A Dual-Dimensional Assessment of AI in Healthcare: Applications and Perceived Opportunities Across the WHO European Region

The rapid adoption of artificial intelligence (AI) in healthcare is reshaping service delivery and enabling more personalized, data-driven care. However, cross-country differences in AI implementation and perceived strategic importance remain insufficiently understood. This study proposes a dual-dimensional framework to assess AI maturity across 50 countries in the WHO European Region, distinguishing between actual AI applications and perceived opportunities. Using data from the WHO 2024–2025 Artificial Intelligence for Health survey, the AI Applications Index (AIA) is constructed using an intuitionistic fuzzy TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) method that accounts for uncertainty in implementation. In parallel, the AI Opportunities Index (AIO) is developed using a belief-structure TOPSIS approach to capture perceptions of AI’s strategic relevance. To better understand underlying patterns, Multiple Correspondence Analysis and Ward hierarchical clustering are applied to identify latent structures, homogeneous groups, and transitional development pathways. An Index of Alignment (IA) is introduced to measure coherence between AI applications and perceived opportunity. Countries are grouped into four development trajectories based on the mean values of the AI Applications and AI Opportunities indexes: AI leaders, implementation-driven systems, opportunity-driven systems, and lagging systems. These results are further compared with Ward clustering, revealing hybrid and transitional profiles not fully captured by aggregate classifications. The findings indicate that AI maturity is shaped not only by implementation levels but also by the alignment between technological capacity and strategic perception. The results highlight the multi-speed and institutionally differentiated nature of AI transformation in European healthcare systems.