As AI erodes seat-based and time-and-materials pricing, competitive advantage shifts from AI tools to institutional knowledge. Firms that capture and operationalize that knowledge can own customer outcomes, and price for value instead of hours.
Summary
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.
Challenges
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.