This guide sets out how we assess readiness in the first two weeks of an engagement, and what we look for before recommending any spend.
What AI readiness actually means
Readiness is not a maturity score. It is a set of specific, testable conditions in your business that determine whether a use case can be delivered in weeks and measured in numbers your finance team recognises. A team with modest data and clear ownership will outrun a team with a data lake and nobody accountable for it.
In practice we test three things: can the decision be described precisely enough to automate, does the data exist at the quality the decision needs, and is there a named person whose job changes when the system works. Where all three hold, pilots land. Where one is missing, they stall.
The four signals we look for
Across advisory and delivery work in regulated, messy, real world operations, four signals separate the engagements that succeed from the ones that quietly fade.
- A decision with a cost attached. If you cannot put a number on the hours, errors or delays today, you cannot prove the gain tomorrow.
- Data within reach. Documents, tickets, spreadsheets and inboxes count. Perfect warehouses are rare and rarely necessary.
- A named owner. Someone whose week gets easier when the system works, and who will defend it internally.
- A human checkpoint. A person who reviews output before it reaches a customer, a regulator or a payment.
What good looks like in the first ninety days
A well run first quarter produces a working system in production, not a slide deck. We expect a prioritised opportunity map in the first fortnight, an agreed architecture and security position by week five, and a live pilot with evaluation dashboards before the quarter closes.
From there, scale is a commercial decision rather than a technical one. Teams that instrument their pilot early, with cost per task, accuracy against a human baseline and drift alerts, are the ones that get a second budget.
Not sure where you stand?
Our free AI audit applies this assessment to your own processes. You leave with a prioritised view of what is worth building first, and what to leave alone.