Tools change quickly. Teams need transitions.
A new AI tool also changes handovers, responsibilities and habits. Introducing it well creates room to learn and makes its everyday value visible.
A new tool can be tried in an afternoon. Changing a shared workflow takes longer. My time as a team lead at NetsDirekt and later as a Product Owner at netzwerk P left me with this perspective: technology always enters an environment where people are already getting work done.
That environment has established handovers, tacit knowledge and responsibilities. Introducing AI changes those things too. For me, that means the introduction starts before choosing the right tool.
Start with the workflow
I would first look at a specific step together with the people doing the work. Where is information copied several times? Where is context missing? Which check takes time but prevents an expensive mistake?
Consider a handover for which someone writes a summary from several notes. An AI draft could help. But if the notes are incomplete or nobody knows who accepts the handover, the underlying problem remains. The text is ready sooner; the work is not finished yet.
Responsibility has to move with the work
As soon as a system takes over part of the work, people need a new agreement. Who reviews the draft? Who adds missing information? What happens when the result is unusable? These questions should be settled before an experiment becomes an expectation for the whole team.
For me, that includes a clear way back. Someone who gets stuck in the new workflow still needs to be able to complete the task. A pilot becomes difficult to assess when people have to hide failures to keep working.
Learning is part of the work
I would initially treat scepticism as information. Someone may see an exception that the demo missed. The time saved may simply move into a more demanding review. Or people may be unsure about what will be expected of their roles.
A team needs time to explore these questions through real tasks. That includes shared examples and the freedom to openly reject a poor suggestion. People expected to show only successful results cannot provide useful feedback about everyday work.
The value has to survive the demo
I would judge an introduction by whether the entire task becomes easier: less rework, clearer handovers, more reliable results. The number of people who have opened a tool once tells me little about that.
Sometimes the benefit justifies broad use. Sometimes a tool fits only a small part of the workflow. Both are useful outcomes if the team can work better afterwards.
Tools will keep changing quickly. I see my responsibility in shaping the transition so that people know what they can leave to the system and where their judgement is needed.