This article focused on two main topics currently on many agendas: smart cities and Artificial Intelligence (AI). The growing interest in the former is due to these cities’ multidimensionality and adaptability in terms of residents’ needs and the requirements of each municipality's reality. AI, in turn, currently plays a transformative, disruptive role in various areas by performing “smart” tasks, thereby facilitating the automation of processes and differentiation initiatives. Smart city strategic planning, especially in the long term, will most likely have to deal with adaptations to AI. Thus, research is needed that can contribute to a more holistic view of these topics and support decision-making processes in these areas. Based on the epistemological principles of the multiple-criteria decision analysis approach (MCDA), this article developed and tested a dynamic analysis system that allows smart city initiatives to address the challenges of adapting to AI. The proposed system highlights the cause-and-effect relationships in this context. The article included an application of the decision-making trial and evaluation laboratory (DEMATEL) technique. The procedural steps followed to implement this methodology were enhanced by close collaboration with an experienced decision maker, who has coordinated various projects in this research context. The proposed system's contributions and limitations were also analyzed in this article.