Training Tech Teams for Inclusive AI

Training Tech Teams for Inclusive AI

Event graphic titled "Training Tech Teams for Inclusive AI" for World Usability Day. The image features two circular headshots: James Thurston (Head of Accessibility & Digital Inclusion for North America, Atos US) and Michaël Vanderheyden (Lead UX Engineer Central Europe, Atos Germany). The slide includes IAAP certification badges (CPACC, CPWA, KB-BFL), the World Usability Day logo, and the Atos logo against a blue and white background.

Event: Texas DIR World Usability Day
Organizer: Texas Department of Information Resources (DIR)
Date:
Location: Austin, Texas / Virtual

I am thrilled to be (virtually) in Austin today for the Texas Department of Information Resources (DIR) World Usability Day celebration!

It was a true honor to step in for my colleague Beatriz González Mellídez today and join James Thurston on stage to discuss one of the most pressing challenges in our industry: Training Tech Teams for Inclusive AI and Better Accessibility.

Accessibility Level Setting: A Must for Some, Good for EVERYONE

Inclusive AI isn’t just a buzzword; it’s a design imperative. Before diving into training strategies, we grounded the conversation in a shared understanding of accessibility — not as a compliance checkbox, but as a fundamental quality attribute that benefits every user in every situation.

Trainings and Good Practices: Embedding Accessibility — Shared Roles & Responsibilities

Real inclusion happens when accessibility becomes a shared responsibility across the entire team, not just a task delegated to a specialist. In this section, James and I explored how to embed accessibility into daily workflows through targeted training, clear role ownership, and a culture of continuous improvement. The goal: shift teams from reactive remediation to proactive, empathy-driven design.

10 Game-Changing Steps Towards Accessible GenAI

When it comes to Generative AI, accessibility doesn’t happen by default — it has to be designed in. We walked through a practical checklist of 10 actionable steps every team can take to build more inclusive AI-powered products:

  1. Inclusive Sources: Train models against bias by using diverse, representative datasets.
  2. Include laws & policies in training: Embed legal and regulatory accessibility requirements directly into model training.
  3. Ensure full keyboard interaction: Every AI-generated interface or interaction must be fully operable without a mouse.
  4. Use descriptive titles: Clear, meaningful headings and labels help all users navigate AI-generated content.
  5. Ensure authentic representation in generated media: Avoid stereotypes and ensure generated images and videos reflect real human diversity.
  6. Tag and label elements properly: Semantic markup and ARIA attributes are just as important in AI-generated output as in hand-crafted code.
  7. Simplify language and tag it correctly: Plain language benefits everyone; pair it with proper lang attributes for screen reader accuracy.
  8. Follow WCAG’s color contrast standards: AI-generated UIs must meet minimum contrast ratios to be readable for users with low vision.
  9. Provide text alternatives for audiovisual media: Captions, transcripts, and audio descriptions are non-negotiable for AI-generated video and audio content.
  10. User testing with people who have lived experience: No checklist replaces feedback from real users with disabilities — involve them early and often.

Conclusion and Q&A

We wrapped up with an open Q&A, fielding questions from the audience on everything from practical tooling to organisational change management.

A huge thank you to the Texas DIR for hosting such a vital conversation and to James for being a fantastic co-presenter.

Let’s keep making the digital world accessible for everyone!