In AI is Eating SaaS, I’ve explained how AI is quickly and inexorably changing entire verticals, breaking these “narrow commercial use case silos” into a single unified outcome-based use case.
In The AI Business Architect, I’ve explained how the business profession has to change to become a valuable component of building up a market that is just developing.
In this issue, I want to give you the framework to create value as a professional in this specific time window, which I would like to define as “the AI’s sweet spot.”
Or a time where instead of having a demand bottleneck (over-supply), we have the opposite, a supply bottleneck (over-demand).
In short, there is so much demand for AI services that supply can’t keep up with it, and yet, that’s the tricky part of it, this demand is not well-shaped yet.
Meaning there is not yet a specific set of commercial use cases, at scale, around which this demand might be able to consolidate.
In short, we are in a “market discovery phase” where enterprise companies want to leverage AI but are not sure yet in which specific use case will apply to them, how and in which part of the organization will implement it, and what methodology to use to test and learn.
This requires a different kind of business profile and mindset.
In a time when the various pieces that make AI viable, as a broad technology and not a bunch of narrow use cases, are finally coming true, what does that imply for an organization?
For that sake, understanding the ecosystem’s business architecture and the company sitting on top of that ecosystem will be pretty critical.
Let’s get into it.
