AI and Enterprise
Most SaaS companies are protecting the wrong moat.
We’ve spent years thinking features, UI polish, and enterprise checkboxes keep competitors at bay. But the real defensibility in a post-AI world sits deeper: in the data model itself. If the foundation that structures work no longer maps to how people actually get things done in an AI-native environment, even the strongest moats start to crack. A decade of investment can become technical debt overnight if the underlying mental model of work shifts.
And that shift is already happening. The biggest enterprise AI wins aren’t coming from chat interfaces or clever prompts. They’re coming from automated inference quietly running inside workflows. No one wants their team juggling chat windows all day. They want a system that notices, interprets, and acts without being asked. Over the next few years, the companies that win are the ones that embed intelligence directly into the operational fabric.
The real unlock is moving from “AI you talk to” to “AI that just does the work.” And the SaaS players built on flexible, deeply structured data models are positioned to ride that wave. Those tied to legacy assumptions about how humans interact with software will feel the ground shifting beneath them.