AI Competency Frameworks for University Teachers: A Systematic Literature Review Based on UNESCO Dimensions

Abstract

This article presents a systematic literature review on artificial intelligence (AI) competency frameworks for university teachers, based on UNESCO dimensions. The study follows the PRISMA 2020 methodology and analyses 12 peer-reviewed articles published between 2017 and June 2025.
Five key competency dimensions are identified: human-centred mindset, AI ethics, AI foundations and applications, AI pedagogy, and professional development. Findings reveal a predominance of technical approaches over pedagogical and ethical perspectives.
The AI foundations dimension emerges as the most developed area in the literature. In contrast, human-centred and professional development dimensions receive comparatively limited attention.
The study highlights the need for teachers to understand both technical aspects and the societal implications of AI. It also emphasizes the importance of integrating ethical principles such as fairness, transparency, and accountability.
AI pedagogy focuses on the use of generative tools and personalized learning approaches. Continuous professional development is identified as essential for adapting teachers to technological change. The analysis also reveals a fragmented research landscape with limited collaboration among authors and institutions.
There is a strong dominance of computer science publications and limited contributions from education research.
Key challenges include technological, pedagogical, and regulatory barriers to AI adoption. The article calls for more interdisciplinary and collaborative approaches in teacher training.
In conclusion, developing AI competencies for university teachers is a critical technological, pedagogical, and ethical imperative in higher education.