If you have ever tapped captions in a noisy cafe, asked your phone to read a message while your hands were full, or relied on autocorrect when you were tired, you have benefited from features born in accessibility. That is the essence of accessible technology: it starts by removing barriers for people with disabilities and ends up helping everyone.

Artificial intelligence can accelerate this ripple effect. In the last two years, AI systems have gotten far better at understanding images, speech, and context. That means alt text that actually describes what matters, captions that keep up with fast speakers, and voice interfaces that adapt to different accents or atypical speech patterns. The payoff is huge—for independence, employment, education, and everyday dignity.

There is also urgency. With the European Accessibility Act’s June 2025 applicability date, many consumer products and services in the EU must meet accessibility requirements. For a helpful overview of what is covered and what timelines apply, see the European Commission’s explainer on the EAA here. Whether you ship software in Europe or not, the direction of travel is clear: accessible by default.

What AI Can Do Today (And Where It Helps Most)

AI is not a magic wand, but it is a powerful toolbox. Here are areas where it already removes friction:

  • Image understanding: Vision models can generate alt text and scene descriptions that go beyond “A person” to “A man in a blue jacket crossing a wet street at dusk, holding a white cane.” Tools like Be My Eyes use AI plus human volunteers for context-sensitive assistance.
  • Speech to text: Live captions and transcripts support Deaf and hard-of-hearing users in meetings, classes, and videos. Google’s Live Transcribe and YouTube auto-captions have improved through AI.
  • Text to speech: Natural voices with better prosody make screen readers and voice assistants less fatiguing. VoiceOver (Apple) and TalkBack (Android) benefit from richer TTS options.
  • OCR and document cleanup: AI can recognize text in scans, preserve reading order, and tag headings—critical for accessible PDFs and forms.
  • Conversation and summarization: ChatGPT, Claude, and Gemini can simplify language, summarize long documents, and convert instructions into step-by-step checklists for cognitive accessibility.

The key is to combine these capabilities with user-centered design. AI can draft; humans and standards must guide.

Real-World Examples You Can Learn From

Accessibility improvements are not theoretical—they are shipping:

  • Be My Eyes: Its AI-powered Virtual Volunteer can describe scenes, read labels, and guide users through interfaces. The app routes tricky tasks to volunteers when AI is unsure.
  • Microsoft Seeing AI: Reads text, identifies products via barcodes, describes people and scenes, and explores photos by touch.
  • Live captions everywhere: Zoom, Google Meet, and Microsoft Teams provide live captioning; several now support speaker attribution, custom vocabulary, and multilingual captions.
  • Apple features: Personal Voice and Live Speech support users at risk of losing speech; Voice Control enables full device control via voice; VoiceOver image descriptions have improved via on-device intelligence.
  • Workplace assistive workflows: A helpdesk bot can draft clear, plain-language steps based on a company’s knowledge base; a sales tool can generate accessible product descriptions with proper alt text and ARIA labels for web teams.

Each example pairs AI with clear intent: reduce cognitive load, provide alternative modalities, and respect user privacy and control.

Design Principles: Build In, Not Bolt On

Accessibility is easiest when it is structural, not decorative. Use these principles:

  • Follow WCAG: The Web Content Accessibility Guidelines are still your best baseline for perceivable, operable, understandable, and robust content. AI can help you meet WCAG, but it does not replace it.
  • Prefer multiple modalities: Offer text, audio, and visual affordances. For example, provide captions plus a transcript download, and pair AI-generated alt text with a manual review.
  • Maintain keyboard-first navigation: Ensure every interactive control is reachable without a mouse. AI-generated UIs must inherit proper focus order and visible focus styles.
  • Label everything: Inputs, buttons, and images need programmatic labels. Use ARIA thoughtfully; do not make AI guess. Ensure AI-authored components include proper roles and labels.
  • Keep language simple: Offer text in plain language; use headings, lists, and summaries. AI can create a simplified version alongside the full version.
  • Respect privacy: For accessibility data (like voice profiles or personal prompts), prefer on-device processing or explicit consent and retention controls.

A quick analogy

Think of accessibility like sidewalks and ramps. AI is the snowplow that clears them faster after a storm—but the sidewalks and ramps still have to be built correctly.

Using ChatGPT, Claude, and Gemini for Accessible Content

These general-purpose models can be great co-pilots if you prompt them with accessibility in mind:

  • Ask for alt text with intent: “Generate concise alt text (under 150 characters) that conveys the key action and context for a screen reader user: [image description]. Avoid redundant phrases like ‘image of’.”
  • Demand structure: “Rewrite this onboarding guide in plain language at a 7th-grade reading level. Keep headings, numbered steps, and include a short summary.”
  • Inclusive outputs: “Provide screen reader-friendly HTML for this component with ARIA roles, labels, keyboard interactions, and a visible focus state. Include a short test checklist.”
  • Caption polish: “From this transcript, produce captions chunked at natural pauses, with speaker labels, sound cues in brackets, and line lengths under 42 characters.”

All three—ChatGPT, Claude, and Gemini—can follow these patterns. For sensitive content (like medical or HR communications), add instructions about privacy, tone, and bias mitigation. Then, verify the output with assistive tech and automated linters.

Evaluation: Test With People, Tools, and Real Environments

No model output should ship unchecked. Layer your evaluation:

  • Automated checks: Run axe, Lighthouse, or WAVE on your pages. For PDFs, check tags, reading order, and contrast.
  • Assistive technology testing: Use VoiceOver, TalkBack, NVDA, or JAWS to navigate the exact flows users will follow. Confirm the focus order, labels, and announcement timing.
  • Edge cases: Test low bandwidth, high motion sensitivity (reduce motion), and color vision deficiency simulators. Verify captions under fast speech and overlapping speakers.
  • Human review: Involve people with disabilities early and often—paid, respectful, and iterative. AI-generated descriptions can unintentionally hallucinate; human validation protects dignity and accuracy.
  • Governance: Align with your organization’s accessibility policy, and document the model, prompts, reviewers, and sign-offs for each release.

Tip: Track an “a11y budget” like a performance budget. If an AI feature adds complexity or cognitive load, that is a regression.

Policy and Risk: Avoid New Barriers While Removing Old Ones

AI can create barriers if left unchecked:

  • Hallucinations: An image description that guesses the wrong medication or misidentifies a hazard can harm. Fail safely: “Unclear” is better than wrong.
  • Bias in voice and vision: Models may underperform for certain accents, dialects, skin tones, or assistive device appearances. Curate diverse training and test sets.
  • Privacy and consent: Voice profiles, disability-related prompts, and screen captures are sensitive. Default to opt-in, minimize retention, and disclose processing locations.
  • Dark patterns: Do not gate accessible features behind paywalls or complicated opt-ins. If captions are the only way to consume your content, they must be easy and free.

Regulatory momentum is real—from the European Accessibility Act to evolving procurement standards. Keep product, legal, and a11y teams in the loop so you are improving continuously, not scrambling before audits.

Putting It Into Practice: A Lightweight Plan

You do not need a giant budget to start. Think in small, high-impact loops.

  • Pick high-traffic flows: Onboarding, checkout, support, and dashboards. Use AI to draft improvements, then test with assistive tech.
  • Build a reusable accessibility prompt library: Store prompts for alt text, captioning, plain-language rewrites, and ARIA-friendly components. Share them in your design system.
  • Close the loop: Add accessibility checks to CI, including contrast tests, HTML validity, and keyboard navigation smoke tests. Require human validation for AI-generated content that affects meaning.

Concrete next steps

  1. Audit one core workflow with a screen reader and keyboard-only navigation, and log issues by severity. 2) Use ChatGPT, Claude, or Gemini to draft alt text and plain-language summaries for that workflow’s key screens—then review with at least two users with disabilities. 3) Establish a 2-week cadence to iterate: fix issues, retest, and document decisions in your design system.

Conclusion: Accessibility Is a Strategy, Not a Checkbox

Accessible AI is about dignity, speed, and scale. When you design with disability in mind, you make your product clearer, faster, and more resilient for everyone. AI can help you do that work—drafting captions, generating alt text, simplifying language, or guiding users through complex steps—but it must be grounded in standards, validated by people, and governed with care.

Start with one flow. Use the tools you already have—ChatGPT, Claude, Gemini—to prototype improvements, and then test them with real users and real assistive technology. That is how you turn accessibility from a compliance task into a durable product advantage—and how you ensure your AI truly works for people.