From deskilling to reskilling: Navigating AI integration in academic practice in higher education

Abstract

The rapid integration of artificial intelligence (AI) into higher education (HE) has triggered both optimism and tension, with debates focusing on whether AI will empower or displace educators. This study addresses this paradox through a systematic pragmatic literature review (PLR) guided by the PRISMA framework, synthesizing 22 peer‐reviewed articles published between 2015 and 2025. The systematic review investigates three questions: (1) How is AI transforming the roles and practices of educators in higher education? (2) How are institutions responding to deskilling through professional development and reskilling programmes? and (3) What pedagogical challenges and misalignments arise from AI integration? Literature findings reveal that AI automates routine academic tasks such as grading, feedback and content preparation, creating risks of deskilling through authority loss and diminished creativity. Yet, reskilling pathways are also emerging, as educators transition into roles as facilitators, mentors and ethical gatekeepers. Institutional responses remain largely policy‐driven, focusing on compliance and integrity, with few structured reskilling programmes. Pedagogical challenges such as plagiarism, AI bias, hallucinations and over‐reliance are being addressed through authentic assessment redesign, critical AI literacy and blended human–AI pedagogy. To conceptualize this transition, the study integrates transformative learning theory (TLT) and the technological–pedagogical content knowledge (TPACK) framework, producing an integrative conceptual model. TLT frames AI as a disorienting dilemma requiring reflective identity transformation, while TPACK highlights the knowledge balance needed for effective AI adoption. Both TLT and TPACK explain the deskilling–reskilling pathway and provide a holistic foundation for practice. The study contributes theoretically by mapping TLT and the TPACK framework onto the context of artificial intelligence in higher education, highlighting the importance of positioning AI as a collaborator rather than a competitor in academic practice.

Rationale for this study: The rapid integration of artificial intelligence (AI) in higher education has intensified longstanding challenges related to academic identity, faculty development, and pedagogical adaptation. However, existing scholarship remains fragmented, with limited understanding of how AI simultaneously creates risks of deskilling and opportunities for reskilling among educators.

Why these findings matter: The findings demonstrate that AI is neither inherently deskilling nor reskilling. Rather, its impact depends on institutional support, educator agency, and the extent to which professional development, pedagogical innovation, and AI literacy are systematically embedded within higher education.

Implications for educational researchers and policymakers: The study highlights the need for researchers to examine AI integration through both professional identity and pedagogical lenses, while encouraging policymakers to move beyond compliance‐focused governance toward sustained investment in faculty development, ethical AI literacy, and authentic assessment practices that support long‐term educational transformation.