Can you futureproof your career by choosing an AI-resistant degree?

Charlie Ball, an expert on graduate employment for Jisc, warns that trying to future‑proof a 45‑year career by selecting an “AI‑resistant” degree is a near‑impossible task in an era of rapid technological change. He argues that rather than hunting for specific vocations that might escape automation, young people should be equipped with adaptable skill sets that allow swift response to labour‑market shifts. Nonetheless, Ball identifies several fields where human involvement is likely to remain essential: research and development, engineering, creative arts and entertainment, medicine, nursing and midwifery, and education. In each of these areas, the core work—whether it is the imaginative spark of R&D, the physical oversight required in civil engineering, the uniquely human touch in artistic expression, or the empathetic delivery of health news—relies on capabilities that AI cannot fully replicate.

The underlying reason these sectors are less vulnerable to AI takeover is their dependence on human interaction, creativity, and responsibility. In research, AI can only draw on existing data, leaving the generation of truly novel ideas to humans. Engineering, especially large‑scale civil projects, demands real‑world judgment and oversight that machines cannot yet provide. Creative outputs from AI are, according to Ball, merely remixes lacking a distinctive new voice, and audiences tend to prefer authentic human artistry. In healthcare, while AI may aid diagnosis, the accountability for life‑changing decisions and the delivery of difficult news will stay with doctors, nurses, and midwives, whose roles also encompass compassionate care that technology cannot substitute. Similarly, education benefits from technological tools, yet the relational and pastoral aspects of teaching are inherently human.

Looking ahead, Ball anticipates that AI will augment rather than replace professionals in these fields, helping to alleviate shortages—particularly in nursing, midwifery, and teaching—while preserving the core human elements of the jobs. He envisions a future where doctors, educators, and engineers continue to operate alongside intelligent systems, with the latter handling routine tasks and the former focusing on complex, nuanced responsibilities. This hybrid model suggests that students and workers should prioritize developing soft skills, critical thinking, and ethical judgment to remain relevant, as these attributes will be indispensable in navigating a workplace increasingly intertwined with AI technologies.

⚡ Effects Interpreter