Part three of our four-part series on accessibility.
In the first two parts of this series, we explored how accessibility shows up in real working environments and how cognitive load affects the way users interact with digital interfaces. Designing inclusive experiences requires attention to many details, from visual clarity to information structure.
As AI rapidly becomes part of everyday workflows, it also creates new opportunities to support accessibility throughout the design process. AI is already helping teams draft content, review designs, and explore ideas faster. When used intentionally, it can also help identify accessibility gaps earlier and encourage more inclusive thinking during design and development.
Where Accessibility Work Often Slows Down
Accessibility improvements tend to get overlooked in fast-paced projects. Teams are balancing tight timelines, complex requirements, and multiple stakeholders. As a result, accessibility reviews sometimes occur late in the process or rely heavily on manual checks.
Some common challenges include:
- Missing or incomplete alt text for images and icons
- Low contrast color combinations that reduce readability
- Dense or unclear instructions that increase cognitive effort
- Inconsistent labels across screens that make navigation harder
- Accessibility reviews happening too late in the design cycle
These issues rarely happen intentionally. They often appear when teams are moving quickly and juggling many details.
Using AI to Support Inclusive Design
AI can serve as a helpful assistant during design and content workflows. It can’t fully replace accessibility expertise, but it can help teams spot potential issues earlier and reduce manual effort.
AI can support accessibility in design by:
- Generating draft alt text for images, then refining it with context and intent
- Simplifying complex instructions or microcopy to improve clarity
- Reviewing labels and form fields to identify ambiguous language
- Exploring edge cases by prompting AI to describe how different users might experience an interface
- Evaluating clarity by asking AI to interpret content as if the user is distracted or multitasking
To support inclusive design, teams can use AI with targeted prompts that guide reviews and surface potential issues:
- Alt text and image context: “Generate alt text for this image. Ensure the description is concise, accurate, and reflects the purpose of the image within this interface. Identify any missing context.”
- Clarity and readability: “Review this content for clarity. Identify any instructions or messaging that may be too dense or difficult to scan. Suggest simpler alternatives while preserving meaning.”
- Form labels and inputs: “Review these field labels and instructions for clarity. Could a distracted user understand what information is required and how to complete this form? Identify confusing language and suggest improvements so all users can complete the form confidently.”
- Edge-case user scenarios: “Describe how a user in a high-pressure, distracting, or fast-paced environment might interact with this interface. Identify where potential confusion or errors could occur.”
- Cognitive load and flow: “Analyze this interface for cognitive load. Identify where users may need to pause, re-read, or interpret information. Suggest ways to reduce mental effort through structure and hierarchy.”
The most effective approach to this treats AI as a second set of eyes, not the final approval. It can draft, review, and question design decisions, but human judgment is still needed to make sure the final experience is thoughtful and accurate.
Strengthening Accessibility Through Better Tools
When used thoughtfully, AI can help teams integrate accessibility into everyday workflows instead of treating it as a separate review step.
This can help teams:
- Identify potential accessibility issues sooner
- Reduce manual review time during design and content creation
- Encourage inclusive thinking during ideation and prototyping phases
- Maintain more consistent patterns across complex interfaces
AI won’t replace accessibility expertise, but it can support the work by helping teams move faster while maintaining attention to detail.
In the final post in this series, we explore what accessibility may look like in an AI-driven world and how strong structure and clarity support both human users and intelligent systems.