AI-DRIVEN CHALLENGES IN TECHNICAL HIGHER EDUCATION: AN INSTITUTIONAL PERSPECTIVE

Abstract

The rapid development of artificial intelligence (AI) technologies is substantially transforming higher education, particularly in technical universities that prepare specialists for high-tech industries. AI tools enable personalised learning, automate assessment, and enhance educational analytics, while simultaneously generating new pedagogical and ethical challenges. The aim of this study is to identify the key problems associated with the application of AI technologies in higher technical education institutions and to analyse their impact on teaching and learning processes. The research employs a mixed-methods approach that combines a review of the scholarly literature with an empirical investigation conducted through an online survey of 1,916 students and 515 faculty members. In addition, the authors carried out a supplementary survey in cooperation with student self-government bodies regarding the key AI tools used by students in the course of their studies; the sample of this supplementary survey comprised 378 respondents. The results show that AI is widely used by students, primarily for information retrieval, idea generation, and text production, while its application in complex analytical tasks remains limited. A significant gap was identified between students and faculty in the adoption of AI. Furthermore, the findings highlight problems related to academic integrity, the decline of independent learning, and the absence of a clear institutional policy regulating the use of AI. The study concludes that the integration of AI into higher technical education is systemic in nature and requires the development of institutional policies, the transformation of teaching methods, and the enhancement of digital competencies among both faculty and students.