What does it mean to educate when machines can process information faster, analyse data more thoroughly, and even write more efficiently than most graduates? This question increasingly preoccupies higher education as artificial intelligence transforms not merely how we work, but what work itself means. The traditional promise of university education — that knowledge and credentials lead to meaningful employment — appears increasingly tenuous when many recent graduates struggle to find positions in their chosen fields.
Consider the peculiar disconnect emerging between academic confidence and graduate reality. It seems that whilst educators generally believe their students are workforce-ready, a significant portion of recent graduates report feeling unprepared to even apply for entry-level positions. How did we arrive at this extraordinary misalignment? Perhaps more pressingly, what does this gulf reveal about our fundamental assumptions regarding the purpose of higher education?
The erosion of traditional entry-level pathways raises profound questions about professional development itself. When AI completes in hours what junior lawyers once spent weeks reviewing, when coding tools handle the debugging that taught novice programmers their craft, what becomes of the apprenticeship model that has underpinned professional formation for centuries? Are we witnessing merely another technological disruption, or does AI represent something qualitatively different — a challenge not just to specific skills but to the very concept of human expertise?
Yet might this disruption illuminate rather than obscure education’s essential purpose? If machines excel at information processing and pattern recognition, perhaps the human contribution lies elsewhere — not in competing with AI’s computational prowess but in exercising capabilities that remain stubbornly, irreducibly human. What are these capabilities, and how might we cultivate them?
The question demands we reconsider what we mean by “skills” altogether. The contemporary discourse speaks of “soft skills” — communication, creativity, collaboration — as though these were gentle supplements to harder technical competencies. But isn’t this taxonomy itself a relic of industrial thinking? When employers increasingly seek workers who can navigate uncertainty and integrate new tools into existing workflows, they describe not soft skills but sophisticated intellectual capabilities: the ability to synthesise disparate information, to exercise judgement in ambiguous contexts, to create meaning where algorithms find only patterns.
This suggests a more radical possibility: that the value of higher education lies not in its capacity to transmit specific knowledge or technical competencies — both increasingly susceptible to AI displacement — but in developing what we might call intellectual versatility. The ability to think across disciplines, to reason ethically about unprecedented situations, to imagine possibilities beyond existing parameters — these represent not luxury additions to practical education but its essential core.
Yet here we may encounter a troubling paradox, and one that will not lead to the way forward we may need. Many academic programmes today would emphasise teaching “critical” skills, but crucially, they mean the ability to be vocally critical of today’s Western society, and its accomplishments, more than critical analytic skills and a stable intellectual platform from which to have a critical opinion about human society in the first place. When universities prioritise ideological critique over intellectual formation, they produce graduates fluent in deconstruction but lacking the foundational knowledge and reasoning capabilities to construct alternatives. Is it any wonder such graduates struggle when confronted with AI systems, which in one way or another are an ineliminable feature of modern professional life. These systems, whatever their limitations, operate from consistent logical principles, which should not be just understood at an engineering level but at this logical level itself.
If current cognitive-vocational skills are becoming outdated at an accelerating pace, should we not question the very premise of skills-based education, which can do little more than stack additional skills without end? Rather than asking how universities can better align with current labour market demands — demands that shift with ever-increasing velocity — might we ask how education can develop human capabilities that transcend specific applications and make us stable and responsible actors in whatever the new labour market looks like?
The liberal arts tradition, long dismissed as impractical, may offer unexpected guidance here, offering intellectual breadth over vocational specialisation, critical thinking over opinion formulation, personality formation over pragmatic training.
The stakes extend beyond individual career prospects. When vast numbers of jobs face displacement whilst entirely new categories of work emerge, we confront not adjustment but transformation. How do we prepare students for careers that don’t yet exist, for challenges we cannot currently articulate? The answer may lie not in predicting the future but in cultivating the intellectual resilience to create it. Obviously, this is not just a plea for some liberal arts education, but has its priorities straight. The comfortable assumption that higher education naturally leads to employment has been quietly eroded. One reaction is to defend academia against the evil forces of employability concerns, but that would be reactionary. Another reaction is to reinstate liberal arts programs, which opportunistically stack new skills and competences, which are visibly in touch with an assumed new reality. But beyond these typical reactions a more demanding question emerges, which may well benefit from developing a curricular response to artificial intelligence as the new and persistent kid on the block. The answer we give will determine not merely curriculum reforms but also the fundamental compact between universities and society.
Frank Hartmann, Lux Mundi Advisory Board