Dr Julia Chen, Hong Kong Polytechnic University, discusses the need for higher education to urgently update its strategic goals in light of the growing use of artificial intelligence.

This blog was originally published in the second edition of the HE Horizons magazine, read all of the magazines here.

AI-driven job displacement took centre stage at the recent World Economic Forum (WEF) in Davos. The Managing Director of the International Monetary Fund warned of an AI ‘tsunami’ hitting the global workforce, underscoring the urgency for higher education institutions to rethink whether their current curriculum graduates students into unemployment or a navigable future. 

Alongside concerns of AI automation becoming AI domination, there is a growing recognition of the enduring and increasing value of human-centric skills. The most recent Hong Kong Education Bureau (EDB) Employers Survey, published in 2025, shows that employers consistently rank work attitude (including passion, patience and perseverance) higher than technical knowledge required for the job; and interpersonal, analytical and problem-solving skills, and language proficiency as other important aspects for work. 

On top of employer preferences, universities must also understand the nature of the future workforce.  In my keynotes at education events, I often refer to several frameworks used to characterise the future, including VUCA (Volatility, Uncertainty, Complexity, Ambiguity), TUNA (Turbulence, Unpredictability, Novelty, Ambiguity), and BANI (Brittleness, Anxiety, Nonlinearity, Incomprehensibility).  These acronyms capture the reality that tomorrow’s graduates will enter environments marked by rapid change, unpredictable challenges, and complex systems that defy simple solutions. 

In such a context and the possibility of an AI tsunami that brings about an entry-level jobpocalypse, traditional curricula may no longer be sufficient.  Universities must design future-ready degree programmes with at least the following four mandatory components to help students survive overwhelming uncertainty. 

1. AI literacy should be a foundational element of every degree programme. It must, however, go far beyond the use of AI tools to a deep understanding of the capabilities and limitations of AI systems, and their ethical, social, and economic implications.  Importantly, students should also be trained to be designers of AI solutions, not just their consumers.  This includes hands-on experience in learning to leverage AI to enhance productivity and innovation in their chosen fields.   

2. While AI is transforming every sector, deep (trans)disciplinary education remains essential. Whether in engineering, business, or humanities, students can benefit from a strong foundation and rigorous training in their chosen fields. This expertise enables them to solve discipline-specific problems and apply AI and other emerging technologies in contextually relevant ways. Universities should ensure that disciplinary curricula integrate up-to-date industry practices and relevant technological advancements. 

3. In a recent ‘Student Voices’ forum I organised, students in two universities in Hong Kong described soft skills as the new hard skills. Indeed, they are power skills and powerful skills, such as emotional intelligence, communication, collaboration, leadership, and intercultural competence that are critical for success in life.  In a world where teams are often ‘glocal’ and diverse, the ability to connect, persuade, and work effectively with others is indispensable. Universities can embed training opportunities in these skills through interactive learning and assessment tasks, internships and co-curricular activities. 

4. Perhaps most crucially, curricula must intentionally cultivate attributes that prepare students for a future defined by VUCA, TUNA, and BANI. 

This means developing: 

• Resilience: the capacity to recover from setbacks and persist in the face of challenges. 

• Agility: the ability to adapt to new circumstances. 

• Self-learning: the ability to learn to learn and a commitment to continuous learning. 

• Systems thinking: seeing the interactions of elements within complex systems, and the effects of one step on the next in holistic problem-solving. 

• Value development: cultivating a strong sense of purpose and ethical grounding to avoid becoming brittle or overly anxious in the face of uncertainty. 

• Analytical skills: the ability to make sense of complex, volatile, and nonlinear situations, and to draw actionable insights from data, discussions and experience. 

These attributes cannot be taken for granted. They need to be nurtured through experiential learning, reflective practice, mentorship, and exposure to real-world challenges. Universities should design curricula that encourage experimentation, reward curiosity and initiative, and allow students space to rebound from setbacks. It is also imperative that universities be aware of the dangers of emotional dependence on AI as personal advisors. There have been too many post-AI counselling suicide cases to risk students’ emotional stability on AI.   

Dare to make paradigm shifts with strategic roadmaps 

As AI continues to reshape the landscape of work, universities must dare to make urgent and thoughtful reforms to their curricula to prevent today’s students from becoming redundant in the future. It is worthwhile to deliberately and explicitly embed complexity, uncertainty and unpredictability into course syllabi that integrate diverse perspectives and encourage authentic learning through academia-industry collaborations. Institutions should develop strategic roadmaps for curriculum innovation, starting with pilot initiatives and scaling successful models. Continuous dialogue with the industry and ongoing assessment of emerging trends are essential to anticipate evolving talent needs. When universities show this courage and determination, there may be a chance that higher education can remain relevant for the benefit of students and the society.