Author: Brigitta Kalina Tristani HernawanEditor: Iradat Wirid
Across universities worldwide, a quiet anxiety has begun to surface among recent graduates. They did everything right – choosing future-proof degrees, learning coding and digital skills, developing critical thinking and creativity. Then they started to apply for jobs.
The frustration is not simply the rejection, but the realization that the skills they spent years building are being quietly devalued – not because of other candidates, but the tools that can approximate them instantly, and, for free, Artificial Intelligence (AI).
This then raises a question: if AI replaces high-skilled jobs and reskilling won’t help, what is the relevance of higher education?
The Promise vs The Reality
The belief that higher education leads to better jobs and upward social mobility has long underpinned both individual aspiration and public policy. Rooted in human capital theory (Becker, 1964; Schultz, 1961), this claim has been validated across decades. From the Industrial Revolution onward, each wave of technological change operates on the same logic – workers who invested in education adapted, while those who did not were left behind (Katz & Murphy, 1992). The losers of technological advancement were those with only a high school diploma or less, whose routine tasks were gradually replaced by machines, computers, and eventually, the internet (Bell & Korinek, 2023).
This promise gained even greater urgency in the age of AI. As AI displaces an even-wider range of tasks, individuals are encouraged to upskill, reskill, and pursue the degrees that machines cannot replicate. The World Economic Forum’s Future of Jobs Report (2025) projected AI and big data skills as the most needed competencies by 2030. AI-related degrees such as computer science, data science, and big data are very promising as it is claimed that its graduates will survive the AI-driven world (Forbes, 2025). Governments responded accordingly. In Indonesia, LPDP scholarship programmes began prioritizing STEM fields (LPDP, 2025), while AI and coding were introduced into schools to prepare a competitive future workforce (Kemendikdasmen, 2024). In this context, higher education thus promised not only cognitive and creative capacities, but also relevance in an AI-driven world.
However, the reality has proven otherwise. The rise of generative AI is increasing automation exposure to precisely the white-collar, high-skilled occupations thought to be immune (Bell & Korinek, 2023). Generative AI can now write news and generate pictures, analyze legal documents, and even write code (McKinsey Global Institute, 2023), replacing occupations linked to university-level education such as STEM professionals, psychologists, lawyers, and consulting jobs (Felten et al, 2021; McKinsey Global Institute, 2023). These jobs that require the cognitive abilities that higher education cultivates (analytical thinking, logical reasoning, and problem-solving) are now more prone to automation than jobs that do not require a higher-education degree (Inglese, 2025).
The Misdiagnose
The conventional response to graduate unemployment is always the skills mismatch. However, such a claim does not seem to be relevant anymore as graduates have been prepared with skills and cognitive abilities needed for their future jobs. The relevance of higher education becomes questionable.
The problem, perhaps, is no longer a matter of mismatch. Acemoglu & Restrepo (2019) argued that AI displacement has begun to outpace what economists call ‘reinstatement’, meaning that AI are taking over cognitive tasks faster than new roles for human workers can emerge. If that is the case, no amount of curriculum reform or reskilling can close a gap that is not fundamentally about skills at all.
For decades, the value of higher education has been reduced merely to its instrumental purpose: producing employable graduates. While it is as important, Nussbaum (2010) has warned that treating education primarily as a tool for economic productivity erodes the very capacities needed to critically engage with the complex global problems, including AI itself. Instead of asking how do we prepare students for the AI economy, we should be asking about how do we prepare citizens to shape it?
The Society We Want
This reframing even points toward a more urgent purpose for higher education that goes beyond ensuring employability, but rather focusing towards two main ideas.
The first is education as meaning-making. Universities should be spaces where students do not merely acquire skills, but also develop values. The cognitive skills taught in the classes should encourage discussion on what a good life looks like and decide what kind of future they want – not simply how to fit into the one being built for them. This is not an abstract philosophy, but rather the precondition for a functioning democracy – citizens who have learned to think, deliberate, and judge (Dewey, 1997). In the context of AI, a student who has never been asked what they value cannot meaningfully participate in decisions about what AI should be allowed to do.
When citizens have been prepared with the capacity to think and imagine the kind of future they want, higher education has the role to build civic governance. Students should not only be equipped with the ability to build or use these systems, but also to scrutinize them. They should be able to understand AI embedded biases, contest AI outputs, and participate meaningfully in decisions about how AI is deployed – not only technically, but also ethically. In the age where AI can basically ‘build themselves’, it is important to have the capacity in analyzing who benefits from this system and who is harmed by it, so that we can govern it. These are the questions that require human judgement which are rooted in values.
By that, students are not merely prepared to become a workforce that keeps pace with AI, but rather to become a public who has agency to hold it accountable. Higher education becomes a civic institution that produces individuals who are capable of directing where AI goes.
Therefore, the question on what is the relevance of higher education in the age of AI will always be difficult to answer in the market terms. But, if we rather shift our focus to the kind of society that we want to build alongside AI, higher education is indispensable. More urgent, in fact, than it has ever been.
References
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