How do people discover useful AI capabilities when they do not know what to ask for?

Connected ideas

• When does measuring AI adoption stop being useful?

  AI usage can be a useful transitional signal while organisations are building capability, but the enduring measures should be what changed: service quality, time, cost, reliability, user experience, learning or some other meaningful outcome.

• Will the most useful AI agent be the one we trust enough to let in?

  As agents become capable enough to act, their practical usefulness depends on context, permissions and delegated authority. Trust is part of the architecture: identity, boundaries, auditability, approvals and revocation determine what an organisation is willing to let an agent do.

• If models become interchangeable, where does durable organisational AI capability accumulate?

  The durable capability around AI may sit less in the model itself and more in the context, permissions, tools, workflows, evaluations, controls and operating knowledge that allow models to work safely and repeatedly inside a real organisation.

• If AI changes what an organisation can feasibly do, should the strategy focus on AI or on the possibilities that have opened up?

  The strategic significance of AI is not simply that organisations can now use AI. It is that activities which were previously too expensive, slow, complex or impractical may become feasible. Strategy should examine those changed constraints rather than turn use of the technology itself into the objective.