Bridging the gap: Factors influencing AI adoption in higher education institutions in Bangladesh

Abstract

This study examines the key factors shaping stakeholders’ (e.g., students, faculty members, and administrative staff within Bangladeshi universities) intentions and attitudes toward adopting artificial intelligence (AI) in Bangladeshi universities. To understand the drivers and inhibitors of AI adoption, we used two well-known models, Unified Theory of Acceptance and Use of Technology (UTAUT) and its updated version, UTAUT2, while also looking at factors like attitude, perceived risk, and the practical value of AI. Stratified random sampling is used to collect relevant data from public and private universities across major cities. Data collection involved a structured questionnaire designed with a 5-point Likert scale to measure constructs related to AI adoption as mentioned earlier. Our findings show that performance expectancy, hedonic motivation, utilitarian value, social influence, and facilitating conditions directly influence stakeholder attitudes and behavioral intention. Perceived risk and effort expectancy, however, do not significantly impact attitude. We consider attitude a strong predictor of behavioral intention, which is a key influencer of actual AI adoption in Bangladesh. These results provide actionable recommendations for policymakers, university leaders, and tech entrepreneurs who intend to develop a conducive environment for AI-led innovation in universities in Bangladesh.