AccessLumens

WCAG 1.1.1

Non-text Content

SeriousLevel AWCAG 2.0Common in US litigationEAA enforcement-relevant

32%

of the 609 sites we scanned fail this

Ranging from 21.5% of US local government to 61.3% of Shopify DTC stores. Pooled across five targeted cohorts, so treat it as a convenience sample rather than a rate for the web.

Separately, 49.9% of the 941 county government PDFs we scanned fail it (470 documents). That is a different population from the sites above, so the two figures are not comparable. How we scanned the PDFs

What it means and how to fix it

What 1.1.1 covers

  • We detect this: Images with no alt attribute at all
  • Partly detected: Icon fonts, SVGs and CSS background images that carry meaningAn SVG exposed as an image with no name is detected. A meaningful CSS background image is invisible to any engine, because nothing distinguishes it from decoration.
  • No engine can detect this: Alt text that exists but does not describe the imagealt="image" passes every automated check ever written. Judging whether alt text conveys what the image conveys means seeing both.
  • No engine can detect this: Decorative images that should have been hidden insteadWhether an image is decorative is an authorial decision, not a property of the markup.

Of that, 4 failures are detectable automatically, and these are what the rates on this page measure. Each needs its own fix. The percentage is the share of all 609 scanned sites affected. These do not sum to the 32% above: a site can fail more than one of them, and most that fail any fail several. A further 1 failure was detected on fewer than five sites each and are not listed.

  • Images are missing descriptions for screen readers26.6%

    Users who cannot see images may miss critical information or functionality conveyed visually.

  • An SVG used as an image has no text alternative4.8%

    Whatever the graphic conveys is unavailable to anyone who can't see it.

  • An element marked as an image has no text alternative1.3%

    It's announced as an image with no indication of what it shows.

  • A progress bar has no accessible name1%

    The progress value is announced with no indication of what is progressing.

What it looks like in code

HTML
Fails
<img src="image.jpg">
Passes
<img src="chart.png" alt="Sales rose 40% between January and June">

<!-- Decorative image: empty alt, so it is skipped rather than announced -->
<img src="divider.png" alt="">

Every <img> needs an alt attribute. Describe what the image conveys, not that it is an image. Use alt="" for purely decorative images so they are skipped.

Shown for Images are missing descriptions for screen readers. The failing example is real markup from a site in our research cohorts. Class, style and data attributes are removed, and ... marks a value we elided. The structure is unchanged, because the structure is the failure.

For what the criterion formally requires, read the W3C Understanding document.

How often it fails

Shopify DTC stores46/75
61.3%
Indian financial services21/61
34.4%
EU e-commerce32/107
29.9%
US healthcare providers62/208
29.8%
US local government34/158
21.5%

Share of scanned sites in each cohort. These are five targeted studies, not a random sample of the web, so read the contrast between cohorts rather than any one figure as a web-wide rate.

Who fails it most3 cuts by state, sector, country

By state

MO5/8
62.5%
KS5/10
50%
NY3/8
37.5%
CA6/25
24%
LA2/9
22.2%
FL3/15
20%
TX2/13
15.4%
OH1/8
12.5%

By sector

Grocery5/12
41.7%
Banking7/19
36.8%
Travel / Ticketing5/14
35.7%
Retail / Marketplace4/12
33.3%
Telecom6/21
28.6%
Fashion0/8
0%

By country

Germany9/19
47.4%
Poland4/11
36.4%
Spain4/11
36.4%
Italy4/12
33.3%
Ireland3/12
25%
France3/12
25%
Netherlands3/15
20%
Sweden2/15
13.3%

Groups smaller than 8 sites are not shown: a rate over a handful of sites moves by tens of points on a single result.

What the numbers do not say

Missing alternative text is the criterion people expect to dominate, and on web pages it does not: it is beaten by name, role and value. Alt text is well understood and widely tooled. The picture inverts in documents, where it fails on roughly half the county PDFs we scanned, because nothing in a normal PDF export prompts anyone to supply it.

What this does not measureLimits of these figures, and where the corpus came from
  • These are five targeted cohorts, not a random sample of the web. Per-cohort rates are the figure to quote; the pooled rate is a convenience sample.
  • Denominators count sites that produced a result. Sites that were blocked or errored are excluded rather than counted as passing.
  • Occurrence counts are floors: the engine records at most 25 occurrences of a rule per page.
  • The EU and Indian cohorts retained only the primary success criterion per finding, so a rule mapping to several criteria contributes to one of them in those two cohorts and to all of them in the other three.
Cohorts in the corpus, with sites scanned and attempted
CohortScannedAttempted
Shopify DTC stores7575
US local government158221
US healthcare providers208218
EU e-commerce107170
Indian financial services6172

Corpus generated 2026-09-18.

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