AI is the biggest technological advance in the history of our species and unis must catch up, argues Professor Danny Samson
Unis are obsessed with trying to catch AI cheats but missing the bigger picture – their courses aren’t equipping students for an AI-dominated world, argues a senior academic.
Universities should undertake a paradigm shift with respect to how we are working with artificial intelligence, because right now we are in danger of severely underplaying what is required in what and how we teach.
This will result in a shortfall in our graduates’ skills and capabilities relative to what they will need in the workplace.
AI is arguably the fastest-moving, most dynamic and impactful technological change occurring in the world of work since our species began, along with the steam engine, electricity, computing and digitalisation. The world of work has markedly changed and our curricula mostly have not.
Two big changes must occur. First, we should be updating what we teach in almost every university degree to prepare students for the AI-enabled world: to not do so is to shortchange both our graduates and their future employers.
This necessary revolution in our curricula is not limited to incorporating large language models such as ChatGPT but must also include agentic AI and all other forms of how human capabilities can be ‘AI-augmented’.
Second, university assessment practices should not just be defending against ‘AI cheating’, but should be embracing AI to reflect what is happening in the real world and hence assessing AI-enabled problem-solving capabilities.
Testing students’ recall of facts has long become an anachronism, just as it is in the world of work. For example, closed-book exams, still in common use, always reflected an unrealistic approach to assessing student capabilities and given the AI enablement of work, this gap is now much exacerbated.
Workplaces are changing fast. Lawyers are using AI to simulate negotiations, litigations, optimise contracting structures and a host of other functions, not just writing letters and emails.
Scientists and engineers are using AI to improve their innovation processes and designs, making their work both more efficient and more effective, leading to faster, better and more efficient service deliveries.
Accountants and business executives are using AI to optimise resources.
These uses will accelerate. To not prepare graduates for the AI enabled world of work is like sending a plumber into the workplace without the ability to use a pipe wrench.
AI is sweeping through almost every conceivable industry: banking and insurance is using AI for both strategic and operational decision improvements, achieving better decision making through using more data in logical ways to optimise resource allocation, and also to improve risk awareness, analysis and management.
Supply chain managers use AI to improve their decision making from one end of their supply chains to last mile delivery, including production, transport and inventory policies and decisions.
Doctors and other clinicians are already using AI not just for note taking, but for suggesting and enhancing optimised and personalised diagnostic and treatment regime decision support, whereby in some applications AI is already outperforming unaided human judgment. Curricula needs to catch up and keep up.
An additional benefit of this proposed jump-shift in how and what we teach will be that thousands of university academics will be catalysed to learn about and embrace AI which will enhance and accelerate our research outputs, including in their relevance and quality .
The current culture and trajectory of universities is a traditional and relatively slow and conservative pace of change, which does and will not meet the requirements of the AI enabled economy for our graduates.
Rapid, action-oriented task forces are required to introduce real change in 2026, lest the gap between what and how we teach, and the realities of the fast moving AI-enabled workplace will widen, and our graduates will be less ‘fit for purpose’.
Universities may well need to change the structure of our course redesign and approval processes to match the speed and acceleration occurring in the AI enabled professional world.
In the near future some universities will move with significantly higher speed and quality in embracing AI into their curriculum and laggards will find their graduates much less attractive to employers: this will shift patterns of demand across the university sector.
In regard to rapidly evolving our curricula and teaching approaches to the fast-moving AI-enabled world, there is a case to be made for a centralised approach to such support, such as in curriculum development and case studies, such that resources could be concentrated to develop the newly required curriculum once rather than separately in our 42 universities.
The Department of Education could play a key role in catalysing this, and could even provide incentives to help the laggards move forward, in the national interest.
Danny Samson has been Professor of Management at the University of Melbourne for over three decades. His new book is titled Leading Improvement and Organisational Excellence in Hospitals
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