Advances in AI present a clear and present risk to the higher education sector.
Regulators in TESQA are rightly pressing the issue—institutions need hand-on-heart (and eye-on-the-data) confidence that every student crossing the graduation stage is qualified (and did the assessment that had their name on it). But beyond assessment regulation, teaching and learning need to be prioritised.
Supporting academic staff and students to use AI responsibly in and for learning is the next frontier.
The AI in Higher Education Symposium at the University of Sydney last week was a prime example of how institutions can work together to meet this challenge. A sincere thanks to the Sydney team for bringing the sector together (2,500 people registered) —events like this are vital for shaping AI policy and practice in a way that is practical, evidence-based, and sustainable.
Policy impact happens through translation to practice.
When it comes to AI policy impact, academic teaching staff matter most. The Sydney event provided translation inspiration and learning along with professional joy and connection.
The sense of belonging that comes from realising you are not alone trying to figure out “programmatic assessment”, “levels of assessment security”, and the latest ways smart-prompting students can use AI to pass your class. AI is a challenge, but it’s one we are tackling together.
These communities of practice do more than share solutions—they remind us that higher education is a collective effort, not an individual struggle.
AI is moving fast. If higher education wants to shape the future rather than just react to it, cross-sector collaboration needs to continue. The Accord calls for a national body to advance quality teaching and create ongoing opportunities for collaboration—this is how we build not just AI policy, but a stronger university sector.
Professor Kelly Matthews works with the Institute of Teaching and Learning Innovation at the University of Queensland.
