AI contracts
9 min read
Updated 2026-05-18
An AI Software Development Contract Checklist
What buyers should clarify before hiring for AI-assisted software work, including scope, data access, model use, evidence, and handoff expectations.
Key takeaways
- check_circleAI-assisted delivery needs clearer scope, data, and ownership language than ordinary feature work.
- check_circleThe contract should explain which AI outputs are acceptable, which human review is required, and what proof will be submitted.
- check_circleBuyers should ask for handoff evidence that lets them operate the software after the facilitator leaves.
Treat AI as part of the delivery method
AI tools can accelerate planning, code generation, testing, documentation, and review. They can also introduce uncertainty around data handling, authorship, security assumptions, and quality control.
The useful contract question is not whether AI appears anywhere in the workflow. It is how AI-assisted work will be reviewed, what data it can touch, and what evidence proves the final software is ready for the buyer.
Clarify the work product
A buyer should know exactly what they are accepting at each milestone. For AI-assisted software delivery, the work product may include more than code.
- task_altProduction or staging application changes.
- task_altPrompts, evaluation notes, or configuration used in AI-enabled features.
- task_altData schemas, migration scripts, model routing settings, or provider configuration.
- task_altTests, QA notes, security assumptions, and known limitations.
- task_altHandoff documentation for running, deploying, and maintaining the system.
Set boundaries for data and tools
AI-assisted projects often involve sensitive product data, customer data, credentials, private repositories, or internal documents. The contract should describe what data can be used, what tools can access it, and which accounts remain under buyer control.
When the project uses external model providers, vector stores, analytics services, or automation tools, the buyer should know which services are involved before approving the milestone.
Require human review and delivery evidence
AI output should not be treated as accepted software by default. The facilitator should still provide inspectable evidence: working URLs, repository changes, tests, logs, screenshots, deployment notes, and a plain-language explanation of what changed.
For AI features, useful review evidence may also include sample inputs and outputs, guardrail notes, fallback behavior, cost assumptions, and failure cases.
How BeUntethered frames AI delivery
BeUntethered uses AI to help structure scope, highlight risks, generate review prompts, and compare submitted evidence against the milestone record. Human facilitators and buyers remain responsible for approval decisions, ownership, and release.