European Accessibility Act: automating web accessibility audits with n8n and AI

Since June 28, 2025, the European Accessibility Act (EAA) has changed the picture: digital accessibility is no longer a public-sector-only constraint — it now applies to private companies too, once they cross 10 employees or €2 million in annual revenue, with e-commerce, online banking, ticketing, and on-demand audiovisual services front and center. Penalties can reach €50,000 per non-compliant service, and sites already live before June 2025 only have until June 28, 2030 to catch up. Many SMEs find out about the obligation too late, for lack of regular monitoring. This guide shows how to build an n8n pipeline that scans your pages, isolates the most critical WCAG failures, prioritizes them with AI, and feeds a real audit trail — without hiring a full-time accessibility expert for routine monitoring.

What the EAA actually changes for an SME

Three things worth separating before building anything:

• The scope. The EAA transposes an EU directive (2019/882) into French law and covers consumer-facing digital services: e-commerce sites, banking apps, transport ticketing, on-demand audiovisual content. Micro-enterprises (fewer than 10 employees AND under €2M revenue) are exempt; everyone else is covered, including SMEs that never expected an obligation historically limited to government agencies.
• The reference standard. Compliance is demonstrated through the European standard EN 301 549, which for the web portion maps onto RGAA 4.1.2 in France, itself aligned with WCAG 2.1 level AA. Concretely: sufficient color contrast, text alternatives on images, full keyboard navigation, a coherent heading structure, and properly labeled forms.
• The timeline. Any service launched after June 28, 2025 must be compliant immediately. Services already live before that date get a transition period until June 28, 2030 — a comfortable-looking window, but one that only means something if a compliance plan is actually progressing along the way.

Why automate detection instead of auditing once a year

A full manual RGAA audit by an expert is expensive and typically happens once a year — nowhere near enough for a site that publishes content continuously (product pages, blog posts, new landing pages). Between two audits, dozens of pages can introduce new regressions: an image added by a teammate without an alt attribute, text/background contrast broken by a theme update, a redesigned form with no associated label. An n8n pipeline that scans your pages regularly doesn't replace a human audit, but it fills the gap between two audits and catches regressions before an inspection — or a user — finds them first. It's the same logic already covered for detecting SEO content decay: monitor continuously instead of finding out after the fact.

Building the audit pipeline in n8n

1. List the pages to audit

An HTTP Request node fetches your sitemap.xml, and an XML node converts it into a usable list of URLs (see our n8n XML node guide). On a large site, filter first on your highest-traffic or most sensitive templates (checkout flow, contact forms, category pages) rather than aiming for full coverage on the first pass.

2. Run the scan with the PageSpeed Insights API

axe-core, the engine behind Lighthouse's accessibility audit, is available for free through Google's PageSpeed Insights API — no need to host a headless browser for this first layer of scanning. A looped HTTP Request node (via Split In Batches, with a short delay between calls to stay within quota) queries:

GET https://www.googleapis.com/pagespeedonline/v5/runPagespeed
    ?url=https://your-site.com/page
    &category=accessibility
    &key=YOUR_API_KEY

The response includes lighthouseResult.categories.accessibility.score (0 to 1) and the detail of every check under lighthouseResult.audits, each tagged with a technical ID (image-alt, color-contrast, label, link-name…).

3. Prioritize failures with AI

A Code node filters audits scoring below 1 in the accessibility category, then an AI Agent node translates each technical ID into a plain-language, actionable explanation, ranked by severity and mapped to the matching RGAA/WCAG criterion — similar to the pattern already described for scoring support tickets with AI, applied here to Lighthouse reports instead of customer requests. This step turns a JSON blob that's unreadable to a non-specialist into a fix list a product team or an external agency can actually act on.

4. Log every audit run

Each execution writes to a Supabase table the score per page, the list of failed criteria, and the timestamp — the exact same principle as the GDPR audit trail with n8n and Supabase, applied here to accessibility instead of personal data processing. That table becomes dated proof of active monitoring, useful in the event of an inspection and for tracking real progress toward the 2030 deadline.

5. Alert and create a backlog

A Slack or Gmail node sends a weekly summary of pages under a defined threshold (for instance, an accessibility score below 0.9), and a dedicated node automatically pushes a task into your tracking tool for each detected regression — see our connection guides for Linear or Notion depending on your stack. As with any repeated API call inside a loop, plan for delays and transient errors: our guide on HTTP Request retries and timeouts applies directly here.

Why automation doesn't replace a human review

A study by Markel Vigo, Justin Brown, and Vivienne Conway, published in 2013 in the proceedings of the W4A conference ("Benchmarking web accessibility evaluation tools: measuring the harm of sole reliance on automated tests"), compared six automated scanning tools on their coverage, completeness, and correctness against WCAG 2.0 criteria: none of them covers more than a fraction of the criteria that are actually testable, and relying on them exclusively can create a false sense of compliance — particularly on criteria that require human judgment, such as whether alt text is genuinely meaningful, whether a keyboard journey is coherent, or whether an error message is actually clear. The pipeline described here is built for continuous monitoring and prioritization, not for generating a full RGAA compliance declaration on its own — that still requires a human audit on a representative sample of pages, complemented by this kind of automated monitoring between audits.

Common pitfalls

• Confusing a high PageSpeed score with full RGAA compliance. A perfect score on Lighthouse's accessibility audit means the absence of errors an automated tool can catch — not full RGAA compliance, which includes criteria no tool can test automatically.
• Scanning only the homepage. Checkout flows, forms, and login pages usually concentrate the most failures and are the journeys most scrutinized under the EAA.
• Letting the backlog fill up with no prioritization. Without ranking by severity and by the traffic volume of the affected page, an accessibility audit quickly generates dozens of tickets to work through in no particular order.
• Waiting until 2030 to start. The transition period only means something if compliance work actually progresses every quarter; an inspection or a complaint can happen well before the deadline.

Wrapping up

The European Accessibility Act sharply widens the range of companies subject to digital accessibility obligations, with real penalties and a transition window that shrinks every month for sites already live. n8n lets you build, in a handful of nodes, a continuous monitoring pipeline — scanning through the PageSpeed Insights API, AI-driven prioritization, Supabase logging, and automatic alerts — that fills the gap between human audits without pretending to replace them. If your immediate priority is precisely tracking and logging this kind of monitoring reliably and demonstrably in the event of an inspection, the Compliance & Audit Pack (€149) already ships a timestamped audit-trail SQL schema and the related follow-up workflows — directly reusable for the logging portion of this accessibility audit pipeline. For full coverage of your compliance and AI automation workflows, the Complete FlowKit Bundle (€269) combines this pack with the Inbox AI Pack (€79) and the RAG Assistant Pack (€119).