Why this matters
Patients, students, and referring physicians increasingly begin their search for UAMS information by asking an AI assistant rather than a search engine. UAMS AI Wayfinding is the 2026 initiative that helps those tools represent us accurately.
When a patient wants to know whether UAMS treats a rare cancer, they used to type a search term and scan results. Increasingly, they ask ChatGPT, Claude, Gemini, Perplexity, or Microsoft Copilot directly, and they trust the answer. When those tools confuse a subspecialty, invent a provider, or send a patient to the wrong clinic, it becomes a patient-experience problem, a brand problem, and a risk problem all at once.
UAMS cannot control whether people use AI to ask about us. We can control how accurately AI represents us when they do. That is what this initiative is about.
The work is lightweight. It uses existing staff, existing infrastructure, and no new vendors. It continues the accessibility and content standards UAMS already follows. But it closes a real gap in how our web presence functions in 2026.
How it works: three small files
Every UAMS web property carries three small text files that tell AI tools what the site is, what it covers, and where to send users for the right next step.
The gatekeeper: robots.txt
The security desk that decides which AI tools are allowed to read each section of a site.
The handshake: llms.txt
A short, AI-readable summary that introduces the site and points to the most important content for answering questions.
The directory: llms-full.txt
A deeper content index that tells AI tools how to route questions, what to cite, and when to redirect users to a more appropriate UAMS site.
200+ UAMS web properties
This work applies to every public-facing UAMS website under Web Services governance, from uamshealth.com to individual college and department sites. The scale is the point. A patient asking about UAMS could land on any of them, and AI tools need a consistent way to understand each one.
Two layers, working together
The UAMS web presence has two layers. The first is the routing architecture: the arrangement of subdomains, the primary gateway at www.uams.edu, and the technical origin that supports them. That layer has been stable for years and is maintained jointly by Web Services and UAMS IT. Nothing about it changes.
The second layer is new in 2026. AI Wayfinding sits on top of the routing architecture, providing the signage that helps visitors (human and machine) get where they need to go. If the routing architecture is the building, this is the hallway directory and the color-coded floor lines.
Both layers are owned by Web Services within the Office of Communications and Marketing. The work is not speculative, not experimental, and does not disrupt existing SEO or accessibility investments. It reinforces them.
See also
Other pages and posts in the AI Wayfinding series.
AI Wayfinding at UAMS (hub)
The main landing page for AI Wayfinding at UAMS, with links to everything in one place.
Visit the hub
Inside the file triad: a technical deep-dive
A longer narrative walkthrough of how the three files work together, with examples from UAMS properties.
Read the technical deep-dive
An introduction
A short introduction to AI Wayfinding for UAMS staff and content editors.
Read the staff intro