The adoption of electric vehicles (EVs) constitutes a pivotal strategy in mitigating climate change. The successful integration of EVs into the transportation system is predicated on the development and effective management of a robust charging infrastructure. The effectiveness of this infrastructure depends on the active participation of diverse stakeholders. However, the extant literature provides limited insight into the interrelationships among the charging infrastructure goals and the prioritization of these goals from the stakeholders’ perspectives. Stakeholders, including EV users, governmental authorities, charging station operators, charging station manufacturers and suppliers, e-mobility service providers, electricity distribution service providers, EV manufacturers, and research institutions hold diverse and sometimes conflicting priorities regarding infrastructure development. To systematically address these complexities, this study integrates the MACTOR (Matrix of Alliances and Conflicts: Tactics, Objectives, and Recommendations) method with Intuitionistic Fuzzy Sets (IFS), which extend classical fuzzy logic by incorporating both membership and non-membership degrees. This approach allows for a more comprehensive representation of stakeholder preferences by accounting for their degree of support, opposition, and uncertainty in decision-making. This study evaluates and prioritizes key EV charging infrastructure goals across multiple dimensions, including user experience, cost efficiency, integration, digitalization, sustainability, resilience, and safety. Through an intuitionistic fuzzy-based multi-criteria decision approach, stakeholder viewpoints are systematically aggregated to determine the relative importance of each goal, while also capturing the uncertainty in their evaluations. The findings offer a structured decision-support mechanism to help policymakers, urban planners, and industry stakeholders optimize infrastructure deployment amid diverse and ambiguous preferences in the EV ecosystem.