Once you have developed your AI solution, what will it take to scale it across settings? And how does that affect your decisions today?
As we have seen, it pays dividends to think about long-term strategy while you are developing your MVP.
Two last considerations are worth mentioning here.
First, if your ultimate vision is to scale your AI solution across markets, it is particularly important to think ahead.
For example, if you develop an algorithm based on a Chinese data set, the results do not necessarily translate to the US. There may be relevant differences between people in both countries, or you may be required to provide clinical proof based on local datasets. The two health systems have different needs, and each has their own regulatory standards. If you optimize your solution for a certain market, or only use data from that market, you may compromise your ability to enter another market.
So if you have the opportunity, familiarize yourself early with different markets, and explore the possibility of running pilots or clinical trials in different countries as a future step.