How AI Is Reshaping PDF Accessibility at Scale
Explore how GenAI can transform stubborn PDFs into screen-reader-ready course materials in minutes, with concrete before-and-after examples and actionable strategies you can immediately apply.
Presented by:
Elle Corvette, William Peace University
Hear it from the author:
Transcript:
Thank you for looking at my poster Pathways to Success: How Gen AI Transforms PDFs for Students with Low Vision or Blindness. My name is Elle Corvette, and I'm Director of Faculty Development and Immersive Learning at William Peace University. What is so fantastic about using Gen AI for PDF accessibility is that what used to take us 4 hours to remediate a document so that a screen reader like Jaws could access the file and read it to the student with low vision or blindness; it now takes us a matter of minutes. This has been a game changer for teaching our faculty how to use it and upload documents into LMS, but things like notebook LM, seeing AI, and vision AI, as well as Google Glasses, are all helping our students at our university, and they can help you as well. Please feel welcome to reach out with me with any questions. Look forward to talking.
Key Words:
Accessibility, Screen Readers, PDFs
Abstract:
This poster showcases how Generative AI (GenAI) can dramatically streamline PDF remediation for students with low vision or blindness who rely on screen readers. By automating structure tagging, image descriptions, table reformatting, and text cleanup, GenAI reduces the time and expertise needed to create accessible course materials while improving consistency and alignment with standards such as Web Content Accessibility Guidelines (WCAG) and Section 508 (digital accessibility compliance). This poster session highlights practical workflows, before-and-after examples, and lessons learned from early classroom use, offering participants concrete strategies to scale accessible PDF creation and enhance inclusivity across disciplines.
Outcomes:
1. Use GenAI to automate PDF accessibility tasks by reducing reliance on manual remediation expertise.
2. Foster inclusive learning environments by ensuring compliance with accessibility standards.
3. Promote cross-disciplinary adoption of AI-driven accessibility solutions.
References:
Dolmage, J. T. (2017). Academic Ableism: Disability and Higher Education. Ann Arbor: University of Michigan Press.
Leporini, B., Buzzi, M., & Penna, G.D. (2025). A preliminary evaluation of generative AI tools for blind users: Usability and screen reader interaction. In Proceedings of the 18th ACM International Conference on Pervasive Technologies Related to Assistive Environments (PETRA ‘25, pp. 562-568). Association for Computing Machinery, New York, NY. https://doi.org/10.1145/3733155.3737910
Zhao, X., Chen, X., & Cox, A. (2025). Exploring the affordances of generative AI in academic writing for disabled students. In Proceedings of the 58th Hawaii International Conference on System Sciences (pp. 4938–4945). ScholarSpace. https://hdl.handle.net/10125/109442