What should you check before launching an AI pilot?

That the right teams have signed off (security, network, and whoever owns the connected systems), that people know which data stays out, that someone owns the tool afterward, that you can switch it off, and that success measures are agreed. The checklist above tailors the list to your project.

Who needs to sign off before an AI tool goes live?

Usually security, the network team, and the enterprise apps team if it connects to a system of record. Legal or privacy joins when personal or regulated data is involved, and your own process may add others, such as procurement or HR.

What is a go/no-go checklist for AI?

A short list of conditions that must be true before a launch. If every required item is done, you go. If not, you know exactly what is blocking you, so the conversation is about specific gaps, not a general feeling that the project isn’t ready.

Why does every AI launch need a way to switch it off?

AI output can be wrong in ways nobody predicted, and an integration can behave badly under real load. If you can stop it quickly and know how, a bad day is an inconvenience. If you can’t, it becomes an incident.

Do I need a checklist for a small pilot too?

Yes, a shorter one. Small pilots can skip approvals, and that is how data ends up in places nobody agreed. The checklist gets longer as the number of users, the data sensitivity, and the system access grow.

What does ready to start actually mean?

Every required item is done, so no known gap would surprise you in the first week. Recommended items still help, but a missing one shouldn’t stop a start. The verdict in the tool shows what is left.

AI Launch Readiness Checklist | Courtney Stephenson

Project name (optional)

What is the AI doing?

Where does it run?

What data does it touch?

Check everything that applies.

Public informationInternal business informationCustomer or employee personal dataRegulated data (health, financial, legal)

Can it change things, or only read?

Who will use it first?

A wider launch adds items on capacity, communication, and champions.

Your checklist

Not ready yet

0 of 17 required items done. 17 required items are still open. Starting now would mean launching with gaps.

Launch readiness checklist for your AI project

Check off each item as it is done. Items marked required are the ones that should be finished before you start.

Approvals

The security team has reviewed the project and signed off.They will ask where data goes, who can see it, and what happens when something goes wrong.The network team has approved the vendor’s domains for access.Network changes have lead times, so asking late can delay your start.The enterprise apps team has agreed the integration and who supports it. RecommendedAnything that connects to a system of record needs an owner who will fix it when it breaks.The vendor has been through your due diligence: questionnaire, contract, and data terms.Confirm what the vendor does with your data, including whether it can train its models.

Data and access

People know which data must never go into the tool, and the acceptable use policy has been shared.It’s easy for a well-meaning person to paste the wrong thing.A one-page data-flow summary exists and matches what was actually built.It is the first thing security will ask for, and it keeps everyone describing the same system.Only the intended users have access, granted by role.Broad access during a pilot is hard to undo later.How long the vendor keeps your data, and how it is deleted, is confirmed in writing.Retention isn’t always what people assume it is.

People and support

A named owner is responsible for the tool after launch.Projects without an owner decay once the launch team moves on.A sponsor can settle disagreements between the teams involved.Without one, the slowest team sets the timeline.Pilot users are chosen and have agreed to take part.Include people who are eager and people who are not, so the result isn’t skewed.Users have been trained on what it can and can’t do, and which data stays out.Training is the cheapest safeguard you have.People know who to ask when something goes wrong, and how.If the answer is unclear, people stop using it or work around it.The people affected have been told what is happening and why. RecommendedSurprise is what turns a tool launch into resistance.

Safety net

You can switch it off quickly, and you know exactly how.A launch you can’t reverse should be held to a much higher bar.A person reviews what it produces or changes, where the stakes call for it. RecommendedFluent output can still be wrong, and someone must stay accountable for the result.Its access and actions are logged, and someone looks at the logs.Logs you never read won’t help in an incident.There is a named contact and a short procedure for reporting an incident.In an incident, the first hour matters most.The old way of working is still available as a fallback. RecommendedIt keeps the pilot from becoming a single point of failure.

Measures

Today’s baseline is recorded before the pilot starts.Without it you can’t tell whether the AI helped.Success measures and a scale, fix, or stop rule are agreed in writing.Agreed in advance, the end-of-pilot decision is a check, not a debate.A decision date is on the calendar. RecommendedPilots with no end date drift.

How to use it

Describe the launch. Say what the AI does, where it runs, what data it touches, whether it can change things, and who uses it first.
Work through the list. Check items off as they are done. The verdict updates, and any open required item shows what is still blocking you.
Copy it to your plan. Copy the checklist, with the items you’ve checked off, into your project plan or send it to your sponsor as a status update.

Why a checklist before launch

Think about what could go wrong on day one: a team that wasn’t asked, a data rule nobody shared, no one to call when something goes wrong. Each gap is small, and each is cheap to close before the start and expensive after it.

I like a short list that makes the gaps visible while there’s still time. To plan who to involve and when, use the AI rollout plan generator, and to set the rules people follow, see the AI acceptable use policy generator.

AI launch readiness, explained

What should you check before launching an AI pilot?: That the right teams have signed off (security, network, and whoever owns the connected systems), that people know which data stays out, that someone owns the tool afterward, that you can switch it off, and that success measures are agreed. The checklist above tailors the list to your project.
Who needs to sign off before an AI tool goes live?: Usually security, the network team, and the enterprise apps team if it connects to a system of record. Legal or privacy joins when personal or regulated data is involved, and your own process may add others, such as procurement or HR.
What is a go/no-go checklist for AI?: A short list of conditions that must be true before a launch. If every required item is done, you go. If not, you know exactly what is blocking you, so the conversation is about specific gaps, not a general feeling that the project isn’t ready.
Why does every AI launch need a way to switch it off?: AI output can be wrong in ways nobody predicted, and an integration can behave badly under real load. If you can stop it quickly and know how, a bad day is an inconvenience. If you can’t, it becomes an incident.
Do I need a checklist for a small pilot too?: Yes, a shorter one. Small pilots can skip approvals, and that is how data ends up in places nobody agreed. The checklist gets longer as the number of users, the data sensitivity, and the system access grow.
What does ready to start actually mean?: Every required item is done, so no known gap would surprise you in the first week. Recommended items still help, but a missing one shouldn’t stop a start. The verdict in the tool shows what is left.

I’m Courtney Stephenson, an AI strategy and implementation leader, and I built this tool. If you’re about to launch a pilot and want a quick check on whether you’re ready, get in touch.

Want a second opinion on your results?

Book a free 15-minute call and we’ll talk through what this means for your team.

Book a 15-minute call

Read the guide

How to set AI pilot success metricsAgree the measure, the target, and what happens at the end, before the pilot starts.