International students ask AI about rankings first. What Canadian institutions should publish
International students who use AI to choose a university ask about rankings first, then programmes and outcomes. The pages a Canadian institution should fix.
The short answer
International students who use AI in their search ask first about rankings and reputation, then about programmes, career outcomes and student life. A Canadian college or university should publish those facts where engines can read them: a dated rankings page, programme pages with fees and intakes, and outcome data. Then check what AI says in your main source countries.
Key takeaways
- In INTO's survey of newly enrolled international students, reported by ICEF Monitor in January 2026, rankings and reputation were the most common question students put to AI.
- The strongest evidence on AI in college search is from the US: in EAB's survey of more than 5,000 US high-school students in October–November 2025, 46% used AI tools in their search.
- In the same EAB survey, 18% of US students removed a college from their list based on AI results.
- Programme pages that state fees, intakes, entry requirements and duration in plain text give an engine facts to repeat instead of guesses.
- Test your institution's AI answers with prompts written the way students in your main source countries ask them.
In this article
What do international students ask AI?
They ask about rankings and reputation first. ICEF Monitor reported in January 2026 on a survey by INTO University Partnerships of newly enrolled international students, fielded in September 2025.1 A minority had used AI in their initial search, with higher use among students from several East Asian markets. Those who did asked most often about rankings and reputation, then about programme details, career outcomes and student life.
IDP's Emerging Futures survey of prospective international students, reported by Times Higher Education in October 2025, found the same direction of travel. Students were using ChatGPT and similar tools to shortlist institutions and choose a field of study, often before they spoke to an adviser.2
We did not find a survey of this kind limited to students choosing Canada. The pattern above comes from students heading to other destinations. Our view: the questions students ask are not specific to the destination, so a Canadian institution can plan around them now and test its own answers rather than wait for local data.
The clearest numbers come from US college search
The best-measured evidence comes from domestic US students, so read it as a signal, not a Canadian figure. In EAB's survey of more than 5,000 US high-school students in October–November 2025, 46% said they used AI tools in their college search, up from 26% in EAB's spring 2025 survey.3
The figure that should worry admissions teams is the next one. In the same survey, 18% of US students said they had removed a college from consideration based on AI results.3 An institution can drop off a list without a student ever visiting its website.
We looked at what those US students ask in our July piece on admissions pages. International applicants add questions a domestic student rarely asks: fees in their own terms, work rights during and after study, and how the institution compares with options in other countries.
US high-school students, Oct–Nov 2025
AI already shapes the shortlist
What should a Canadian institution publish?
Publish the facts behind each common question on a page an engine can read, in plain text, with a date. Answers built from vague marketing copy fill the gaps with guesses or with third-party sites that may be out of date.
| Student question | Page to own it | Facts to state |
|---|---|---|
| Is it well ranked? | Rankings and recognition | Ranking name, year, position, link to the method |
| Does it offer my programme? | Programme page | Credential, duration, intakes, campus, delivery mode |
| What will it cost? | International fees | Tuition for international students, in CAD, by year |
| Can I get in? | Entry requirements | Grades, English test scores, deadlines by country |
| Will it lead to a job? | Outcomes | Employment and co-op data, with survey year and method |
| Can I work while studying? | Work and immigration | Link to the federal rules; never paraphrase them loosely |
Illustrative. Our checklist; adapt the pages to your programmes.
Two rules make these pages useful to an engine. First, put the fact in the text, not in a PDF brochure or an image. Second, date it. A tuition figure with "2026–27" next to it is quoted correctly far more often than one without.
Our view: the outcomes page is where most institutions are weakest. If you publish graduate employment figures, state the survey year, the response rate and who was counted. An engine that repeats an unexplained figure helps nobody, and a student who checks it will trust you less.
Rankings: be precise or be absent
Because rankings are the first question, engines will answer it whether you help or not. They draw on ranking publishers, student forums and agents' sites, and they blend different tables and years into one sentence.
Publish a single rankings page that names each table, the year and your position in it, and links to the publisher. Do not round up, do not say "top" without the table and do not mix subject and overall rankings. Engines repeat superlatives, and a claim a student cannot verify does more harm in an AI answer than on a brochure.
If your institution does not appear in the major tables, say what you are measured on instead: accreditation, co-op placement, programme-level recognition. Silence leaves the engine to compare you on someone else's terms.
Your agents' pages are sources too
Many international students hear about an institution through an education agent, and agents' sites are among the pages engines read. If an agent lists last year's fees or a programme you have closed, an answer can repeat it with confidence. Send your agent network a dated fact sheet each intake, ask them to link to your programme pages rather than copy them, and check the largest agents' listings when you check the engines.
How to check what AI says now
Ask the engines the questions your applicants ask, in the way they ask them. Write prompts for your main source countries, such as India, the Philippines, Vietnam or Nigeria, and include the programme, the budget and the country choice in the student's own words.
- "Best colleges in Canada for a diploma in data analytics for an Indian student with a budget of 20 lakh"
- "Is a business degree in Canada better than in Australia for a student from Vietnam?"
- "Which Canadian universities have co-op for computer science international students?"
Record whether you are named, what is said about fees and rankings, and which sources are cited. Repeat the prompts on more than one day, because answers vary between runs. Our audit runs each prompt on three separate days across six engines: ChatGPT, Gemini, Perplexity, Claude, Copilot and Google AI.
Where an answer is wrong, trace the error to its source before rewriting your own pages. Our guide on fixing what ChatGPT gets wrong about you sets out that process, and the accuracy audit lists the facts to check first. For institutions, those are fees, intakes and rankings.
