What should leaders learn from an AI adoption dashboard?
Decide what an AI adoption dashboard is supposed to support before you read it. Usage numbers need labels: logins can show reach and completed tasks can show use, yet neither establishes quality, customer benefit or financial return. Add a few outcome checks tied to the assignment.
A dashboard can show how many people opened a tool without showing whether their work got better. The summit's focus on organizational transformation calls for a clearer link between activity and a result.
A manager deciding where to invest training needs different information from an owner deciding whether to keep a workflow in service. Keep the usage data, since it still tells you something about reach and use.
For outcomes, look at whether the work was accepted, what corrections it needed and whether the result reached the person who needed it. Show the unresolved problems too, next to the successes.
Bring the dashboard to the people doing the work. Ask them what the numbers leave out and which decision should change.