Artificial Intelligence Adoption Amongst Digitally Proficient Trainee Teachers: A Structural Equation Modelling Approach Morales-Cevallos, María Belén Alonso García, Santiago Martínez Menéndez, Alejandro Victoria Maldonado, Juan José Artificial Intelligence (AI) Teacher training Educational technology Digital competence AI adoption in education The present study examines how pre-service teachers’ digital competence influences their acceptance and use of Artificial Intelligence (AI) in educational settings. Employing a quantitative approach via Structural Equation Modelling (SEM), the authors analyzed self-reported data from Early Childhood and Elementary Education students in Andalusian (Spain) universities. The findings indicate that professional engagement is associated with a critical assessment of AI, focusing on pedagogical and ethical considerations, whereas digital content creation skills promote a more positive and proactive attitude toward AI adoption. These results underscore the importance of teacher education programs that combine technical skills with critical thinking to foster responsible AI integration. This study acknowledges limitations, including its regional scope and cross-sectional design and recommends future longitudinal and comparative research to validate and expand these insights. By addressing these gaps, future studies could enhance our understanding of AI adoption in diverse educational contexts. 2025-07-04T11:03:59Z 2025-07-04T11:03:59Z 2025-06-03 journal article Morales-Cevallos, María Belén, Santiago Alonso-García, Alejandro Martínez-Menéndez, and Juan José Victoria-Maldonado. 2025. Artificial Intelligence Adoption Amongst Digitally Proficient Trainee Teachers: A Structural Equation Modelling Approach. Social Sciences 14: 355. [DOI: 10.3390/socsci14060355] https://hdl.handle.net/10481/105079 10.3390/socsci14060355 eng http://creativecommons.org/licenses/by/4.0/ open access Atribución 4.0 Internacional MDPI