Tag: AI

Prepare an AI test using real scenarios

An AI test is more useful when it has evaluation criteria. Collect common questions, expected answers and examples where the system should request help. Choose representative cases without unnecessary private information.

Review clarity, accuracy and recognition of limits. Record what changed between versions so an easier question is not mistaken for an improvement. Also test the handoff and the information the advisor receives.

These readings cover AI in customer conversations. Use them to define a supervised pilot and decide which tasks can be automated and which need human review.

• Evaluate an AI chatbot
• Organize service across multiple agents

Evaluate an AI trial with representative examples

Select enquiries that represent your operation and remove personal information before using them in an evaluation. Include common questions, difficult cases and requests the tool should not resolve independently. For each example, write down what an acceptable answer must contain and when asking for human assistance would be the correct outcome.

• Compare responses with a reference reviewed by someone who understands the business.
• Separate factual mistakes from tone problems or instructions that are difficult to understand.
• Record when context is missing and whether the tool asks a useful question to obtain it.
• Repeat the evaluation after changing instructions or updating the information sources.

Choose measures tied to the task: correctly resolved enquiries, necessary corrections or review time. A long response does not demonstrate quality, and one successful demonstration does not represent every conversation. These articles help turn an automation idea into a practical trial with criteria your team can review and improve over time.