Operations and adoption

Getting your team to actually use the system

Adoption is an operations problem, not a software problem

LB Labs2 min read7 Apr 2026

Context

Plenty of automation projects are technically finished and operationally dead: the workflow runs, but the team quietly keeps doing it the old way.

Routing around a system is rational when the system makes an individual's day harder, even if it makes the business better off.

Adoption is won or lost in the first fortnight after go-live — before the workarounds harden into habit.

AI systems improve with use — corrections, examples and edge cases feed them — so low adoption now also means a system that stops getting better.

The gap between a demo and daily reality is wider with AI: trust has to be earned per workflow, not granted per project.

Teams have seen tools come and go; the default assumption is that this one is temporary too.

01Involve the people who run the process before the build, not at the training session.
02Retire the old path deliberately — running both indefinitely guarantees the old one wins.
03Make the first fortnight easy to get help in: a named owner, fast fixes, visible responses to feedback.
04Show the team what the system saved them, in their terms, not the project's.
05Fold their corrections into the system quickly enough that reporting a problem feels worthwhile.

Declaring victory at go-live and disbanding the support around it.
Training that demonstrates the happy path and ignores the messy Tuesday afternoon reality.
Leaving the old process available 'just in case', indefinitely.
Treating quiet non-use as acceptance instead of as feedback.