How Universities Can Prepare PDFs for Accessibility Review

A mid-sized university with 10,000 to 20,000 students might maintain 5,000 to 15,000 active PDFs across its websites. A large public research university with multiple campuses could have 30,000 or more. These documents span nearly every function of the institution – admissions packets, financial aid worksheets, course catalogs, syllabi, degree audits, housing contracts, dining guides, employee handbooks, research reports, event brochures, policy updates, and advancement newsletters. Here is what makes this especially hard: most of these PDFs are created independently by staff with no accessibility training. The admissions office exports forms from InDesign. Academic departments export Word documents with a single click. The registrar exports database reports directly. Each department picks its own tools and its own workflow. The result is predictable. Many of these PDFs lack proper tagging, have unreadable scanned text, use images without descriptions, or fail to define a logical reading order. When an external accessibility review arrives, the institution is caught off guard by the volume of issues. That surprise leads to rushed vendor contracts and emergency spending.

Not every PDF demands the same urgency. Smart prioritization starts with separating high-risk documents from the long tail of lower-priority files. Think about it in four dimensions. Public-facing versus internal. A PDF on your public admissions website is far riskier than a file on a staff-only SharePoint site. If a prospective student can find it through a Google search, it should be accessible. Required for enrollment versus optional. A financial aid award letter is not optional – a student needs it to make enrollment decisions. An event flyer for a guest lecture is lower stakes. Required documents that students must read, sign, or submit should top your list. Student-facing versus staff-only. Documents used by students carry higher obligation than administrative files used by employees. A course registration tutorial, a housing contract, or a disability services accommodation letter all fall into this category. Legally sensitive versus general information. Documents related to financial aid, legal rights, disciplinary procedures, health services, or accommodation requests sit in a higher-risk zone. So do documents tied to federal compliance programs. A mis-tagged loan disclosure or an inaccessible conduct code is a direct path to an OCR complaint. Concrete example: A financial aid verification worksheet – posted publicly, required for enrollment, used by students, and tied to federal aid regulations – scores high across every dimension. An internal landscaping committee agenda scores low. Start with the financial aid worksheet.

You cannot protect what you have not counted. The first step is building a practical inventory of PDFs across your institution. Do not aim for perfection. Aim for coverage. Approach by department. Send a request to each department asking for a list of PDFs they maintain on their websites and in shared drives, with URLs when possible. This surfaces documents that no automated crawl will find – especially PDFs in password-protected portals or learning management systems. Use a web crawler. Tools like Screaming Frog or Sitebulb can crawl your main university website and extract every PDF URL. This gives you an objective count of public-facing files. Export results into a spreadsheet with columns for URL, department, document type, and estimated traffic. Flag the high-traffic files. Use web analytics to identify which PDFs get the most downloads. The course catalog page with 10,000 views per semester matters more than a workshop PDF that had twelve downloads. A reasonable goal: a spreadsheet of every public-facing PDF, sorted by department, with a rough traffic estimate and a risk category. This becomes your working document for everything that follows.

Once you have an inventory, the next step is understanding what is actually wrong with your PDFs. An automated PDF accessibility scan gives you that baseline quickly and affordably. An automated scan checks for structural and technical issues detectable by software: missing document tags, absent reading order, images without alt text, tables lacking headers, form fields without labels, insufficient contrast, and security settings that block assistive technology. Across a large university catalog, this surfaces patterns you would never catch by opening files one at a time. For example, you might discover that 80 percent of your PDFs lack proper tags because your campus default export settings do not generate them. Or that every financial aid form has the same missing language attribute. These patterns tell you where to focus training and which workflows to fix. What an automated scan does not do is replace human judgment. It cannot tell you whether a heading structure makes semantic sense or whether alt text descriptions are meaningful. It does not certify WCAG 2.1 AA compliance or guarantee that a PDF will pass an external audit. What it does is show you where the problems are and how widespread they are. That knowledge alone puts you ahead of most institutions. Think of it as a pre-audit report – an internal risk review that prepares you for the real thing. When you run an automated scan across your university's PDF catalog, you move from "we probably have issues" to "we have 340 untagged documents in admissions and 90 percent of our financial aid forms lack proper form labels." That specificity changes everything.

Armed with scan data and your risk categories, you can now build a realistic priority list. The formula is straightforward: multiply legal exposure by student impact by document volume. Documents that score high on all three go first. Wave 1: High-traffic public documents required for enrollment. This includes course catalogs, application packets, financial aid forms, and housing contracts. These are the documents every student touches and that would be the first targets of any complaint. Fix these first or have them professionally remediated. Wave 2: Student-facing documents tied to services. Disability services forms, health insurance summaries, billing statements, academic policy handbooks. These are not always high-traffic, but they directly affect students who may already need accommodations. Wave 3: Administrative and internal documents. Employee handbooks, committee reports, training materials. These still matter under employment accessibility law, but are lower risk than student-facing content. Wave 4: Archival and historical documents. Old research reports, past event materials, legacy newsletters. In many cases, these can be made available upon request rather than proactively remediated. Some universities add a disclaimer for archived PDFs that have not yet been reviewed. This staged approach prevents the paralysis of trying to fix everything at once. It also lets you show progress. If an auditor asks what you are doing, pointing to a completed wave with documentation carries far more weight than saying "we are working on it."

At some point, automated detection stops being enough. Complex forms, tagged tables, and meaningful alt text all require human judgment. That means either training internal staff or hiring a remediation vendor. This is where your pre-audit report becomes a procurement asset. Instead of sending a vendor a vague request to "make our PDFs accessible," you can provide a complete inventory sorted by priority, scan results showing issue types and severity per document, a defined scope of work, and clear acceptance criteria. Vendors price remediation based on time and complexity. When you hand them detailed scan data, they can quote accurately. When you show up with nothing, they either overcharge to cover uncertainty or underbid and surprise you later with change orders. One accessibility coordinator told us that having scan data before contacting vendors cut her initial quotes by nearly 30 percent. You can also assign simpler fixes internally. Issues like adding document titles, setting the primary language, or adding basic alt text can be handled by trained staff using Adobe Acrobat Pro. Reserve vendors for complex documents where expertise matters.

An external accessibility review typically works by sampling. Auditors select a representative set – often focusing on high-traffic pages, enrollment-related content, and student services documents. They test those samples against WCAG 2.1 AA criteria using a combination of automated tools and manual inspection. Here is where preparation pays off. If you have already run automated scans, categorized your documents, and begun remediation on your highest-risk PDFs, you walk into that review with context. You know which issues exist and which ones you have fixed. You can speak specifically about your process rather than reacting defensively. Auditors notice preparedness. An institution that can produce a scan report and remediation timeline looks different from one discovering its own PDFs during the review. The former signals commitment. The latter signals neglect. An external review does not certify you as "compliant forever." It does not check every document. And it does not provide remediation – it identifies issues. The actual fixing still falls to you or your vendor. Having scan data ready means you are not starting from zero when the review concludes. The strategic advantage is simple: know your issues before they do. An automated PDF accessibility scan gives you that visibility. It is a preparedness tool – one that helps universities face accessibility reviews with confidence and a clear plan.