Generative AI like ChatGPT is truly exciting, and it’s easy to be seduced by the technology’s potential to produce, well, almost any sort of output. Be careful. The opportunity in generative AI is enormous but requires careful analysis of where the best applications lie. Healthcare, in particular, requires this assessment – this isn’t an industry known for fast change, and the risks of inappropriately deploying new technology can be huge. For instance, consider the hype around IBM’s Watson Health a few years ago; this AI was going to figure out complex cancers! It didn’t, and it was sold off cheaply in parts last year.
With healthcare, we can deploy a straightforward, five-part approach to evaluate where enterprise-ready generative AI will gain traction early on:
1. Start with the problems the technology can help to address; what is it really good at doing?
2. Search for the big areas that have those problems
3. Understand the triggers and obstacles to adopting the technology in those top use cases. This includes what people need to stop doing in order to start embracing the new solution. (For Watson, oncologists were definitely not going to stop diagnosing cancers)
4. Assess the business dynamics around how the high priority categories will be entered
5. Look broadly at the levers for creating a full solution, including the technology but also going beyond to include, for example, workflow consulting, patient education, and much more