Running it with an internal AI taskforce, answered in full.

Because scaling an agent pilot requires changing roles, decision rights and governance across functions the taskforce has no authority over. A taskforce is typically staffed part-time by enthusiasts from one or two teams. It can prove agents work; it cannot redefine other people's jobs, and that is what scaling actually requires.

The first third adopt because they were always going to, they are curious and self-directed. Everyone else adopts only when their actual role, incentives and measurement change to assume the new way of working. More training does not move this number because awareness was never the constraint.

Usually yes. A taskforce is cheap, fast, and discovers real friction points better than any external party. Run it, learn what agents can do in your context, and bring in outside help at the point where scaling requires authority the taskforce does not have. Engaging a consultancy before that point tends to buy analysis you could have generated yourselves.

The reliable signals are: pilots succeeded but did not spread; adoption plateaued and more enablement is not moving it; different functions are building incompatible things; or risk and audit have started asking questions nobody can answer. Any two of those together mean the constraint has moved from capability to operating model.