AI Vendor Evaluation Checklist

Evaluating an AI vendor combines normal software procurement with questions specific to probabilistic systems, meaning systems whose outputs can be wrong. **Accuracy evidence.** Ask what the product was tested on, which metrics were used, and how it performs on your data. The strongest evidence is a pilot on a test set you build from real cases, including hard and unusual ones, scored by your own staff. Ask which foundation model sits underneath, how often it changes, and whether you will be told before its behavior changes. **Data handling.** Ask whether your inputs and outputs are used to train or improve models, how long they are kept, where they are stored and processed, and which subprocessors handle them. Get the answers written into the contract or data processing agreement, not a sales email. **Security.** Request a SOC 2 Type II report, which covers how controls operated over a period of time. A Type I report only describes controls at a single point in time. ISO/IEC 27001 certification is another common signal, and ISO/IEC 42001 is a newer standard for AI management systems. Ask about single sign-on, role-based access, audit logs and penetration testing. If the product reads external content, ask how it defends against prompt injection. **Roadmap and viability.** Ask how dependent the vendor is on a single model provider, what happens if that provider changes its terms, and how the company is funded. **Pricing stability.** Clarify per-seat versus usage pricing, overage charges, and how much notice comes before a price change. **Exit options.** Confirm you can export your data and configurations in usable formats and get written confirmation that your data has been deleted. **Red flags:** - claims of 100 percent accuracy - refusal to run a pilot on your data - vague answers about training on customer data - inability to name subprocessors - contracts that allow price or terms changes without notice