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This study presents a dynamic multi-criteria assessment of the digital readiness of European Union and selected neighboring countries for implementing artificial intelligence (AI) in smart cities. Using Vector Measure Construction Method (VMCM), a synthetic indicator was developed based on DESI data for years 2020–2024. The analysis revealed significant differences in digital maturity and allowed to distinguish both leaders and idlers in the digital transformation process. Countries such as Ireland, Hungary and Greece demonstrated the most dynamic improvements, driven by growth in e-government, e-commerce, and online financial services. On the other hand, countries like Poland and Slovakia showed measurable progress but remained at an intermediate level of readiness. The findings emphasize the importance of multidimensional development, policy coherence, and infrastructural investment for successful AI adoption in urban governance. Our VMCM approach proved effective in identifying not only the state but also the trajectory of digital transformation, offering valuable insights for decision-makers and planners in the context of smart urban development.

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Multi-criteria Assessment of DESI Levels for Managing AI Implementation in Smart Cities of European Union and Neighboring Countries

  • 会议论文

  • 发表日期：

    2026年

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  • Kesra Nermend,
  • Laura Brancu,
  • Jarosław Woźniak,
  • Waldemar Tarczyński

摘要

This study presents a dynamic multi-criteria assessment of the digital readiness of European Union and selected neighboring countries for implementing artificial intelligence (AI) in smart cities. Using Vector Measure Construction Method (VMCM), a synthetic indicator was developed based on DESI data for years 2020–2024. The analysis revealed significant differences in digital maturity and allowed to distinguish both leaders and idlers in the digital transformation process. Countries such as Ireland, Hungary and Greece demonstrated the most dynamic improvements, driven by growth in e-government, e-commerce, and online financial services. On the other hand, countries like Poland and Slovakia showed measurable progress but remained at an intermediate level of readiness. The findings emphasize the importance of multidimensional development, policy coherence, and infrastructural investment for successful AI adoption in urban governance. Our VMCM approach proved effective in identifying not only the state but also the trajectory of digital transformation, offering valuable insights for decision-makers and planners in the context of smart urban development.