Note: The creation of this article on testing Keyboard (No Exception) was human-based, with the assistance on artificial intelligence.
Explanation of the success criteria
WCAG 2.1.3 Keyboard (No Exception) is a Level AAA conformance level Success Criterion. It ensures that all content is operable from the keyboard. This Success Criterion raises the bar for accessibility by requiring that all functionality of a digital experience be operable through a keyboard, with absolutely no exceptions. Unlike WCAG SC 2.1.1, which allows alternatives when keyboard access is not feasible, this criterion removes any allowances, ensuring that every feature, no matter how complex, must be fully navigable without reliance on a mouse or other pointing device.
Consider a web application that includes a custom drawing tool. Under SC 2.1.1, the developer might argue that this feature inherently requires a mouse. SC 2.1.3, however, challenges that assumption, pushing teams to design keyboard-accessible alternatives, such as arrow key movements, shortcut commands, or form-based inputs that replicate the same functionality. Similarly, a complex video game or interactive simulation cannot dismiss keyboard accessibility as optional; it must provide keyboard operability alongside mouse or touch controls.
What this criterion demonstrates is a philosophical shift: accessibility is not about doing the minimum, it’s about ensuring that no user is locked out of essential functionality. By embedding this mindset, organizations not only meet compliance but also cultivate innovation, designing flexible interaction models that benefit every user. The result is a digital ecosystem that values inclusion as a driver of creativity and progress, rather than as a constraint.
Note that this Success Criterion is at a conformance level of AAA. This means that this Success Criterion is generally considered aspirational, going beyond the standard A & AA conformance levels. It addresses more specific accessibility needs and is not mandatory for all websites or content. However, achieving Level AAA can provide additional benefits in terms of inclusivity.
Who does this benefit?
- people with motor disabilities
- people using screen readers
- power users who prefer faster, keyboard-driven navigation
Testing via Automated testing
Automated testing offers speed and scalability, quickly scanning large volumes of content for code-level issues that may indicate a potential keyboard trap.
However, automation is inherently limited; it cannot fully simulate user interaction or reliably confirm whether a trap exists, making its findings more suggestive than definitive.
Testing via Artificial Intelligence (AI)
AI-based testing pushes the boundaries further by applying pattern recognition and predictive models to flag likely problem areas that automation might miss.
While this introduces a degree of nuance, AI remains imperfect, it still struggles with contextual understanding and can generate false positives or overlook complex interaction flows.
Testing via Manual testing
Manual testing, on the other hand, delivers the most accurate and trustworthy results because it directly measures the real user experience. By navigating solely with a keyboard, testers can confirm whether users encounter traps and validate compliance in ways no algorithm can.
The drawback, of course, is time and resource intensity; thorough manual testing requires expertise and focus, making it less scalable than automated or AI approaches.
Which approach is best?
No single approach for testing Keyboard (No Exceptions) is perfect. However, using the strengths of each approach in combination can have a positive effect.
Begin with automated testing, which efficiently identifies low-hanging issues such as elements missing tabindex or interactive controls that cannot receive focus. These quick wins reduce manual burden and establish a baseline of compliance.
Next, AI-based testing is introduced to simulate more complex user behaviors, such as navigating interactive widgets, modal dialogs, or dynamic menus. AI can highlight patterns of potential keyboard inoperability that automation alone would miss, especially when dealing with custom JavaScript components.
However, these insights must be validated through manual testing, where skilled accessibility professionals confirm not just technical operability, but also usability, ensuring tab order follows a logical path, focus indicators remain visible, and all interactions are truly achievable without a mouse.
This layered approach creates a virtuous cycle: automation for speed, AI for scale and predictive detection, and manual testing for depth and assurance. By integrating these methods strategically, organizations can balance efficiency with thoroughness, ensuring both compliance and meaningful accessibility outcomes.