The Council of Ontario Universities, representing 20 member institutions, has released a road map urging collaboration to address artificial intelligence's impact on higher education. According to the report, universities must work together rather than individually to navigate AI-driven changes, including threats to academic integrity and shifts in workplace demands. The report makes a dozen recommendations for universities and a handful for provincial and federal governments.

Why Ontario's 20 universities are pooling resources on AI

The report, produced by a task force, argues that individual institutions cannot tackle AI's challenges alone. As Vivek Goel, president of the University of Waterloo and a task force member, told the Council:universities are trying to grapple with what the right principles should be when it comes to artificial intelligence. The report proposes shared principles and joint initiatives to avoid duplication and leverage institutional strengths, according to the Council's statement.

This collaborative push comes as generative AI models raise widespread anxiety about cheating, since university assessments have long reiled on written work. The report suggests that approach may no longer be sufficient, pointing to oral examinations as a potential alternative.. The Council's president, Steve Orsini, identified four major tasks: preparing students for a changing work world, helping Ontario industries adopt AI, updating instruction and assessment, and protecting digital sovereignty.

The shift from written work to oral exams

One of the most concrete proposals in the report is a move away from traditional written assessments. The report notes that generative AI can produce volumes of text at the click of a button, prompting widespread concern about cheating. As a result, the report suggests that written work may not be the primary tool for assessing student learning in the future, and that oral examinations may become more important.

This recommendation, however, raises practical questions. How would oral exams scale for large introductory classes? Would faculty need retraining? The report does not detail implementation costs or timelines, leaving universities to figure out logistics. According to the Council's report, the change is framed as a necessary adaptation rather than an immediate mandate.

Digital sovereignty: why the report wants Canadian-hosted data

The Council's report calls on the federal government to invest in additional computing capacity that would make it possible to host data on servers located in Canada , rather than in the U.S. This reflects concern over control of sensitive student and research data when using AI tools.. Steve Orsini said the goal is to protect digital sovereignty by ensuring that control of sensitive data remains in Canada.

The request is part of a broader push for infrastructure funding. Without Canadian-hosted computing, universities risk relying on U.S.-based cloud services, which may expose data to foreign legal jurisdictions. The report argues that Canadian universities have played an important role in the development of artificial intelligence and should maintain that leadership by keeping data within national borders.

What Ottawa and Queen's Park are asked to fund

Beyond data hosting, the report asks the provincial government to provide more support for co-op placements and work-integrated learning opportunities. This is intended to help students gain hands-on experience in AI-affected industries. The recommendations for governments are a smaller set than those for universities — a handful versus a dozen.

Yet the report does not specify dollar amounts or funding mechanisms. As the Council acknowledges, universities see preparing students for a work world in a state of flux as a major task. Whether the provincial or federal governments will allocate new money remains an open question. The report also does not address potential resistance from faculty unions or student groups worried about job displacement or the erosion of traditional academic practices.

According to the Council, universities must leverage their various strengths in different aspects of AI for the benefit of the system as a whole. But without clear funding commitments and a timeline for collaborative action, the road map may prove easier to draft than to follow.