No degree is AI-proof. But delaying specialisation may offer students an edge
As AI transforms graduate careers, universities should rethink when students specialise and how they combine disciplinary expertise with broader skills.
The rapid advancement of generative artificial intelligence, exemplified by tools like ChatGPT and Claude, has created a complex landscape for students and universities in New Zealand and beyond. While AI can now perform tasks such as drafting reports, summarising research, writing code, and generating professional content, it is not yet reliable enough to replace professional expertise.
This development has led to significant changes in job roles, with 87% of New Zealand business leaders reporting that AI has altered or eliminated job roles, and one-third slowing entry-level hiring. In response to these challenges, the author argues that universities should reconsider the timing of students' specialisation and the structure of degree programmes.
Instead of abandoning disciplines or forcing every student into computer science, universities should focus on how early students specialise and whether current programmes provide genuine opportunities for cross-disciplinary learning. The blurring of disciplinary boundaries, driven by AI, necessitates a shift towards graduates who possess not only subject-specific knowledge but also the ability to question, verify, interpret, and take responsibility for information.
This ability, combined with critical thinking and professional judgement, becomes more valuable as AI excels in producing polished yet potentially inaccurate or irresponsible outputs.
Brief written by urgent.news from The Conversation AU's own syndicated text. Machine-written — it may contain errors, so check the original before relying on it.