"AI can speed access to information, but only critical thinking turns information into understanding and understanding into wisdom," says Dr Adeboye Dada, Senior Lecturer in Entrepreneurship at the University of Northampton.
Beyond the prompt: why critical thinking must lead teaching in the age of AI
- Before AI: a tradition of deep thinking
- The present: AI embedded in everyday learning
- The future: willingness, adaptation and embedding critical thinking
Introduction
Artificial intelligence is no longer a novelty in Higher Education (HE); it is now the ambient atmosphere in which learning takes place. Conversely, Critical thinking has long been central to the quest of universities and has renewed urgency as generative AI reshapes how students learn, educators teach, judgments are formed, and knowledge itself is produced. Global guidance alerts that AI capabilities are advancing faster than educational systems can adapt, which advances the importance of human judgment, ethical judgment and inquiry (UNESCO, 2023; Department for Education, 2025). At the same time, the pattern of student behaviour has shifted; recent UK findings indicate that 92% of undergraduates use generative AI in their studies and 88% use AI to support assessments, reshaping preparation, drafting and study habits across the sector (HEPI and Kortext, 2025).
My close observation of events reflects that policies and regulations now promote responsible integration rather than resistance. The Quality Assurance Agency asks providers to redesign assessments for an AI-enabled context, and UNESCO calls for a human-centred approach that protects privacy, equity and integrity (Quality Assurance Agency for Higher Education, 2024; UNESCO, 2023). Against this backdrop, fostering critical thinking in the AI era offers reflection across three lenses: our teaching and learning tradition before AI, the realities of an AI-inundation in the current teaching practices, and the demands of a future enabled by AI. Each of these three stages is taken in turn:
Before AI: HE embraced a tradition of deep thinking
Long before machine intelligence entered classrooms, HE cultivated disciplined inquiry. For instance, John Dewey framed learning as a cycle of doubt, investigation, reflection and renewed understanding, rather than the passive reception of settled answers (The Education Hub, 2021). Similarly, Socratic teaching educates learners to ask better questions, probe assumptions, and justify claims, rather than regurgitating conventions or repeating conclusions (Chong, 2019). Evidence from a large meta-analysis shows that dialogue, authentic problems and mentoring reliably strengthen critical thinking across disciplines, which means pedagogic design and not only content drives growth (Abrami et al., 2015).
In my teaching experience, I have observed that practice reflects this legacy. In a humanities seminar, a live question such as What is justice invites students to articulate, defend and revise interpretations in dialogue with peers, the kind of structured discourse associated with gains in critical thinking (Abrami et al., 2015). In a laboratory, learners defend experimental designs, encounter unexpected findings and adjust methods, a cycle that aligns with Deweyan inquiry (The Education Hub, 2021).
The present: AI embedded in everyday learning
Today, generative AI functions not as an occasional tool but as a daily companion for students (HEPI and Kortext, 2025). Studies emerging from UK business schools suggest AI tend to improve performance mainly at lower cognitive levels, such as outlining and summarising, while raising concerns about reliability, accuracy and ethics (Essien et al., 2024). In response, sector guidance recommends moving beyond detection to assessment designs that authenticate student thinking through viva-style dialogues, design notebooks, field logs and transparent declarations of AI use (Quality Assurance Agency for Higher Education, 2024), while building AI literacy and protecting integrity (UNESCO, 2023).
Classroom practice is already evolving. For example, in a business module assessment, students use AI to draft and pass market analysis and then review the output for bias, errors, missing evidence and flawed assumptions before making recommendations, an approach aligned with both usage data and quality guidance (HEPI and Kortext, 2025; QAAHE, 2024). So, AI may support market or venture simulations, allow learners to experiment with opportunity evaluation, design a business plan and evaluate strategic decision-making. As such, educators can seek the rationales or evidence that show the student’s own judgement and reasoning visibly (QAAHE, 2024).
In philosophical terms, the imperative is clear. Kant’s postulation of sapere aude, dare to think for yourself, is largely relevant in the AI age. The vulnerability is not merely thinking incorrectly but ceasing to think at all. The educator’s task is to cultivate cognitive independence so that human judgment cannot be avoided (UNESCO, 2023).
The future: willingness, adaptation and embedding critical thinking
Whether accepted or resisted, the presence of AI will continue to weave itself into the fabric of curricula and organisational life, not by force, but by the quiet inevitability with which new paradigms reshape the conditions of thought. Accordingly, the AI Maturity Toolkit provides a pathway from scattered experiments to coherent institutional adoption across policy, staff development and platforms (JISC, 2024). International outlooks forecast that by 2030, about 39% of core skills will have changed, with analytical and creative thinking prominent among employer priorities (World Economic Forum, 2025). In addition, global indicators show rapid diffusion of AI across sectors even as sophisticated reasoning remains a frontier where humans add decisive value (Stanford HAI, 2024).
My take is that a practical AI adoption may involve three learning willingness approaches. First, preparation: it might be useful to develop foundational literacy in AI capabilities, limits and ethical risks, and require short declarations that explain when and how tools were used (UNESCO, 2023). Second, adjustment: weighted process evidence such as viva, pitch, conversations, design notebooks and research logs over product-only submissions, so that thinking remains visible and assessable (QAAHE, 2024). Third, embedding: inquire a regular practice through Socratic routines, reflective cycles and authentic problems, because these approaches strengthen critical thinking (Abrami et al., 2015).
Conclusion
In sum, in a rapidly changing digital landscape, the role of the educator is not diminished but expanded. AI can speed access to information, but only critical thinking turns information into understanding and understanding into wisdom. The moral and intellectual mission of HE remains the cultivation of minds capable of independent judgment. Designing learning so that thinking cannot be skipped; ensures graduates who can use powerful tools without becoming used by them (UNESCO, 2023; QAAHE, 2024). It is not the hat upon the head that matters, but the heart that gives life to thinking.
Dr Adeboye Dada is an Educational Consultant, External Examiner and Senior Lecturer in Entrepreneurship at the University of Northampton. He has over two decades of leading teaching and learning experience. His teaching blends insight, creativity and purpose to prepare tomorrow’s leaders.
