When ease becomes a barrier: What influences student intentions to use Generative <scp>AI</scp> in higher education?

Abstract This study employs the Technology Readiness and Acceptance Model to uncover the factors influencing university students' intentions to adopt generative artificial intelligence (AI) technologies in higher education. With the rapid integration of Generative AI into academic contexts, understanding what drives students' intention to use these tools is crucial for developing effective pedagogical strategies. The study applies a conceptual framework that incorporates personality traits, perceived ease of use, perceived usefulness, compatibility, social influence and attitude towards the use of Generative AI. This study employs a quantitative approach with students currently studying in higher education across the United Kingdom. Findings indicate that optimism and compatibility significantly influence perceived usefulness, while perceived ease of use has a negative impact on intention to use, which contradicts the prevalent sentiment in the adoption literature. Additionally, perceived usefulness and optimism are the greatest positive influences on intention to use Generative AI. The results highlight the importance of aligning AI tools with students' learning needs and fostering positive attitudes to encourage usage. These insights provide valuable recommendations for educators and policymakers aiming to enhance the integration of AI in educational settings, ultimately preparing students for a technology‐driven future.