y. M., Mossberger, K., & Desouza, K. (2021). Responsible urban innovation with local government artificial intelligence (AI): A conceptual framework and research agenda. Journal of Open Innovation: Technology, Market, and Complexity, 7(1), Article 71. https://doi.org/10.3390/joitmc7010071
Zhu, X., Li, H., & Wang, Y. (2025). Public administration with, of, and through AI: Toward a new paradigm in the era of intelligence. Public Management Review, 27(2), 185-201. https://doi.org/10.1080/23812346.2025.2578589
Zuiderwijk, A., Chen, Y. C., & Salem, F. (2021). Implications of the use of artificial intelligence in public governance: A systematic literature review and a research agenda. Government Information Quarterly, 38(3), 101577. https://doi.org/10.1016/j.giq.2021.101577
