# UK Higher Education AI Discoverability Audit: Methodology

**Publisher:** Axelerant Research Team  
**Version:** 1.1  
**Published:** August 31, 2026  
**Last reviewed:** September 21, 2026

## Sample

The study covers 64 UK universities, university colleges, and specialist institutions across England, London, Scotland, Wales, and Northern Ireland. Russell Group and larger civic universities were excluded because their resourcing and operating context differ from the institutions this study examines.

## Seven checks

1. AI crawler policy in `robots.txt`
2. Network-edge behavior for a browser control and named AI crawler user agents
3. Structured data and Course or FAQPage types
4. Course-page discovery and facts in server-rendered HTML
5. Dependence on PDFs for applicant facts
6. Presence and quality of `llms.txt`
7. Public platform signals

All checks were read-only and used public endpoints. Edge agents were requested at least twice in the full audit. An agent was reported as blocked only when both attempts agreed and a normal browser control was served.

## Coverage and denominators

Fifty-four of 64 institutions were fully readable. Each percentage uses the stated denominator for that check. A failed request is recorded as unverified, never as an absent feature or negative result. The ten unreadable estates likely bias the sample toward understating edge blocking.

## Data handling

The downloadable dataset is anonymized. It contains the same 64 rows displayed in the report. No audited institution is named. University of East London and Regent's University London appear only as separate, permissioned examples from Axelerant's client work and were not part of the audited sample.

## Reproducibility and limits

The audit records what was publicly observable in August 2026. Network policy, markup, course content, and AI crawler behavior can change. A result is evidence of the tested response at that time, not proof of an institution's intent. The free check at https://www.axelerant.com/check can reproduce the checks for a current domain.

## Suggested citation

Axelerant Research Team. (2026). *The State of AI Discoverability in UK Higher Education, 2026* (Version 1.1). https://www.axelerant.com/uk-highered-ai-discoverability