For students with dyslexia, most digital reading tools still assume a “standard” learner. Structured literacy approaches such as Orton Gillingham prove that progress depends on multisensory, individualized instruction. Yet those same principles rarely shape how AI systems are designed.

This session explores how UX professionals can build AI that adapts to the learner rather than forcing the learner to adapt to the system. Participants will see how educator-centered AI agents can summarize phoneme progress, tailor multisensory prompts, and surface adaptive next steps. The focus is not on replacing teachers but on supporting their insight and empathy through responsible design.

Attendees will leave with practical frameworks for inclusive AI design, methods for human-in-the-loop decision making, and ethical considerations for working with neurodiverse learning data.