Developing a model for developing artificial intelligence competencies in students from non-core professional study fields

Abstract

This article presents a model for developing artificial intelligence (AI) competencies in students majoring in non- technical fields. The relevance of this study stems from the widespread penetration of AI technologies into various professional fields, making applied AI literacy a universal requirement for modern professionals. The aim of this work is to develop and provide scientific and methodological justification for a pedagogical model that adapts the study of AI fundamentals to the specific needs of non- technical fields. The model is based on active learning methods, such as project- based learning, case studies, problem- based learning, and the flipped classroom model. These methods, when used, significantly increase student engagement, foster a deeper understanding of the material, and improve graduates' professional readiness. Particular attention is paid to the critical conditions for the successful integration of innovations: the need for systemic institutional support, high teacher readiness to master new pedagogical roles, quality instructional support, and the creation of a flexible, supportive educational environment. The results demonstrate that shifting the focus from technical programming to ethical use, industrial engineering, and the integration of AI tools into professional tasks ensures highly effective training. The practical significance of this work lies in providing educational institutions with an adaptable framework for modernizing curricula and developing interdisciplinary courses.