Vendor Management for AI Services

I have managed vendor relationships across every program I have led, but AI service vendors present unique challenges that most vendor management frameworks do not address. Here is what I have learned.

The Evaluation Gap

Traditional vendor evaluation focuses on feature comparisons, SLA commitments, and pricing. AI service vendors require additional scrutiny. How is your data handled? Is prompt data used for model training? What is the model versioning policy? Can a model update break our production integration without notice?

These questions rarely appear in standard RFP templates. I add them to every AI vendor evaluation I run.

Contract Structures Need Updating

Usage-based pricing for AI APIs creates budget unpredictability that fixed-price or time-and-materials contracts do not. I have seen programs blow through quarterly API budgets in six weeks because nobody modeled the token consumption accurately. Now I build cost modeling into the architecture phase, with consumption caps and alerting baked into the contract.

Data processing agreements must be explicit about AI-specific concerns. Where does data go? Is it retained? For how long? Can it be used to train or improve models? These provisions need to be in writing, not assumed based on a privacy policy that can change.

Model stability clauses are something I now negotiate into every AI vendor contract. If a vendor updates their model, we need advance notice and a migration window. A model update that changes output behavior can break downstream systems in ways that traditional API versioning does not anticipate.

Ongoing Governance

I schedule quarterly vendor reviews for AI services that go beyond uptime metrics. We review model performance, cost trends, data handling compliance, and any model updates that occurred. This is more intensive than traditional vendor governance, but the risks justify it.

The PM's Value

Program managers who can navigate AI vendor evaluation, negotiate appropriate contracts, and maintain governance are solving a problem that most organizations are struggling with right now. This is not a nice-to-have skill. It is becoming essential.