McKinsey identified a trend that is probably no surprise to many: seat-based SaaS licensing is under pressure. AI is reducing headcount in specific functions. Fewer users means fewer seats. Vendors are losing revenue.
Enterprise software pricing was built on people. More users, more seats, more revenue. The commercial model assumed headcount grew. AI is inverting that assumption, and the financial consequences for vendors are significant. This is not unlike the efficiency expectations brands are already placing on their agencies as AI tools mature: fewer people, lower fees, same output.
The monetisation reset
McKinsey advises software leaders to shift toward consumption-based or outcome-based pricing while also establishing their posture with regard to monetising data access and API consumption. These are not separate strategies. They are a coordinated response to the same problem: recovering revenue in response to a declining commercial model.
The brand pays less for access. Outcome-based fees recapture the efficiency gains those fewer seats produced. Data monetisation creates value for the vendor on the intelligence your data generates. The vendor recovers in multiple places.
This is not a future risk. McKinsey describes it as the monetisation reset already underway. Vendors are not waiting for contract renewal to begin.
What stays behind when you leave
Three years of operational data runs through your marketing software. The workflow logic, the predictive scores, the optimisation rules: all of it trains inside the vendor's system. You leave. Your records come with you. Everything the platform learned about how your business operates stays behind. You start over. They do not.
The parallel is worth noting. Agencies are moving in the same direction, shifting away from hourly billing toward outcome-based and software-style commercial models. The mechanism differs. The logic is identical.
For any brand assessing this landscape there are two questions. What capability cannot be built in-house? And where vendors are using your operational data to build products and capability of their own, what does the brand own at contract end?
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