The paper examines how professionals working in Italian educational contexts - social educators and teachers - perceive and use Artificial Intelligence (AI) in their professional practice. Conducted within the TEACH-AI project, the study is based on questionnaire data collected from 400 social educators and more than 4,000 curricular and support teachers. The aim is to identify and compare empirically grounded profiles of engagement with AI by analyzing patterns of affordance-in-practice, professional capability, and sentiment. Cluster analyses identified four recurring profiles - Receptive, Adaptive, Oppositional, and Indifferent - showing structurally similar configurations across professional roles. Findings reveal a gap between the predominantly operational use of AI tools and their perceived potential to support reflective, inclusive, and relational educational practices. The paper discusses how cluster-based profiling can inform the design of adaptive and differentiated professional development pathways, moving beyond an understanding of AI integration based solely on levels of adoption.
Adamoli et al. (2026) studied this question.