Resources / Practical guide
How to evaluate a business AI assistant before launch
Evaluate an assistant against realistic questions, authorised actions and deliberate failures. A useful business system must answer from reliable sources, respect access boundaries and accurately report what happened when a provider or tool fails.
Woro Global editorial · Published 4 October 2026
Define the job and its boundaries
Choose one workflow: answering approved policy questions, preparing a draft or helping staff find a record. Name the owner and the actions that need human approval. Keep information retrieval separate from sending a message, charging a customer or modifying an operational system.
Prepare a source-controlled question set
Collect expected answers from approved business documents. Include ordinary questions, ambiguous requests, missing information and outdated documents. Record which source supports each expected answer. Hold out a set of questions until the design is stable so you are not only measuring examples used to tune it.
Test access, not just wording
Use two separate workspaces or access groups and deliberately ask for another group’s records. Try a retrieved document that tells the model to ignore the rules. Check enforcement in the data and tool layers: a model politely refusing once is not proof that an endpoint prevents access.
Inject ordinary failures
Simulate a timeout, an expired token, a missing balance and a provider accepting work before its acknowledgement is lost. The UI should distinguish a draft, a queued task, a confirmed result and an uncertain result. Retry rules should not create duplicate charges or duplicate customer messages.
Measure usefulness and operating cost
Score fact accuracy, unsupported claims, escalation, successful delivery and completion time. Measure latency and provider cost under representative load. Record failures separately from cost estimates; a plausible answer and a low-cost model are not enough if the workflow never finishes.
Roll out in stages
Start with a controlled group and observable outcomes. Review exceptions, logs and customer feedback before increasing automation. Keep a rollback plan, a way to pause actions and a person responsible for updating knowledge. An evaluation report should state what was tested and what remains unverified.
Discuss your workflow
Explore the service or prepare a project brief. Scope and verification depend on your systems and requirements.