From Patchwork to Policy: Pan-Canadian Generative AI Strategy for Higher Education

Canada needs a national strategy for generative AI in higher education

ChatGPT hit campuses in late 2022 and exposed a gap. Some institutions banned it, others tested it, many waited. Students used it like Google. Faculty questioned the future of essays, assessment, and academic integrity.

Generative AI is no longer a curiosity. Used well, it personalizes learning, supports accessibility, and trims busywork. Used poorly, it widens inequity, spreads misinformation, and erodes trust in credentials.

Canada's post-secondary sector is at a crossroads. There is still no national framework to balance opportunity with risk. The result is a patchwork of policies and uneven student experience.

What Ottawa and the provinces should do

The federal government, provinces, and institutions need a dual strategy: clear rules plus sector-wide literacy. That starts now.

1) Establish a national regulatory framework

Create clarity on acceptable use, data protection, and accountability across teaching, learning, and research. Launch a national advisory council to provide interim guidance while standards are drafted and tested.

• Define acceptable uses of generative AI across coursework, assessment, and research workflows.
• Require compliance with privacy and data-protection laws for student and faculty data.
• Co-develop standards with Indigenous leaders and other underrepresented groups to ensure cultural relevance and fairness.
• Mandate human oversight for critical decisions in grading, admissions, and academic standing.

Use existing federal-provincial coordination through the Council of Ministers of Education, Canada to set baseline principles, align procurement and data norms, and fund pilots, faculty training, and student orientation modules. Ensure guidelines translate into daily practice, not shelf documents.

2) Embed AI literacy across higher education

Every graduate-engineering, business, arts, social sciences-should leave with a working grasp of how these systems function, where they fail, and how to use them ethically.

• Fund curriculum development in English and French that covers prompts, verification, bias, accessibility, and privacy.
• Train faculty on assessment redesign, citation standards for AI use, and discipline-specific use cases.
• Appoint a chief AI officer (or equivalent) at each institution to lead strategy, compliance, and change management.
• Provide targeted support for rural, remote, and Indigenous communities to close connectivity and device gaps.
• Standardize student orientation modules so expectations are consistent across courses and departments.

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The promise-and the risk-inside the classroom and beyond

AI already helps explain complex concepts, generate practice problems, and adapt materials to individual needs. It supports accessibility with real-time transcription, text-to-speech, and translation-critical for the 20 per cent of undergraduates and 11 per cent of graduate students with disabilities, and for international learners.

Administrators use AI for reminders and admission inquiries. Faculty draft lesson plans and build dynamic content faster.

The risks are real. Detection tools produce false positives, disproportionately affecting international and non-native English speakers. Models can hallucinate convincing but wrong information. Bias persists because training data skews Western. Access is uneven: paid plans, devices, and reliable internet are not universal. Indigenous students report lower familiarity with AI tools, reflecting broader digital divides.

A patchwork response is failing students

Only about half of Canadian universities have formal policies on generative AI, and most delegate decisions to individual instructors. The result: confusion, inconsistency, and inequity across programs and campuses.

Other systems are moving. The U.K.'s Russell Group published principles for responsible AI use in teaching and assessment. Canada needs a version that fits our context and governance structure. See the Russell Group's approach here.

Canada has already invested billions in AI research and infrastructure-from the pan-Canadian strategy to new advisory groups-but these efforts sit apart from higher education policy. It's time to connect them.

Generative AI and deeper thinking

AI should not replace thinking; it should raise the bar for it. Use AI for first drafts and idea generation, then require source checks, critique, and revision. Grade the process as much as the product with oral defenses, in-class problem solving, and project logs that make reasoning visible.

The AI literacy gap facing Gen Alpha

Many younger students are comfortable with chat interfaces but lack core skills: verifying claims, spotting bias, and protecting their data. Build these into first-year curricula and reinforce them across programs. Pair this with outreach and infrastructure support for Indigenous, rural, and remote learners so no group is left behind.

A dual path forward

This is not a choice between rules or education. We need both. A national framework provides fairness and accountability. Sector-wide literacy ensures responsible, effective use.

Generative AI is as transformative for learning as the internet was a generation ago. Canada can set the course now: stand up an advisory council within 6 months, publish baseline principles within 12 months, fund pilots and faculty training within 18 months, and make AI literacy a graduation outcome within 24 months. Move first, move together, and make it work on the ground.