Picture the scene: a high school student in Bogotá opens ChatGPT and types “what’s the best university to study UX design in Colombia?”. The AI answers with three names. Yours isn’t one of them.

This isn’t about academic quality. It’s that language models found clearer signals at other institutions. And today, that has real consequences for enrollment.

Why this matters now

For years, SEO was the battleground of university visibility. Landing on Google’s first page was the goal. That game is still alive, and a new one has joined it: generative AI models (ChatGPT, Gemini, Perplexity, Copilot) answer questions directly, without the user clicking through to any site. They’re the new ground zero for information.

It helps to understand how they work. These models combine what they learned during training with real-time retrieval: ChatGPT Search, Perplexity, and Google AI query the web while they draft the answer. In both cases they prioritize the same things: structured content, organized data they can interpret without ambiguity, and mentions in authoritative sources. When your university speaks that language, it joins the pool of sources eligible to be cited.

The race for AI visibility in Latin America is still young. The region’s big names — UNAM, PUC Chile, Universidad de los Andes, UBA, PUCP — are on the same learning curve. What you do this week can shape where you stand in a few months.

This checklist gathers eleven actions across four fronts: content, technical, distribution, and platform. Each one comes with a concrete step you can take without opening a six-month project.

Content: structure and topical authority

1. Identify your five authority topics

Which academic areas is your university genuinely known for, through output, history, or recognition? Pick five and commit to publishing deep, consistent, interlinked content in those areas. AI models favor sources that show topical depth over shallow breadth.

Concrete action: List your five priority areas and check whether each one has at least three related pieces of content on your site.

2. Build or refresh program pages with clear semantic structure

Every degree or graduate program deserves a page with well-defined sections: what you’ll learn, graduate profile, career paths, duration, format. Models pull answers from well-organized content, and running text with no hierarchy gives them far less to work with.

Concrete action: Audit the pages of your three most strategic programs. Do they have clear H2 and H3 headings? Do they answer specific questions?

3. Add FAQ sections to your key pages

FAQs are one of the formats generative models read best. A direct question plus a concise answer is exactly the pattern a model looks for when it decides what to cite. If you want to go further, here’s how to combine FAQs and schema markup at a university.

Concrete action: Add five to eight real questions to your admissions page and to your main program pages. Use the language students use, not institutional phrasing.

4. Write with verifiable citations

If you say your university stands out in research, name the data behind it. If you have a corporate partnership, name the company. Models learn to cite sources that cite sources: editorial rigor carries over into AI credibility.

Concrete action: Review your last five blog posts. Do they cite data, studies, or verifiable external sources?

Technical: the foundations AI needs to read

5. Implement JSON-LD schema on your main pages

Schema markup is the language you use to explain to machines what you are. Organization, EducationalOrganization, Course, FAQPage: each type tells the AI exactly how to classify your content. With schema, it knows; without it, it infers.

Concrete action: Use Google’s structured data testing tool to check whether your pages have schema. If they don’t yet, prioritize at least Organization and FAQPage.

6. Make sure your site loads fast on mobile

Models learn from content crawlers can read easily, and a fast, stable mobile site sends better signals. On top of that, most of your future students visit you from a phone.

Concrete action: Measure your Core Web Vitals in PageSpeed Insights. If your LCP is over 3 seconds, that’s your first technical priority.

7. Create or verify your llms.txt file

llms.txt is an emerging standard, similar to robots.txt, that tells language models which pages on your site are the most relevant ones to read and cite. Some platforms already generate it automatically.

Concrete action: Try loading youruniversity.edu/llms.txt. If it isn’t there, talk to your technical team about creating it. Here’s a deeper look at how to implement an effective GEO strategy.

Distribution: presence beyond your own site

8. Keep a solid Wikipedia and Wikidata entry

Wikipedia is one of the sources AI models cite most. An entry that’s current, complete, and backed by structured data in Wikidata adds credibility every time a model looks for context about your institution.

Concrete action: Look up your university on Wikipedia. Is the information accurate and up to date? Does it have an infobox with founding year, student numbers, and location? Assign someone to maintain it.

9. Earn mentions in authoritative digital media

One article in a regional education outlet that cites your institution carries more weight than ten social posts. Mentions in media with high domain authority are signals models value. Understanding multiplatform citation helps you decide where to invest that effort.

Concrete action: Identify three relevant digital outlets in your country (education, business, technology) and plan a press release or an editorial collaboration this quarter.

10. Activate your Google Business profile with complete data

AI models consume data from Google’s Knowledge Graph. A well-completed Google Business profile — with the University category, hours, description, programs, and photos — feeds that knowledge graph.

Concrete action: Confirm your Google Business profile is claimed, verified, and updated with all the relevant information.

Platform: let your CMS work for you

11. Assess what your web platform does automatically

The ten items above can all be done by hand. But at a university with dozens or hundreds of pages, what happens automatically is what holds up over time. The difference between a GEO strategy that works and one that stays in slide decks is usually systematization.

Concrete action: Ask your digital team: does our CMS generate schema automatically? Do we have llms.txt live? Do metadata update themselves when content changes? Here’s the full strategic context of the shift from SEO to GEO.

The time to act is now

The universities that structure their content, build presence beyond their own site, and adopt GEO-ready platforms will be the ones that show up when a student asks ChatGPT about the best place to study their degree.

You don’t have to solve everything at once. Consistency builds authority, and authority is the currency of generative AI.

Want to see in detail how your university can implement GEO systematically? Download the GEO Playbook for universities or book a Griddo demo and we’ll show you how it works on a site like yours.