AI consulting services: do you know which process to automate first, and whether your data can support it?

They decide what to automate and in what order, check that the data supports it, and make sure the result reaches production. The deliverable is a working system and a team that can run it — not a strategy document.

A readiness assessment takes days, not months. Selecting a use case and agreeing its baseline takes a week or two. A first build in production is typically measured in weeks, depending on how clean the data is and how many approvals the workflow touches.

No, but you need to know its state. The readiness assessment tells you which use cases your current data can support and which need clean-up first. Skipping that step is the most common reason AI projects stall after the demo.

It is priced hourly, as a fixed project, or on retainer, and the range varies widely by scope and region — published 2026 rate guides set out the going figures. The number worth comparing is modelled payback against the number you are trying to move, not the day rate.

Consulting decides what should be automated and why. An automation agency builds what it is asked to build. Engagements that stop at advice tend not to get implemented; engagements that skip the advice tend to build the wrong thing well.

You do. Handover includes documentation, the evaluation set used to prove it works, an escalation path, and a review date to decide whether it still earns its place.

That is agreed in advance. Every use case gets a baseline and a threshold that would make it a failure, set before anything is built, so the decision to stop is a measurement rather than an argument.