AI Governance in Australian Education: Universities, Schools, and the TEQSA/ACARA Regulatory Landscape

The dual AI challenge for Australian educational institutions

Australian educational institutions face AI governance challenges on two distinct fronts simultaneously. As employers and service providers, they must govern their own use of AI — in student management systems, academic analytics, staff recruitment, and administrative operations. As educational institutions, they must develop coherent and defensible policies for student use of AI in learning and assessment. Both challenges require governance frameworks, but they are governed by different regulatory obligations and raise different ethical considerations.

TEQSA and academic integrity in the age of generative AI

The Tertiary Education Quality and Standards Agency regulates Australian higher education providers against the Higher Education Standards Framework. Standard 5.4 (Academic Integrity) requires providers to take reasonable steps to protect the academic integrity of their awards. The widespread availability of generative AI has created significant pressure on academic integrity frameworks — students can now use AI to generate assessments that are indistinguishable from their own work.

The TEQSA response has been to expect institutions to develop coherent, proportionate, and pedagogically sound approaches to AI in assessment — not simply to prohibit AI use, which is unenforceable, but to redesign assessment methodologies to be robust to AI assistance. TEQSA has published guidance encouraging institutions to develop AI literacy as a graduate attribute and to use AI detection tools with appropriate caution given their documented accuracy limitations.

AI detection tools and due process obligations

AI detection tools — including Turnitin's AI detection feature and dedicated tools like GPTZero — have documented false positive rates that have resulted in students being incorrectly accused of academic misconduct. The consequences for a student of an incorrect academic misconduct finding can be severe: course failure, exclusion from programs, and in some cases inability to complete their degree. Educational institutions that rely on AI detection tools without appropriate due process safeguards face legal exposure.

The due process obligations for AI-assisted academic integrity processes are the same as for any disciplinary process: the student must be given notice of the allegation, an opportunity to respond, and a decision made by a human decision-maker who considers all the relevant evidence. An AI detection score alone is not sufficient basis for an academic misconduct finding. The institution must be able to demonstrate that the process was fair and that the outcome was based on evidence, not solely on an algorithmic score.

Student data and privacy obligations

Australian universities are subject to the Privacy Act 1988 and the Australian Privacy Principles for the personal information of students and staff. AI systems that process student data — learning analytics platforms, student wellbeing monitoring systems, academic progression prediction tools — must comply with the APPs. The collection of student data for AI analysis must be disclosed, the use must be consistent with the purpose for which the data was collected, and the data must be secured appropriately. The use of predictive analytics to identify at-risk students raises specific consent and transparency obligations — students should know that their academic data is being analysed by AI systems and that these analyses influence the support or intervention they receive.