AI & HIV: Can Machine Learning Deliver Better Outcomes? | aidsmap

Skepticism regarding the immediate impact of artificial intelligence on HIV treatment and prevention was voiced at the Conference on Retroviruses and Infectious Diseases (CROI) 2026, despite widespread discussion of its potential. Dr. Ravi Goyal, of the University of California, San Diego, and a moderator for an AI-focused session at the conference, questioned whether the promised revolution in public health and healthcare would materialize.

“We’ve been told that it’s going to revolutionise public health, it’s going to revolutionise our healthcare system,” Dr. Goyal stated, according to aidsmap. “But if you’re like me, I don’t know, maybe you don’t quite believe the hype, maybe you haven’t quite seen it yet. And don’t gain me wrong, machine learning and generative AI are very impressive in demos and in labs, but that doesn’t mean that it always translates into better patient outcomes.”

The discussion at CROI 2026 centered on the application of machine learning and generative AI to improve outcomes for individuals living with or at risk of HIV. However, the precise methods for deploying these technologies remain unclear, prompting the expressed doubts. Aidsmap reported on the session, noting the lingering questions surrounding the practical implementation of AI in the field.

The European AIDS Treatment Group also covered the discussions at CROI 2026, highlighting the debate over whether machine learning represents a genuine shortcut to improved HIV outcomes or a potential misdirection of resources.