Procurement is a governance control
AI risk often enters through products teams did not build. A responsible procurement process helps buyers understand what a vendor system does, what data it uses, how it was tested, and what happens when it fails.
The aim is not to demand impossible certainty. It is to gather enough evidence to decide whether the system fits the intended workflow and whether internal controls can close remaining gaps.
Clarify intended use
Start with the use case. Ask the vendor what the product is designed to do, what it is not designed to do, and which use cases require human review. Then compare those answers with the way your organisation intends to use the product.
A product can be safe for drafting and unsuitable for final decisions. Procurement should capture those boundaries before rollout.
Ask for testing evidence
Buyers should ask how the vendor evaluates accuracy, source support, bias, privacy, misuse, security, and performance drift. The evidence does not need to reveal sensitive implementation details, but it should be specific enough to assess fitness.
Look for evidence that resembles your workflow. A generic benchmark may not prove that the system works on your documents, customers, language, or operational rules.
- What task-specific evaluations has the vendor run?
- How are failures tracked and corrected?
- How often are models, prompts, or retrieval sources updated?
- What incidents or known limitations should customers understand?
Review data terms and access
AI procurement should include clear answers on data use, retention, training, deletion, sub-processors, security controls, and access by vendor staff. Settings should be checked during implementation, not just during contract review.
Buyers should also confirm whether prompts, uploaded files, feedback, and logs are treated differently. These data types may have different privacy and retention profiles.
Check human oversight and audit support
A vendor should be able to explain how humans review output, override recommendations, access logs, export evidence, and pause the system. Audit support matters when the AI system touches customer, employee, or regulated workflows.
If the vendor cannot support review evidence, the buyer may need to build internal logging and approval controls around the product.
Plan the exit
Responsible procurement includes exit planning. Buyers should understand how to export records, delete data, remove integrations, revoke access, and replace the workflow if the vendor becomes unsuitable.
Exit planning is not pessimistic. It is a control that protects continuity and reduces lock-in risk when product behaviour or organisational needs change.
