An AI delivery partner takes responsibility for getting an agreed system into production and helping people use it in their working day. The scope matters: an audit or proof of concept answers earlier questions, while a production build includes the work needed to make the system ready for live use.
In practice, delivery connects five jobs. First, decide with your team which workflows AI could help with, what order to tackle them in and what each improvement is worth in currency. Second, design the operating model: whose work changes, which decisions an agent can make, who remains accountable and what happens when it gets something wrong. Third, build inside your estate and repositories alongside your engineers, so they learn how the system works as it develops. Fourth, specify and test the evidence during design: evaluations, audit trails, escalation routes and the points where a person checks or approves an action. Fifth, help people use and improve the new workflow, measuring adoption and inviting their feedback.
Ask what you will be able to review in the first thirty days. Tenhaw commits to measurable value delivered every month and reports a month that delivers none as a failed month. That gives you a clear point to examine the evidence, understand any obstacle and decide what should happen next.