Support decay
The fall in exceptional help a transferred capability needs from its original team over time — the real measure of whether an AI pilot has become an organizational capability.
When a capability moves from the team that built it to a second team, the important measure is not documentation completeness. It is support decay: as the capability moves, does the amount of exceptional help required from the original team fall?
If it does, the capability is genuinely transferring. If it does not, the organization may have only appeared to distribute the capability while actually centralising the expertise needed to keep every instance working. Adding more teams then multiplies the dependency on the same experts. That is a scaling trap.
How to read it
Track the rescue work the second team needs, classify why it was needed, and watch the trend. A healthy curve slopes down: fewer escalations to the founders, shorter waits, more problems solved from the written assets. A flat or rising curve says the capability lives in people, not in the organization.
Support decay is the key result of a second-team test, and it separates a durable capability from a successful AI pilot.
Read more in The second team is the real innovation test.
Related terms
Second-team test
A test of whether a different competent team can reproduce a pilot's useful result without inheriting the first team's exceptional conditions or constant expert help.
AI pilot
A limited trial of an AI use case to test whether it works in practice. A pilot proves one team can succeed; capability starts when others can reproduce the result.
Operating model
How an organization actually runs: its workflows, decisions, roles, governance and handoffs. AI creates value when it changes the operating model, not when it is bolted onto the old one.