The last few years produced a wave of "AI features": a summarize button here, a chat panel there. Most of them are quietly ignored. Not because the underlying models are weak, but because they sit outside the flow of work. Anything that requires a person to stop, switch context, and remember to use it will lose to the path of least resistance.
The tab problem
A model in its own tab is one more destination to visit. Real leverage comes from intelligence that acts where the work already happens — inside the queue, the inbox, the ticket, the record. The best AI systems are often invisible: the user never "opens the AI," they simply find that the right things are already drafted, routed, or flagged.
- Embed decisions into existing steps instead of adding new ones.
- Prefer automatic triggers over manual buttons.
- Draft, route, and pre-fill rather than ask and wait.
- Measure adoption by outcomes, not by clicks on the AI button.
From feature to system
The shift is from thinking about AI as a feature to thinking about it as a participant in a workflow. A participant reads context, takes an action, and hands off to a human when judgment is required. That framing changes everything about how you design, measure, and trust the system.
Nobody wants an AI feature. They want the work to be done. Design for the second thing and the first disappears.
When intelligence is woven into the flow, the question stops being "did anyone use the AI?" and becomes "did the work move faster and with fewer errors?" That is the only metric that has ever mattered.