I wanted to share with you four key considerations for making AI sustainable as an actual business case.
The use case must be explicitly defined
If you are not able to have an effective monopoly on a specific use case, keep narrowing down your niche.
Founders can have grand visions. But if they are not able to describe the individual steps to get to that vision and the solution for each step, then reconsider.
Specified, proprietary data
One option is to find partners who have access to relevant data very early on and lock them in.
The first question you should be asking founders is “How are you going to own proprietary data for your vertical?” Founders need to recognise the importance of proprietary data. If they don’t, reconsider.
The end user/last-mile solution must be built
Understanding how an end user can effectively utilise your output is the essence of product-market fit for AI products.
Your job is to make sure founders have solved that process all the way to the end and have not stopped in the middle.
Secured buy-in from end users
If your potential customer is unable or unwilling to use your product, what’s the point? AI is still in the realm of “scary new” for the vast majority of the world.
This step is critical for any start-up
that is not targeting high-tech multinational firms as potential customers. For every deck you get where the founders pitch an “AI for X” start-up, you should confirm that the founders understand what the end customer of “X” requires for product adoption.
This is an excerpt from Tech in Asia. You can read the full article here