Hot takes from our DHIS West panel on generative AI:
✴ Health systems that are more gen AI-forward are willing to apply it to tasks they *don't* do today but should, vs trying to replace things they already do.
✴ Pragmatic, bottoms-up regulation means leveraging existing accreditation frameworks to vet AI performance, and being willing to measure bias/safety/accuracy amongst the human workforce to benchmark against AI, versus setting thresholds for AI in a vacuum.
✴ AI getting sued for executing prior auth denials "too quickly" is a red herring; what people actually care about is whether they have a means to appeal those denials efficiently.
✴ Sky high valuations for gen AI companies are a reflection of compute costs and tech moat, plus the fact that gen AI goes after not just the O($100B) enterprise software TAM, but the O($1T) services TAM.
And we heard about 100's of AI-powered use cases that are already live in the wild from payors and providers, including those specifically powered by LLMs - it's now not even a matter of if or when, but which!
Panel Participants:
Munjal Shah - CEO of Hippocratic AI
Ashok Chennuru - Global Chief Data and Insights Officer of Carelon @ Elevance
Aabed Meer, MD - Partner at Questa Capital Management
Tarun Mehra - VP Healthcare Strategy, M&A and Partnerships