Artificial intelligence has become one of the most discussed topics in higher education. Universities around the world are debating whether students should be allowed to use AI, how lecturers should respond, and how assessments should be redesigned. While these are important conversations, I believe they overlook a more fundamental question.
The issue is not whether students should use AI. They already are.
The real question is whether we are teaching them to think effectively in an age where AI has become part of everyday life.
For decades, education has focused on helping students acquire knowledge, solve problems, and communicate ideas. Today, an AI system can draft an essay, summarize a journal article, write computer code, translate languages, analyse datasets, and even generate research questions within seconds. If these tasks can increasingly be performed by machines, then the purpose of higher education must evolve.
This does not mean human thinking has become less important. On the contrary, it has become more important than ever.
Students must learn to ask better questions rather than simply search for answers. They must be able to evaluate AI generated responses critically instead of accepting them as truth. They must learn how to distinguish evidence from opinion, recognize bias, verify information, and understand the ethical implications of using artificial intelligence. These are not technical skills. They are intellectual skills.
In many classrooms, discussions about AI revolve around prompt engineering. While prompting is useful, it should never become the end goal. A well written prompt is valuable only because it reflects clear thinking. Better thinking produces better questions, and better questions produce better conversations with AI.
This suggests that AI literacy should be understood differently. It is not simply the ability to operate AI tools. It is the ability to think critically, creatively, and ethically while working alongside AI. A student who can generate impressive AI outputs but cannot evaluate their quality is not AI literate. A student who can challenge AI, improve its responses, and integrate them with human judgement is.
This shift has profound implications for universities. Assessment methods that reward memorization or the reproduction of information are becoming increasingly outdated. Instead, educators should design learning experiences that require students to critique AI outputs, compare multiple perspectives, justify their reasoning, solve authentic problems, and demonstrate original thinking. In this model, AI becomes a learning partner rather than a shortcut.
Perhaps the greatest opportunity presented by AI is not technological but educational. It challenges us to rethink what it means to educate a graduate in the twenty first century. The graduates of the future will not be those who compete with artificial intelligence in producing information. They will be those who know how to ask meaningful questions, exercise sound judgement, make ethical decisions, and create value from the partnership between human intelligence and artificial intelligence.
The conversation should therefore move beyond teaching students how to use AI. We should be teaching them how to think with AI.
That, in my view, is the true future of higher education.