Is higher education adapting fast enough to artificial intelligence? What should students still learn when AI can perform an increasing number of tasks? And how can universities ensure that technology enhances, rather than replaces, human judgement and learning?
These were some of the questions explored during the panel discussion “The AI-ready university: What does it take?”, held on 6 October 2026, as part of the AI-HED Final Event, hosted by the Amsterdam University of Applied Sciences (AUAS).
Moderated by Erik Kostelijk (AUAS), the discussion brought together institutional leaders, researchers, educators and students, including Henk Geveke (Vice-Chair, AUAS Executive Board), Dietmar Paier (Head of Teaching & Learning Center, UAS for Business & Society), Hannah Berkers (Researcher and Coordinator, AUAS), Wilco Verdoold (Lecturer, AUAS) and Jarad Tromp (Student, AUAS).
The conversation went beyond the opportunities and challenges of individual AI tools to address a more fundamental question: how should higher education evolve in a world where AI is becoming an integral part of learning, working and professional practice?
Beyond technology: rethinking education itself
One of the central themes of the discussion was that integrating AI into higher education requires much more than introducing new technological tools.
Panel members questioned whether traditional approaches to curriculum development, teaching and assessment can keep pace with the rapid evolution of AI. While educational programmes often take years to redesign, technological capabilities can change within months.
The challenge, therefore, is not simply to adapt existing practices to new tools, but to reconsider what universities teach, how students learn and which competencies education should develop.
Dietmar Paier described AI as an opportunity to rethink the long tradition of academic education, while other contributions highlighted the importance of reconsidering learning objectives and assessment methods rather than focusing exclusively on technological solutions.
The question is shifting from “How can we use AI in education?” to “What should education become in an AI-driven world?”
Human judgement: an increasingly valuable competence
Throughout the discussion, participants emphasised that technological proficiency alone is insufficient to prepare students for their future professional lives.
Hannah Berkers advocated a human-centred approach in which professionals develop the ability to decide when, why and how AI should be used. Rather than simply following automated recommendations, graduates need to critically assess outputs, understand their implications and retain responsibility for professional decisions.
Wilco Verdoold highlighted the importance of competencies that are difficult to measure or automate, including communication, professional judgement, trust and creativity.
The discussion also addressed the risk of overreliance on AI, including the tendency of AI systems to reinforce users’ assumptions rather than challenge them.
As AI becomes increasingly capable of performing routine and analytical tasks, higher education faces an important responsibility: ensuring that students develop the knowledge, judgement and confidence to work with AI without becoming dependent on it.
What do students expect from an AI-ready university?
Student contributions brought a particularly relevant perspective to the debate.
For students already accustomed to using AI as part of their academic work, the question is not necessarily whether AI should be used, but how universities can help them use it effectively, responsibly and critically.
Participants highlighted that students often develop their AI skills independently, outside formal education. This raises questions about the extent to which universities are providing sufficient guidance and structured learning opportunities.
At the same time, students stressed the continuing value of classroom interaction, group work and collaborative problem-solving.
These perspectives reinforced the idea that AI integration should not reduce opportunities for human interaction. Instead, it should create space for learning experiences that develop cooperation, reflection and critical thinking.
The discussion also raised concerns about unequal access to AI tools and competencies, highlighting universities’ responsibility to provide fair learning opportunities for all students.
From individual experimentation to institutional transformation
Another important theme was the need to move beyond isolated initiatives towards a shared institutional approach.
Panel members discussed the importance of developing AI literacy across academic communities, supporting educators’ professional development and creating opportunities for experimentation and knowledge exchange.
The AI-HED project itself was highlighted as an example of how collaboration across institutions, disciplines and national borders can help educators develop their competencies and explore innovative pedagogical approaches.
However, participants also recognised that experimentation alone is not enough. Universities need a shared vision of the future of education, informed by the perspectives of teachers, researchers, students and institutional leaders.
Such a vision should provide direction without eliminating the flexibility required to respond to continuous technological change.
Putting people at the centre of AI integration
Perhaps the strongest message to emerge from the discussion was the importance of adopting a human-centred — or even humanity-centred — approach to AI.
As Hannah Berkers emphasised, institutions should begin by identifying human needs and educational challenges, rather than allowing technological developments to determine their priorities.
This perspective places the quality of teaching, learning and professional work at the centre of institutional decisions. AI should support meaningful learning experiences, empower educators and students, and contribute to broader societal goals.
The discussion also underlined that universities must prepare students not only for employment, but for fulfilling lives in which creativity, autonomy, human relationships and a sense of purpose remain essential.
From discussion to action: the next steps for higher education
The panel concluded with a call for practical action.
Among the priorities identified were strengthening AI literacy among educators and students, developing collaborative approaches to curriculum innovation, ensuring equitable access to AI tools and involving different members of the academic community in shaping institutional strategies.
The discussion demonstrated that becoming an AI-ready university is not a destination, but an ongoing process of learning, experimentation, reflection and adaptation.
For the AI-HED consortium, this message resonates strongly with the project’s central ambition: moving from improvisation towards the effective, responsible and human-centred integration of AI in higher education.
Ultimately, the future of higher education will depend not only on how effectively universities adopt AI, but also on how successfully they preserve and strengthen the human value of education.
Watch the full panel discussion
Want to explore these questions further and hear the different perspectives shared during the event?
Explore more presentations, best practices and resources from the AI-HED Final Event:
