The Ninety-Two Percent
Ninety-two percent of firms have tried AI. Five percent have achieved their objectives. The gap between those numbers is a product problem.
Ninety-two percent of firms have tried AI. Five percent have achieved their objectives. The gap between those numbers is a product problem.
Most firms have tried AI. Almost none have made it work. The gap between pilot and production is a product design problem.
When every tool is optimized for one property type, the analyst who works across types is left with nothing.
When the market pain is real but the solution is a custom build, the gap for a product is confirmed — not filled.
The right abstraction level for a tool isn't always the one that matches the domain. Sometimes it's one level up.
A tool that owns one layer and integrates cleanly with everything else is harder to displace than a tool that owns everything.
Data is not knowledge. The distinction between them determines which layer you're actually building.
When the MCP ecosystem matures, you stop seeing individual tools and start seeing a stack. The gap moves from 'unbuilt' to 'one specific layer.'
When domain experts start teaching AI workflows to their audience, the DIY wave is already cresting. The product wave follows.
Enterprise AI tools solve the problem for large firms. The gap is the everyone else.