Assessment Instruments for Artificial Intelligence Literacy in Healthcare Professionals: A Scoping Review

Artificial Intelligence is being integrated into clinical practice within regulatory frameworks that assign healthcare professionals responsibility for human oversight, making AI literacy a core professional competency; however, there is little consensus on how it should be measured. This scoping review maps the instruments used to assess AI literacy among healthcare professionals, together with the domains they cover and the psychometric properties they report. Following the Joanna Briggs Institute framework and PRISMA-ScR, five databases were searched for primary studies published from 2017 onwards in English or Spanish. Screening was supported by an active-learning framework, and methodological quality was appraised with JBI tools. Thirty-nine studies were included, predominantly involving nurses and physicians. Methodological quality was heterogeneous, with the main weaknesses concentrated in the identification and handling of confounding factors. The instruments fell into validated standardized scales and study-specific ad hoc questionnaires that seldom report structural validation. Item-level deconstruction suggested a two-level thematic framework: three competence domains—cognitive-conceptual (82.1%), practical-clinical (69.2%), and ethical-regulatory (56.4%)—and two co-assessed domains corresponding to dispositions and organizational context (84.6% and 38.5%). Measurement in this field is fragmented, and reliance on unvalidated instruments limits international comparability. Assessment and training should prioritize critical appraisal of outputs, ethical data governance, and human oversight.