Toward an integrated AI-Driven governance architecture for smart cities and digital economy systems
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Published:
Mar 30, 2026
Keywords:
AI-driven governance architecture, Design science research, Digital economy systems, Predictive and adaptive decision-making, Smart city systems
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Abstract
The rapid growth of smart city technologies and digital economy systems has significantly increased the complexity of urban governance, particularly in integrating heterogeneous data sources, supporting intelligent decision-making, and ensuring effective coordination across systems. However, existing approaches often remain fragmented, with limited integration between data infrastructures, artificial intelligence (AI), and governance mechanisms. This study addresses this gap by proposing and evaluating an AI-driven governance architecture designed to integrate smart city systems and digital economy ecosystems into a unified, data-driven framework. This research adopts the Design Science Research (DSR) methodology, encompassing problem identification, objective definition, architecture design, demonstration, evaluation, and communication. The proposed architecture is structured into five interconnected layers: data acquisition, data management, AI intelligence, governance, and service delivery. A demonstration scenario integrating smart mobility and digital economy systems illustrates the operational capabilities of the architecture. The evaluation is conducted using a multi-framework approach, incorporating COBIT, ISO 37120, TOGAF, NIST AI Risk Management Framework, ITIL, and GDPR, combined with expert-based assessment. The results indicate that the proposed architecture achieves a high level of effectiveness, with an overall evaluation score of 4.39, demonstrating strong alignment with governance, architectural, and service requirements. This study contributes by introducing an integrated AI-driven governance model that bridges smart city systems and digital economy ecosystems, enabling adaptive, predictive, and data-driven urban governance. The findings provide both theoretical insights and practical guidance for developing next-generation governance architectures in complex digital environments.
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How to Cite
Yulistiawan, B. S., Hapsanto, H. E., Wibowo, S., & Sihotang, H. T. (2026). Toward an integrated AI-Driven governance architecture for smart cities and digital economy systems. Indonesia Accounting Research Journal, 13(3), 272–295. Retrieved from https://journals.iarn.or.id/index.php/Accounting/article/view/665
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Boggs, A. S., Buchanan, K., Evans, H., Griffith, D., Meritis, D., Ng, L., & Stephens, M. (2023). National institute of standards and technology environmental scan. In Societa l and technology landscape to inform science and technology research. https://doi.org/https://doi.org/10.6028/NIST.IR.8482
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Hevner, A. R., March, S. T., Park, J., & Ram, S. (2004). Design science in information systems research1. MIS Quarterly, 28(1), 75–106. https://doi.org/https://doi.org/10.2307/25148625
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Janssen, M., & van den Hoven, J. (2015). Big and Open Linked Data (BOLD) in government: A challenge to transparency and privacy? Government Information Quarterly, 32(4), 363–368. https://doi.org/https://doi.org/10.1016/j.giq.2015.11.007
Kitchin, R. (2014). The real-time city? Big data and smart urbanism. GeoJournal, 79(1), 1–14. https://doi.org/https://doi.org/10.1007/s10708-013-9516-8
Kotusev, S. (2018a). TOGAF-based enterprise architecture practice: An exploratory case study. Communications of the Association for Information Systems, 43(1), 20. https://doi.org/https://doi.org/10.17705/1CAIS.04320
Kotusev, S. (2018b). TOGAF Version 9 . 2 : What ’ s New ? What Has Changed ? TOGAF and Genuine EA Best Practices. In The Open Group. (2018) (Issue June). https://www.opengroup.org/togaf
Mensah, P. (2025). AI Governance Models in Smart Cities: Comparative Analysis for Strategic Business Integration and Sustainable Urban Development. In AI in Business Management (pp. 188–220). Productivity Press. https://www.taylorfrancis.com/chapters/edit/10.4324/9781003614074-8/ai-governance-models-smart-cities-philip-mensah
Nam, T., & Pardo, T. A. (2011). Conceptualizing smart city with dimensions of technology, people, and institutions. Proceedings of the 12th Annual International Digital Government Research Conference: Digital Government Innovation in Challenging Times, 282–291. https://doi.org/https://doi.org/10.1145/2037556.2037602
Peffers, K., Tuunanen, T., Rothenberger, M. A., & Chatterjee, S. (2007). A design science research methodology for information systems research. Journal of Management Information Systems, 24(3), 45–77. https://doi.org/https://doi.org/10.2753/MIS0742-1222240302
Russell, S., & Norvig, P. (2021). Artificial Intelligence: a modern approach, 4th US ed. In PEARSON SERIES IN ARTIFICIAL INTELLIGENCE (4th ed.). Pearson. http://lib.ysu.am/disciplines_bk/efdd4d1d4c2087fe1cbe03d9ced67f34.pdf
Safronchuk, M. V, & Sergeeva, M. V. (2019). The concept of economic growth through digital economy perspective. Institute of Scientific Communications Conference, 1264–1271.
Wang, K., Zhao, Y., Gangadhari, R. K., & Li, Z. (2021). Analyzing the adoption challenges of the Internet of things (Iot) and artificial intelligence (ai) for smart cities in china. Sustainability, 13(19), 10983. https://doi.org/https://doi.org/10.3390/su131910983
Wirtz, B. W. (2019). Digital business models. Springer. https://doi.org/https://doi.org/10.1007/978-3-030-13005-3
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/https://doi.org/10.1080/14719037.2018.1549268
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/https://doi.org/10.1080/01900692.2018.1498103
Wirtz, B. W., Weyerer, J. C., & Kehl, I. (2022). Governance of artificial intelligence: A risk and guideline-based integrative framework. Government Information Quarterly, 39(4), 101685. https://doi.org/https://doi.org/10.1016/j.giq.2022.101685
Yoo, Y., Henfridsson, O., & Lyytinen, K. (2010). Research commentary—the new organizing logic of digital innovation: an agenda for information systems research. Information Systems Research, 21(4), 724–735. https://doi.org/https://doi.org/10.1287/isre.1100.0322
Zurawski, J., & Schopf, J. (2023). National Institute of Standards and Technology Requirements (Analysis Report). https://doi.org/https://doi.org/10.2172/1971111
Batty, M., Axhausen, K. W., Giannotti, F., Pozdnoukhov, A., Bazzani, A., Wachowicz, M., Ouzounis, G., & Portugali, Y. (2012). Smart cities of the future. The European Physical Journal Special Topics, 214(1), 481–518. https://doi.org/https://doi.org/10.1140/epjst/e2012-01703-3
Berigüete, F. E., Santos, J. S., & Rodriguez Cantalapiedra, I. (2024). Digital revolution: emerging technologies for enhancing citizen engagement in urban and environmental management. Land, 13(11), 1921. https://doi.org/https://doi.org/10.3390/land13111921
Bibri, S. E., Alexandre, A., Sharifi, A., & Krogstie, J. (2023). Environmentally sustainable smart cities and their converging AI, IoT, and big data technologies and solutions: an integrated approach to an extensive literature review. Energy Informatics, 6(1), 9. https://doi.org/https://doi.org/10.1186/s42162-023-00259-2
Bibri, S. E., & Krogstie, J. (2020). The emerging data–driven Smart City and its innovative applied solutions for sustainability: The cases of London and Barcelona. Energy Informatics, 3(1), 5. https://doi.org/https://doi.org/10.1186/s42162-020-00108-6
Boggs, A. S., Buchanan, K., Evans, H., Griffith, D., Meritis, D., Ng, L., & Stephens, M. (2023). National institute of standards and technology environmental scan. In Societa l and technology landscape to inform science and technology research. https://doi.org/https://doi.org/10.6028/NIST.IR.8482
Brynjolfsson, E., & McAfee, A. (2014). The second machine age: Work progress and prosperity in a time of brilliant technologies. WW Norton & company. https://wwnorton.com/books/9780393350647
Caragliu, A., Bo, C. Del, & Nijkamp, P. (2011). Smart Cities in Europe. Journal of Urban Technology, 18(2), 1–12. https://doi.org/https://doi.org/10.1080/10630732.2011.601117
Chandra, Y., & Feng, N. (2026). Algorithms for a new season? Mapping a decade of research on the artificial intelligence-driven digital transformation of public administration. Public Management Review, 28(3), 620–654.
Charles, V., Rana, N. P., & Carter, L. (2022). Artificial Intelligence for data-driven decision-making and governance in public affairs. In Government Information Quarterly (Vol. 39, Issue 4, p. 101742). Elsevier. https://doi.org/https://doi.org/10.1016/j.giq.2022.101742
Chen, J., Ramanathan, L., & Alazab, M. (2021). Holistic big data integrated artificial intelligent modeling to improve privacy and security in data management of smart cities. Microprocessors and Microsystems, 81(3), 103722. https://doi.org/https://doi.org/10.1016/j.micpro.2020.103722
Das, D. K. (2024). Exploring the symbiotic relationship between digital transformation, infrastructure, service delivery, and governance for smart sustainable cities. Smart Cities, 7(2), 806–835. https://doi.org/https://doi.org/10.3390/smartcities7020034
Data, W. C. on C. (2018). ISO 37120: Sustainable Cities and Communities. World Council on City Data (WCCD). (2018). https://www.dataforcities.org/iso-37120
Davenport, T. H., & Ronanki, R. (2018). Artificial intelligence for the real world. Harvard Business Review, 96(1), 108–116. https://doi.org/https://hbr.org/2018/01/artificial-intelligence-for-the-real-world
GDPR, E. U. (2018). General data protection regulation (gdpr). In Cit. on.
Giest, S., McBride, K., Nikiforova, A., & Sikder, S. K. (2025). Digital & data-driven transformations in governance: A landscape review. Data & Policy, 7(2), e21. https://doi.org/https://doi.org/10.1017/dap.2024.47
Hevner, A., & Chatterjee, S. (2010). Design science research in information systems. In Design research in information systems: theory and practice (pp. 9–22). Springer. https://doi.org/https://doi.org/10.1007/978-1-4419-5653-8_2
Hevner, A. R., March, S. T., Park, J., & Ram, S. (2004). Design science in information systems research1. MIS Quarterly, 28(1), 75–106. https://doi.org/https://doi.org/10.2307/25148625
ISACA. (2019). COBIT® 2019 Framework: Governance and Management Objectives. ISACA. https://netmarket.oss.aliyuncs.com/df5c71cb-f91a-4bf8-85a6-991e1c2c0a3e.pdf
ITIL. (2019). ITIL Foundation: ITIL 4 Edition.
Janssen, M., & van den Hoven, J. (2015). Big and Open Linked Data (BOLD) in government: A challenge to transparency and privacy? Government Information Quarterly, 32(4), 363–368. https://doi.org/https://doi.org/10.1016/j.giq.2015.11.007
Kitchin, R. (2014). The real-time city? Big data and smart urbanism. GeoJournal, 79(1), 1–14. https://doi.org/https://doi.org/10.1007/s10708-013-9516-8
Kotusev, S. (2018a). TOGAF-based enterprise architecture practice: An exploratory case study. Communications of the Association for Information Systems, 43(1), 20. https://doi.org/https://doi.org/10.17705/1CAIS.04320
Kotusev, S. (2018b). TOGAF Version 9 . 2 : What ’ s New ? What Has Changed ? TOGAF and Genuine EA Best Practices. In The Open Group. (2018) (Issue June). https://www.opengroup.org/togaf
Mensah, P. (2025). AI Governance Models in Smart Cities: Comparative Analysis for Strategic Business Integration and Sustainable Urban Development. In AI in Business Management (pp. 188–220). Productivity Press. https://www.taylorfrancis.com/chapters/edit/10.4324/9781003614074-8/ai-governance-models-smart-cities-philip-mensah
Nam, T., & Pardo, T. A. (2011). Conceptualizing smart city with dimensions of technology, people, and institutions. Proceedings of the 12th Annual International Digital Government Research Conference: Digital Government Innovation in Challenging Times, 282–291. https://doi.org/https://doi.org/10.1145/2037556.2037602
Peffers, K., Tuunanen, T., Rothenberger, M. A., & Chatterjee, S. (2007). A design science research methodology for information systems research. Journal of Management Information Systems, 24(3), 45–77. https://doi.org/https://doi.org/10.2753/MIS0742-1222240302
Russell, S., & Norvig, P. (2021). Artificial Intelligence: a modern approach, 4th US ed. In PEARSON SERIES IN ARTIFICIAL INTELLIGENCE (4th ed.). Pearson. http://lib.ysu.am/disciplines_bk/efdd4d1d4c2087fe1cbe03d9ced67f34.pdf
Safronchuk, M. V, & Sergeeva, M. V. (2019). The concept of economic growth through digital economy perspective. Institute of Scientific Communications Conference, 1264–1271.
Wang, K., Zhao, Y., Gangadhari, R. K., & Li, Z. (2021). Analyzing the adoption challenges of the Internet of things (Iot) and artificial intelligence (ai) for smart cities in china. Sustainability, 13(19), 10983. https://doi.org/https://doi.org/10.3390/su131910983
Wirtz, B. W. (2019). Digital business models. Springer. https://doi.org/https://doi.org/10.1007/978-3-030-13005-3
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/https://doi.org/10.1080/14719037.2018.1549268
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/https://doi.org/10.1080/01900692.2018.1498103
Wirtz, B. W., Weyerer, J. C., & Kehl, I. (2022). Governance of artificial intelligence: A risk and guideline-based integrative framework. Government Information Quarterly, 39(4), 101685. https://doi.org/https://doi.org/10.1016/j.giq.2022.101685
Yoo, Y., Henfridsson, O., & Lyytinen, K. (2010). Research commentary—the new organizing logic of digital innovation: an agenda for information systems research. Information Systems Research, 21(4), 724–735. https://doi.org/https://doi.org/10.1287/isre.1100.0322
Zurawski, J., & Schopf, J. (2023). National Institute of Standards and Technology Requirements (Analysis Report). https://doi.org/https://doi.org/10.2172/1971111
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