Buyer guide · Scoping
The AI statement of work, and what makes a good one
A statement of work is the document that turns an AI idea into an agreement: scope, data, success metrics, timeline, price, and ownership. Get it right and the project delivers; leave it vague and it ends in a dispute over what was promised. Here is what a solid AI SOW includes and where they usually go wrong.
The checklist
Six things a good AI SOW nails down
Problem and objective
The business problem in one paragraph and the measurable outcome the project targets. If this is vague, everything downstream is negotiable later, which is how budgets blow up.
Scope and out of scope
What the build includes, and just as important, what it does not. A named out-of-scope list is the single best defense against scope creep.
Data requirements
Which data the model needs, who provides it, and in what shape. AI projects live or die on data access, so this belongs in the document, not in a surprise later.
Success criteria
The metric and the threshold that count as done: accuracy, resolution rate, time saved. Without a number, acceptance becomes an opinion.
Timeline and milestones
Phases with dates and what is delivered at each. For AI, expect an evaluation milestone before full rollout, so you see results on real data before committing further.
Pricing, IP, and operation
The pricing model, who owns the resulting code and data, and how the system is maintained after launch. AI needs ongoing operation, so a build-only SOW with no operation plan is half a plan.
Why AI is different
An AI SOW is not a software SOW with the word AI added
Regular software does what it is coded to do. An AI system performs to a measured level on your data, which is why an AI statement of work has to be explicit about two things a normal one skips: the data it depends on, and the metric that counts as success. Add an evaluation milestone before full rollout and an operation plan after it, and you have a document that protects both sides.
How we work
A good SOW is the output of scoping, not a template
At Kemeny Studio the statement of work comes out of a paid audit: we review your workflow and data, pick the highest-ROI slice to build first, and hand you a scoped SOW with a fixed price. Start with an audit, see how we work, or check what an AI build costs.
FAQ
Common questions
What is a statement of work (SOW) for an AI project?
An AI statement of work is the document that defines the project: the problem, the scope and what is out of scope, the deliverables, the data required, the success metrics, the timeline, and the pricing and ownership terms. It turns a vague idea into an agreement both sides can hold each other to.
How is an AI SOW different from a regular software SOW?
Two things. First, data: an AI project depends on data access and quality that a normal build does not, so the SOW must nail down who provides what. Second, acceptance: model performance is measured, not assumed, so the document needs explicit metrics and an evaluation milestone, plus an operation plan, because models need ongoing tuning.
What is the biggest mistake in an AI statement of work?
Leaving success undefined. If the SOW does not state the metric and the threshold that count as done, every party remembers a different promise, and the project ends in dispute instead of delivery. The fix is a number everyone signs off on before work starts.
How do I get a good SOW for my AI project?
A good SOW is the output of proper scoping, not a template you fill in blind. A paid audit reviews your workflow and data, picks the highest-ROI slice to build first, and produces a scoped statement of work with a fixed price, so you start from an agreement instead of an estimate.
Next step
Stop hiring. Deploy an AI agent.
Book your AI audit. In 10 days you'll know which workflows to hand off to an AI agent, the expected savings, and a fixed-price agent build scope. We build it. Then we run it.
20 minutes. No pitch deck. No commitment.