This review provides a critical reading of recent literature on the application of artificial intelligence (AI) in design education, focusing on emerging themes corresponding to the advent of AI in the pedagogy of different design disciplines. Using systematic screening, bibliometric and thematic analyses, the study examines 114 peer-reviewed articles published since 2020. This work is a thematic and bibliometric synthesis that uses PRISMA as a reporting guide rather than a fully compliant systematic review with meta-analysis. Key themes include the integration of generative AI into curricula, the facilitation of personalised learning, the enhancement of creativity, ideation, and technical skills, and uncertainty of the future job market. The review indicates that while AI tools could serve as a catalyst for design education, they also introduce challenges such as risks to academic integrity, diminished originality and critical thinking, over-reliance, and ethical dilemmas regarding authorship. A central observation is that the literature itself leans markedly optimistic: benefits such as creative augmentation are frequently reported, often on the basis of short-term, self-reported, or small-scale studies, whereas troubling consequences such as de-skilling, homogenisation of student output, and epistemic dependence on generative tools are acknowledged in principle but rarely investigated with comparable rigour. This review therefore reads the prevailing enthusiasm with deliberate caution and treats this imbalance as a finding in its own right. It concludes by advocating for a balanced, ethically grounded approach positioning AI as a cognitive collaborator. Such an outcome, however, is contingent rather than assured, and current optimism should be tempered until documented risks meet the same evidentiary standards as the claimed benefits.
Pooya Lotfabadi (Tue,) studied this question.