How universities can organise reliable information for AI discovery

Start with the information a student must trust

Before commissioning more pages, choose one priority audience and one decision: whether a course fits, whether applications are open, or how to ask an admissions question. Then identify the facts needed to make that decision. A university-wide visibility programme becomes manageable when its first scope is a named set of decisions and pages, rather than every departmental website at once.

Google's helpful-content guidance asks publishers to consider clear sourcing and easily verified factual errors. For an institution, a practical response is a fact register: a controlled record of what is approved, who can confirm it and where it appears. The register below is our proposed working method, not a platform requirement or a guarantee of AI inclusion.

Create a seven-field fact register

For each fact, record the approved value, applicable course or cohort, source URL or document, accountable owner, approval date, next review date and public pages that reuse it. Keep an unresolved value marked as unresolved rather than filling the gap with an assumed answer.

• Identity: official institution, school, department, course and award names; distinguish the teaching institution from the awarding body where relevant.
• Status: open, closed, suspended or proposed; preserve any approval conditions.
• Eligibility: academic and language requirements, prerequisites and applicant-specific conditions.
• Dates: intake, application deadline and relevant time zone; separate firm deadlines from indicative timings.
• Costs: tuition, mandatory charges and deposits, with currency, cohort and applicant category clearly identified.
• Delivery: location, mode, duration and attendance requirements; distinguish online, hybrid and in-person components.
• Next step: the official application page or responsible enquiry team, with a working contact route.

Assign an owner before asking a supplier to rewrite

A communications team can coordinate presentation without owning every underlying decision. Ask the institution to name the approving function for each field: for example, academic registry for an award title, admissions for eligibility, finance for fees and a programme team for delivery details. These are suggested roles; the institution should use its actual approval structure.

The supplier's scope should separate finding a conflict, proposing a correction, approving the fact and publishing the change. A GEO supplier should not resolve two contradictory fee tables by choosing whichever looks newer. Escalate the conflict to the named owner and retain the decision record.

Map every public copy back to the approved fact

Take the chosen course page and locate its prospectus PDF, department summary, FAQ and English or Chinese adaptations. Record which fields each copy contains. For external directories or partner pages, record the correction route and request status rather than assuming the institution can edit them directly.

Use this row for each discrepancy: [fact] / [approved source] / [conflicting URL and wording] / [affected cohort] / [owner] / [proposed correction] / [approval] / [published check]. Translation review must preserve conditions and scope; a shorter Chinese summary must not turn a conditional offer into a promise.

Make the approved information accessible and consistent

Google says its ordinary search foundations also apply to AI features: make important information available as text, provide useful internal links and ensure structured data agrees with the visible page. Meeting requirements does not guarantee crawling, indexing or appearance. Do not buy a supposed special AI markup package as a substitute for correcting the actual information.

Its structured-data guidelines also require current, relevant information that represents the page. Include metadata, structured data and downloadable files in the change checklist; correcting a visible paragraph alone can leave conflicting machine-readable or downloadable copies. Only use supported markup appropriate to the page, and do not treat a successful technical validation as proof that the underlying facts are accurate.

Use a bounded acceptance checklist

Start with a small agreed sample of high-priority pages. Ask the supplier to show a completed register, conflict log, owner approvals, implemented changes and dated live-page checks. Separately record any search or AI observations with the question, language, interface, date and cited URL. A corrected source page is evidence of completed work, not proof that every AI answer has changed.

SALIENS provides GEO audits, AI visibility monitoring, content and technical improvements, and ongoing GEO delivery for universities and other institutions, including English and Chinese requirements. Email info@oxfordintelligence.co.uk with your website, priority audiences, course or service areas and available information owners. The written scope determines delivery; rankings, citations, applications and enquiries are not guaranteed.

• Can every important claim be traced to an approved source?
• Does each changing fact have an owner and review trigger?
• Are unresolved conflicts visible rather than silently rewritten?
• Do language versions preserve the same conditions?
• Do pages, downloads and structured data agree?
• Are completed changes kept separate from measured discovery outcomes?