An AI readiness checklist for small businesses and nonprofits

Readiness is a quieter idea than it sounds. It does not mean your organization is behind, or that you need a large program first. It means you have thought carefully enough to take a first step without surprising your team, your clients, or your constituents.

This checklist is meant for small businesses and nonprofits. It is not a test, and there is no passing score. If you cannot answer a question yet, write down what you know and what you still need to find out.

1. What problem are you trying to ease?

"We should be using AI" is not a problem. "We spend too many hours rewriting the same kind of update," or "intake questions pile up faster than we can answer them," is a problem. Name the work in ordinary language. If you cannot describe the pain without using the word AI, pause and get more specific.

2. Who is affected, and who decides?

List the people who do the work today, the people who will review it, and the people who will feel the change — a client, a donor, a student, a customer. Then name one person who can say yes or no. A small team does not need a steering committee, but it does need a clear owner.

3. What information is involved?

Write down the kinds of information that would pass through the workflow: public web copy, internal notes, names, contact details, financial records, health or legal information, stories people told you in confidence. For each kind, ask whether it could be used in a third-party tool at all. If the answer is no, the project has to be designed around that limit, or it should not proceed.

4. What tools do you already have?

Many organizations already pay for software that includes writing help, transcription, or automation, and no one has agreed how to use it. Start there. It is often better to choose one path and use it well than to add another login.

5. What must stay human?

Some work can be drafted by a tool and reviewed by a person. Some work should be done by a person from the first word: a difficult conversation, a decision about someone's standing, a promise, a statement of official advice. Draw that line before you start, not after a mistake.

6. How will you tell if it is working?

Pick a simple measure you can observe in a few weeks: time spent on a recurring task, the number of drafts that needed heavy rewriting, how the team feels about the change. If you cannot tell whether the experiment helped, you will not know whether to continue.

7. What does a careful first experiment look like?

The first project should be small, reversible, and easy to stop. It should use information you are already comfortable sharing, and it should include a review step. A hypothetical example: a five-person office tries AI-assisted first drafts of a weekly public newsletter for one month, with a staff member editing every issue, and then decides whether to continue. That is a better first step than connecting a model to your full email archive.

8. What will you tell the team?

People fill a silence with worry. Say plainly what you are trying, why you are trying it, what will not be automated, and how you will use any time that is saved. If the goal is to make room for better work, say so. If you do not yet know, say that too.

How to use this

You can walk through these questions in a single meeting and write the answers in a shared document. The gaps will tell you whether you are ready to try something small, whether you need a simple use policy first, or whether more basic work comes first — a clearer process, a cleaner contact list, a website that already explains what you do.

If you would like a second pair of eyes on those answers, we are happy to look them over with you. There is no need to arrive with a finished plan.