The drivers and outcomes of adopting AI in FinTech education from students’ perspective

Purpose This study aims to explore the determinants of adopting artificial intelligence (AI) in FinTech education and the expected outcomes. It explores the potential role of curriculum design, availability of AI tools and platforms, faculty expertise, and student acceptance of AI in the level of adopting its applications in teaching FinTech. The study also examines the impact of AI applications on the critical thinking ability, student engagement, and knowledge retention of FinTech students. Design/methodology/approach The study used the quantitative descriptive analytical approach. Data were collected from 252 FinTech students at Jordanian universities. These data were analyzed using Smart PLS, version 4.1.0.6. Findings The results found that curriculum design, availability of AI tools and platforms, faculty expertise, and student acceptance of AI significantly impact the level of adopting its applications in teaching FinTech. The results also indicated that AI applications significantly improve the critical thinking ability, student engagement, and knowledge retention of FinTech students. Originality/value This study enhances theoretical understanding of AI adoption in FinTech education and evaluates its performance. It bridges the gap between theory and practice by highlighting how AI supports effective learning in FinTech programs. The findings offer valuable insights for educators, curriculum developers, AI solution providers, and policymakers working on accreditation standards, contributing to more innovative and effective FinTech education systems.