AI Is the Grease, Not the Machine: Why Institutional Knowledge Wins the AI Economics™ Era

Two pricing models are breaking at once: seat-based software licensing and time-and-materials services billing are both being eroded by AI, and both are converging on outcome-based pricing. In this conversation, Certinia's Terry Melnik sits down with TSIA's Bo DiMuccio to make the case that institutional knowledge, not AI tooling, is what lets a firm own an outcome, price for value, and avoid fragile dependencies.

As AI automates workflows, seat-based and time-and-materials pricing models are collapsing even as delivered value goes up. Most AI initiatives stall at the “last mile,” a gap driven by fragmented systems and unproven operational maturity, not raw technology. Homegrown, ad-hoc AI agents built without institutional knowledge become a liability rather than an asset as they drift and degrade over time.