AI is not simply another new tool in education. It is changing the way classrooms, workplaces, and even our homes function. From personalised tutors to automated grading, artificial intelligence is changing how students learn, how teachers teach, and how institutions run. As we race to equip the next generation with AI skills, we might be missing the real question. Instead of only asking how to bring AI into education, we should rather ask why we are doing it and for whom.
The stakes are higher than they appear. In a recent Science article, Marie Lynn Miranda (2026) emphasises that higher education must do more than just teach students to use AI. Institutions should train students to critically assess AI output, verify it against human expertise, and identify its biases and limitations. The objective is to develop not only proficient, but also ethical and professional AI users. This is a call for clarity, not caution.
AI is here to stay, and its benefits will be distributed unevenly unless we act intentionally. While students are busy using AI tools to get easy answers to their queries on anything and everything, including what is asked in their assignments and project work, institutions are racing against each other to claim integration of AI into their curricula to make students employable. On the other hand, reports indicate that our graduate students are largely unemployable. Large organisations are downsizing because AI bots are cheaper and better at performing routine tasks than even trained human beings.
According to the World Economic Forum’s 2026 Future of Jobs Report, on average, 39% of skill requirements across job categories, industries, and geographies are likely to change over the 2025–2030 period due to AI and other macrotrends. We are at a strange inflection point where trends contradict one another. Learning about AI tools is essential to get a job, and the same AI is the reason not to get a job or even to lose one.
The primary risk is not job loss but the concentration of AI’s advantages among a select few, which could widen existing disparities in race, income, and geography. Industry needs bots, but it also requires minds that can distinguish truth from hallucination and read between the lines before making a decision. Higher education has a significant opportunity to address this challenge, and this is exactly where the discussion needs to expand. Education systems should focus on critical thinking, sound judgment, and emotional growth rather than merely imparting knowledge to get certificates.
This is not just about pedagogy. It is about survival. The youth unemployment crisis is often captured by a single statistic: a rising share among those with higher education. But these numbers only tell one part of the story. Unemployment is rarely experienced by individuals alone. Behind every educated graduate who is out of work is often an entire household that has financed the degree, adjusted its spending, and continues to support the young adult’s job search. The pressure on families becomes even more acute when unemployment persists.
This is the ground against which we must think about the role of AI in education. The promise of AI is that it can make knowledge accessible to everyone, personalise learning to each student, and equip students with the skills they need to survive in a fast-changing world. But if we do not base this change on a strong ethical and human-centred approach, we risk creating a future where AI worsens the inequalities it was supposed to address. The push for AI integration in education is often justified by the need to prepare students for future jobs. And indeed, being skilled in AI, knowing how to create prompts, use AI in daily tasks, and work well with AI systems, will be very significant.
But what happens if these skills are not paired with understanding the core ethical issues of AI? What happens if students can build AI-run systems but cannot question whether they are fair, clear, or how they affect society? The result is a generation that is not ready to handle the moral complexities posed by the technologies they make.
This is where humanities as a discipline must play a role. Philosophy, literature, history and ethics are not just obsolete parts of a STEM-focused curriculum; they are the courses that enable students to think clearly, question authority, consider outcomes, and, most importantly, imagine and innovate. These are exactly the skills that the industry is looking for. In a white paper published in December 2025, the World Economic Forum defined Human Centric Skills as the four most essential skills that employers will look for.
These skills include emotional intelligence, collaboration and communication, learning and growth and creativity with problem solving. The same report suggested that employers’ demand for analytical and systems thinking, creativity, resilience, motivation and self-awareness, as well as curiosity and lifelong learning, will make these the core skills that remain critical over the next five years. India’s National Education Policy already outlined this synthesis, focusing on cross-disciplinary learning and a four-year undergraduate degree that allows engineering students to take history classes. But what is planned on paper is not the same as what happens in classrooms. In most schools, humanities are still just subjects students take to earn credits, not courses given the same serious attention as computer science or data engineering. This imbalance must change if AI education is to develop judgment, not just skills.
The way forward is a two-tiered approach, and both parts are necessary. Every student, irrespective of domain, needs a basic understanding of how AI systems work, where they can go wrong, and who is most likely to be affected first. Instead of an obscure elective, courses on ethics, critical thinking, and the societal impact of technology must be woven directly into every part of the curriculum. When universities prioritise AI technical skills while treating ethics as an afterthought, they widen the very divide they tried to bridge.
There is also a fairness issue that Indian higher education cannot ignore. Access to advanced AI tools, English-medium teaching, and good placement support is already uneven between public and private institutes, and between big cities and smaller towns. Adding AI skills on top of this existing gap, without investing in ethical and critical thinking skills, risks creating two groups of graduates: those trained to create and benefit from AI systems, and those left to deal with their implications.
None of this is purely an academic issue. Like the unemployment problems that affect whole families, the problems caused by AI education without human values will not remain confined to classrooms. They will appear in hiring decisions, in welfare systems, and in the biases built into systems that affect millions of people.
The human-centric skills retain their relevance over time because they are harder to automate, whereas technical or routine skills require constant updating as AI capabilities evolve. Rather than getting replaced, human-centric skills will become even more valuable as essential complements to digital technologies. Universities, employers, and policymakers must stop seeing humanities as just a balance to technical training and start seeing them as a necessary foundation, the only real way to ensure that the generation now entering our classrooms will become employable by the AI-driven organisations.
Dr. Debarati Dhar, Assistant Professor, Institute of Management Technology, Hyderabad
Prof. (Dr.) Nilanjan Chattopadhyay, Vice Chancellor, Jagran Lakecity University, Bhopal
(Views presented are personal)