AI Adoption Readiness and Use Intention Survey Data from Higher Education Non-Academic Staff: A PLS-SEM Study (N=213)

This dataset contains survey responses from 213 non-academic staff members at a Hungarian University collected to examine factors influencing artificial intelligence adoption intentions in higher education administration. The dataset includes demographic variables (gender, age, educational attainment, work experience, functional area) and Likert-scale responses (1-5) measuring six validated constructs: digital readiness (DIRE, 4 items), AI readiness (AIRE, 4 items), perceived ease of use (AIEU, 4 items), perceived usefulness (AIUF, 4 items), facilitating conditions (AIFC, 4 items), and behavioral intention to use AI (AIUI, 3 items). The data support partial least squares structural equation modeling (PLS-SEM) analysis examining direct and mediation effects in technology acceptance frameworks applied to AI contexts.