How do you automate accessibility (WCAG) testing with AI?
Every QA.tech test run automatically checks for WCAG accessibility issues and logs them alongside functional findings – so accessibility coverage happens as a byproduct of testing you already do, with no separate tool or configuration.
Sub-use-cases
Covers Continuous WCAG checks on every run, accessibility issue triage, export of findings to the backlog and web accessibility coverage across key flows.
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What gets checked against WCAG
Common WCAG issues surfaced during real interaction: missing labels, structure and navigation problems, and other barriers a user would hit. Scope to be aware of: the automatic scanner does not check colour contrast, does not scan content inside iframes, and reports up to 10 accessibility issues per test session.
- 02
How does AI flag accessibility issues?
As the agent interacts with each screen, it detects WCAG issues and records them as minor findings in the same interface as functional issues; they can be sent straight to Jira or Linear.
- 03
When accessibility checks run
Continuously – accessibility regresses quietly between dedicated audits, so checking on every run keeps it from drifting. Include it in your regression test plan so coverage compounds release over release. Relevant for European Accessibility Act readiness.
- 04
Who needs automated accessibility testing
Teams with compliance requirements and anyone wanting accessibility coverage without a separate tool or process.
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How QA.tech helps
Accessibility is usually an afterthought because it needs dedicated effort. QA.tech makes it a default, so issues are caught early and routed to the backlog automatically.
FAQ
Common questions
- Is automated accessibility testing enough for WCAG compliance?
- QA.tech catches many WCAG issues continuously, but the automatic scanner does not cover colour contrast or content inside iframes and caps at 10 issues per session, so a formal audit is still needed for certification.
- Do I need to configure the checks?
- No – they run automatically on every test.
- How are accessibility issues reported?
- As minor findings you can review and export to Jira or Linear.
Related use cases
Account & Profile Settings Testing
An AI agent runs every settings action a user can take – update profile fields, change email and password, upload an avatar, toggle preferences – then verifies the changes persist after a refresh. Settings pages look simple but touch storage, auth and email, so they regress quietly.
ReadAuthentication & Login Flow Testing
An AI agent runs your real login journeys – including the parts traditional tools can't, like opening an email or reading an SMS code – and verifies the user ends up authenticated. QA.tech gives the agent its own inbox and phone number, so magic links, one-time passwords and confirmation emails are tested end to end, not mocked.
ReadBulk Actions Testing
An AI agent selects multiple items, triggers a bulk action – delete, export, status change – and verifies the outcome across the selection. Bulk operations are high-stakes and usually tested by hand, infrequently.
Read
Authentication & Login Flow Testing
Next →Automated Regression Testing
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