How to use AI to generate alt-text for a library of 1,000 images to improve website accessibility?

Design & Visuals, Writing & Content

Alt-text improves accessibility and helps users who rely on screen readers. The goal is to automate consistent, accurate descriptions at scale.

Define clear quality standards for length, specificity, and branding. Establish a review process to catch errors.

Deliverables include a repeatable process, example outputs, and documentation that teams can reuse.

Who is this for?

- Web accessibility teams
- Content creators and editors
- UX and product teams
- Marketing teams needing descriptive alt-text
- QA and compliance leads

Before you start

- Inventory of images
- Defined accessibility guidelines
- Basic familiarity with your CMS
- Stakeholder sign-off for standards

General Process (How it works)

  1. Define accessibility goals and standards Identify required details (content, context, branding) for alt-text and set a length target.
  2. Inventory images and categorize Create a dataset mapping image IDs to categories and usage.
  3. Draft AI prompts and guidelines Design prompts that elicit concise, descriptive alt-text aligned with standards.
  4. Generate alt-text in batches Run prompts on all images to produce initial alt-text descriptions.
  5. Apply quality checks and human review Validate against rubric; fix where needed; decide on fallback wording.
  6. Document process and templates Create checklists, examples, and templates for future batches.
  7. Publish and monitor Apply approved alt-text to CMS and track accessibility metrics.

Common beginner mistakes

❌ Assuming one-size-fits-all descriptions
❌ Ignoring image context or function
❌ Not aligning with the brand voice
❌ Skipping review/QA
❌ Overloading alt-text with keywords
🤔

We are still looking for the perfect solution

Our experts are still analyzing the best tools for this specific task. The database is updated daily.