Barriers to artificial intelligence adoption among instructors of IT-related disciplines in higher education

A survey-based study

Bibliographic Data

ID22168388
AuthorsNadezhda Gorbunova (0000-0002-2549-9683, Karaganda Buketov University), Eduard Vorsin (Karaganda Buketov University), Yelena Spirina (0000-0001-7446-4869, Karaganda Buketov University), Saule Zhumagulova (Department of Applied Mathematics and Computer Science, E.A. Buketov Karaganda University), Sh R Zhumagulova (0000-0001-6587-0507, Karaganda Buketov University), Nadezhda Popova (Karaganda Buketov University)
Year2026
Volume11
Publication date2026-03-31
Peer ReviewedYes
Open AccessYes
TypeARTICLE
VenueFrontiers in Education (JOURNAL)
Journal identifiersISSN: 2504-284X • E-ISSN: 2504-284X
PublisherFrontiers Media SA (PUBLISHER • CH)
DOI10.3389/feduc.2026.1804254
OpenAlexW7144241069
LanguageEN
References cited35

The integration of generative artificial intelligence (AI) into higher education faces contradictory barriers. While the traditional “digital deficit” model posits that a lack of instructors' digital competencies is the primary obstacle, its applicability to IT-related disciplines remains questionable. This study investigates the key factors hindering AI adoption among IT instructors and empirically tests the “competence paradox” hypothesis, grounded in the Technology Acceptance Model (TAM), the Unified Theory of Acceptance and Use of Technology (UTAUT), and Technology Trust Theory. A quantitative multicenter survey ( N = 105) of IT instructors across three universities in Kazakhstan was conducted. The results revealed high self-assessed AI skills (M = 3.86) and strong perceived usefulness of AI (M = 4.19); however, correlation analysis found no relationship between competence levels and integration readiness ( ρ = 0.010, p = 0.917). Instead of internal skill gaps, the critical bottlenecks were external facilitating conditions, specifically the risks of academic dishonesty (M = 3.89), lack of licensed software (M = 3.78), and data privacy concerns (M = 3.41). These findings highlight a dual trust deficit—both technological (risk of hallucinations, M = 3.70) and institutional—culminating in an “institutional crisis of trust.” The study concludes that IT instructors are technically equipped for AI but abstain from full integration due to the absence of a secure and regulated ecosystem. Consequently, universities must shift their strategic focus from basic digital literacy training to robust infrastructural support and ethical policy development

Digital Literacy · Employability · Generative grammar · Higher education · Technological literacy · Technology Acceptance Model · Technology integration · Digital literacy in education · Technology Adoption and User Behaviour · Technostress in Professional Settings

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