Most AI rollouts do not fail because the models are weak. They fail because the business mistakes novelty for implementation.
A single good output in a meeting does not mean a team has a system. It means someone had a moment.
What usually goes wrong
The tool is introduced before the workflow is defined. Context lives in one person's head. Nobody decides where human review belongs. The team gets a spark, not a pattern.
What a real rollout needs
A repeated task. Clear inputs. Clear outputs. Guardrails. Ownership. Context that survives beyond one session. And enough operational discipline to measure whether the thing is helping.
The test
If the workflow disappears when one enthusiastic person gets busy, you did not build a system. You built a temporary performance.
What to do instead
Start small. Pick one painful workflow. Make the context explicit. Install review rules. Run it until the gain is obvious. Then expand.
