AI-to-Production Readiness Playbook
A playbook for taking one AI pilot to go-live: the owner, live data, approvals, the working process, operations and the go-live review.
Free to download. It asks for no email address.
What the playbook holds
- A short account of why pilots stall at the hand-off, and a table of the steps with what each settles and when it is done
- Name the owner: authority to change, pause and stop the system, a deputy, and the date they accepted
- Prove it on live data: a run through the production route, with late, wrong and missing data each tried
- Take it to approval: security, privacy, risk and the business owner, each with the conditions set and the date held
- Redraw the process: the new route in a few sentences, and the day the old one stops
- Plan for failure: the fallback, the person to call and the date it was tested
- The go-live review table, and a record for the first weeks after launch
What completing it does not do
It is meant for a single pilot at a time. Completing it does not make a launch safe, it makes the hand-off visible, and nothing in it is an audit, certification or benchmark. To rate readiness across the whole organization first, use the Enterprise AI Readiness Checklist.
On this page
A pattern we see
The review where one record is missing
A pilot has worked well for its sponsor and its first users. The project team is about to move on. Nobody has been asked to own the system, and the people who answer for security first see the design in the week before launch.
- The owner is named late. The head of operations agrees to own it but has never seen the design. The playbook asks for acceptance in writing, and a deputy.
- Live data exposes the pilot. Run through the production route, the system meets late and missing records that the clean extract never had. The owner decides what it does when data cannot be trusted.
- Approvals set conditions. Security and privacy leads see the live design, not the demonstration, and attach conditions the team can still meet.
- The review asks for each record. The sponsor goes down the steps and asks to see the evidence. One step has none, so the decision is to go with conditions.
Where it endsThe system goes live with a named owner, a tested fallback and a date on which the old route stops. The missing record becomes a condition with an owner, not a surprise after launch.
What do people ask before using the AI-to-production readiness playbook?
Is the production readiness playbook for every AI pilot or just one?
Use it for a single pilot or use case at a time, once it is close to going live. For readiness across the whole organization, rate that first with the Enterprise AI Readiness Checklist. The playbook then closes the hand-off for the specific pilot in front of you.
In what order should I work through the playbook?
In order, with the owner in the room from the start. It begins by naming the owner, then proves the system on live data, takes it to approval, redraws the process, plans for failure, holds the go-live review and follows the first weeks after launch.
When should I take the pilot to security, privacy and risk?
Early, and with the design of the live system, not the demonstration. Approval asked for in the final week is approval refused or delayed. Asking early lets the people who answer for risk set conditions that the team can still meet before launch.
Does completing the playbook make my AI launch safe?
No. It makes the hand-off visible, but it is not an audit, certification or benchmark. Its value is that the go-live review can ask for the record behind each step, so a missing record becomes a condition with an owner before launch instead of a surprise after it.
Holding a pilot that is close to go-live?
Describe what you are weighing in a few lines. A senior practitioner replies with a suggested first conversation.