  Screen-reader software enables blind users to access large segments of
electronic content, particularly if accessibility standards are followed.
Unfortunately, this is not true for much of the content written in physics,
mathematics, and other STEM-disciplines, due to the strong reliance on
mathematical symbols and expressions, which screen-reader software generally
fails to process correctly. A large portion of such content is based on source
documents written in LaTeX, which are rendered to PDF or HTML for online
distribution. Unfortunately, the resulting PDF documents are essentially
inaccessible, and the HTML documents greatly vary in accessibility, since their
rendering using standard tools is cumbersome at best. The paper explores the
possibility of generating standards-compliant, accessible HTML from LaTeX
sources using Large Language Models. It is found that the resulting documents
are highly accessible, with possible complications occurring when the
artificial intelligence tool starts to interpret the content.
