"Preface This document reflects the most accurate guidance I can offer today, based on the current state of accessibility standards, AI tooling, and real-world practice. Both accessibility and AI are evolving quickly. As models improve, platforms change, and new standards emerge, some of the details and recommendations here will need to adapt. The core principles-intentional curation, clear boundaries, and responsible use-are designed to hold up over time, even as the technology underneath them shifts."
"Building a useful accessibility AI isn't about clever prompts or the latest model. It's about trust. More specifically, it's about whether the answers your AI gives reflect how your organization actually works, align with accepted standards, and help people make better decisions without creating new risk. I often describe this as building the brain of your accessibility AI. Prompts are the voice."
Accessibility AI requires curated internal knowledge that reflects organizational practices, accepted standards, and risk tolerances. Prompts act as the voice and models provide horsepower, but curated knowledge forms the brain that makes responses reliable, consistent, and aligned with organizational values. Grounding answers in explicitly allowed sources reduces misinformation, limits new risk, and lowers friction for product teams. Prioritize internal policies and common team questions before incorporating external standards or open-source libraries. Control which materials the system may reference rather than retraining foundation models. Maintain principles of intentional curation, clear boundaries, and responsible use as AI and standards evolve.
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