Why Accessibility Tools That Only Scan Are Failing Universities

You've seen the pitch: "Our accessibility tool scans your content and identifies WCAG violations."

Sounds helpful. And it is—to a point.

But here's what universities are discovering: Scanning tools that only identify problems without fixing them are failing to move the needle on compliance.

Let's examine why, and what actually works.

The Scan-Only Model

How It Works

Traditional accessibility tools follow this workflow:

1. Scan: Crawl content (web pages, documents, videos)
2. Report: Generate list of violations with severity ratings
3. Dashboard: Show compliance scores and trends
4. Stop: Hand off to humans for remediation

The Value Proposition

"We'll tell you everything that's wrong. You fix it."

This sounds reasonable. After all, you can't fix what you don't know about.

The Problem

Here's what actually happens:

1. Scan: Tool identifies 10,000 issues across your LMS
2. Report: "You have 10,000 accessibility violations"
3. Reaction: Panic, overwhelm, paralysis
4. Reality: Faculty don't have time to fix 10,000 issues manually
5. Result: Report sits in a drawer, compliance doesn't improve

The tool did its job (scanning). But compliance didn't improve.

Why Scan-Only Fails in Higher Education

1. The Labor Gap

The math is brutal:

• Average university: 10,000-50,000 files to remediate
• Manual fix time: 15-60 minutes per file
• Total labor: 2,500-50,000 hours

Who does this work?

Option	Problem
Faculty	No time, no compensation, no training
IT staff	Already overworked, wrong skill set
Grad students	Turnover, inconsistent quality
Contractors	Expensive, temporary

Scan-only tools assume unlimited labor exists. It doesn't.

2. The Expertise Gap

Knowing there's a problem isn't the same as knowing how to fix it.

Example violation: "PDF lacks proper structure tags"

What faculty hears: "???"

What's actually needed:

• Export to Word
• Apply heading styles
• Mark lists and tables
• Generate accessible PDF
• Verify reading order
• Add alt text
• Re-upload to LMS

That's 30-60 minutes of specialized work for someone who doesn't know what "structure tags" means.

Scan-only tools assume expertise exists. It doesn't.

3. The Motivation Gap

Faculty are measured on:

• Research output
• Teaching evaluations
• Grant funding
• Service commitments

Faculty are NOT measured on:

• Accessibility compliance scores
• Time spent remediating PDFs

When a scan report says "Your course has 147 accessibility issues," the rational faculty response is: "That's IT's problem" or "I don't have time for this."

Scan-only tools assume motivation exists. It's structurally absent.

4. The Scale Gap

Accessibility isn't a one-time project. New content is created constantly.

Scan-only workflow:

• Scan in January → 10,000 issues
• Work all semester → fix 2,000 issues
• Scan in May → 12,000 issues (new content added)
• Net progress: Negative

You can't out-work the content creation rate with manual remediation.

5. The Specificity Gap

Scan reports give general categories:

• "147 images missing alt text"
• "89 PDFs have accessibility issues"
• "34 videos need captions"

They don't give:

• Which specific images
• What the alt text should say
• Where in the document the issue is
• How to fix it step-by-step

Going from "147 images need alt text" to actually writing 147 alt texts is a huge gap that scan-only tools don't bridge.

What Actually Works: Scan + Fix

The Scan-and-Fix Model

Modern accessibility tools do more than report:

1. Scan: Identify issues (same as before)
2. Analyze: Determine what kind of fix is needed
3. Generate: AI creates proposed fixes
4. Apply: One-click remediation where possible
5. Review: Human approves or adjusts
6. Monitor: Ongoing scanning catches new issues

Why This Works

Addresses the labor gap:

• AI does 80% of the work
• Humans do 20% (review and edge cases)
• 10,000 hours becomes 2,000 hours

Addresses the expertise gap:

• Tool knows how to fix issues
• Faculty just approve or reject
• No accessibility expertise required

Addresses the motivation gap:

• Instead of "fix 147 issues"
• It's "approve these 147 AI-generated alt texts"
• 30 seconds per item vs. 3 minutes per item

Addresses the scale gap:

• New content scanned automatically
• Fixes generated immediately
• Compliance maintained, not achieved once and lost

Addresses the specificity gap:

• "This image needs alt text" becomes "Here's the alt text we suggest: [description]"
• Review workflow, not creation workflow

Case Study: Same University, Different Tools

Scenario: Mid-size university, 15,000 PDFs to remediate

With Scan-Only Tool:

• Tool cost: $50,000/year
• Scan result: 12,000 PDFs have issues
• Faculty remediation: 8,000 hours needed
• Actual remediation: 500 hours available
• After 1 year: 500 PDFs fixed, 11,500 remain
• Compliance improvement: 4%

With Scan-and-Fix Tool:

• Tool cost: $120,000/year (higher, because it does more)
• Scan result: 12,000 PDFs have issues
• AI remediation: 10,000 PDFs auto-fixed
• Human review: 800 hours (review, not create)
• Manual fixes: 2,000 PDFs need human work
• After 1 year: 10,000 fixed, 2,000 remain
• Compliance improvement: 83%

The scan-and-fix tool costs 2.4x more but delivers 20x the improvement.

The Real Cost Comparison

Scan-Only Economics

Item	Cost
Tool license	$30,000-100,000/year
Remediation labor	$500,000-2,000,000
Total	$530,000-2,100,000

Scan-and-Fix Economics

Item	Cost
Tool license	$60,000-150,000/year
Review labor	$50,000-200,000
Total	$110,000-350,000

Scan-and-fix is 3-6x cheaper when you account for the labor to actually achieve compliance.

Evaluating Tools: Questions to Ask

About Scanning

1. What file types can you scan? (PDFs, PPTs, videos, web pages?)
2. What WCAG criteria do you check?
3. Can you scan content inside our LMS?
4. How often can we re-scan?

About Fixing (The Critical Questions)

1. Do you generate fixes, or just identify issues?
2. What percentage of issues can be auto-fixed?
3. What does the review workflow look like?
4. Can fixes be applied without downloading/re-uploading files?

About Integration

1. Does the tool integrate with Canvas/Blackboard/Moodle?
2. Can faculty see and approve fixes in-context?
3. Is there API access for custom workflows?

Red Flags

• "We provide detailed reports" (but no fixes)
• "Our dashboard shows your compliance score" (but doesn't improve it)
• "Faculty can use our reports to prioritize remediation" (assumes labor exists)
• "We identify issues so you know what to fix" (scan-only positioning)

What Aelira Does Differently

Scan

• All document types (PDF, PPTX, DOCX, XLSX, LaTeX)
• Web pages and LMS content
• Video captions
• Image alt text quality (not just existence)

Fix

• PDF: AI generates structure tags, reading order, alt text
• PowerPoint: Auto-fix contrast, generate alt text
• LaTeX: Convert to accessible MathML with natural language descriptions
• Video: AI caption cleanup (accuracy, timing, speaker ID)
• Images: Context-aware alt text generation

Review

• Faculty see suggested fixes in their workflow
• One-click approve or edit
• Batch approve for similar items
• Audit trail for compliance documentation

Monitor

• New uploads scanned automatically
• Fixes generated before issues compound
• Compliance maintained, not just achieved

The Bottom Line

Scan-only tools answer the question: "What's wrong?"

That's necessary, but not sufficient.

Scan-and-fix tools answer the question: "How do we make it right?"

That's what actually achieves compliance.

The universities succeeding with accessibility aren't the ones with the best scan reports. They're the ones whose tools do the work, not just report on it.

If your current tool only scans, you're paying for a problem list. You need a solution list.

See how Aelira scans AND fixes | Request a demo