Navigating AI Integration Into Higher Education: A Study of the Dynamics Influencing Early-Career University Teachers’ Readiness to Integrate AI in Education

Abstract

Despite growing interest in AI in higher education, little is known about how early-career university teachers perceive and engage with it. This study addresses this gap by examining their perspectives and readiness to integrate AI into academic work. Fifty-seven teachers with less than one year of experience participated in semi-structured interviews and were classified into four readiness groups: Ready, Preparing, Not Ready, and Neutral/Indifferent. Epistemic Network Analysis was used to uncover the cognitive and relational dynamics shaping their strategies. Teachers in the Ready group demonstrated a balanced understanding of AI and regarded its adoption as both necessary and inevitable. The Preparing group recognized its complexities and actively considered technical and ethical implications. The Not Ready group lacked experience and expressed skepticism, often shaped by ethical concerns. The Neutral/Indifferent group showed uncertainty, heavy reliance on external support, and a limited sense of AI’s relevance. By highlighting these differentiated perspectives, this study reveals how early-career teachers navigate AI integration, pointing to diverse needs across readiness levels. Given AI’s transformative role in higher education, the findings stress the urgency of tailored support and professional development to help new educators develop the confidence, literacy, and ethical awareness needed for effective AI use.

Keywords

AI readiness early-career teachers higher education epistemic network analysis professional development

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