How to evaluate AI business software

Find the business action behind the answer

An application may write an excellent paragraph explaining that a customer owes money. If that paragraph was produced from an old note, the quality of the writing says little about the current balance. Ask which source establishes the amount and where a confirmed payment would change it.

ChatGPT company knowledge illustrates that general assistants can use connected organizational sources. The application category alone therefore does not tell you whether context is available. What matters is how a product retrieves, checks and changes the relevant information.

Inspect the review boundary

A proposed change should be understandable before it becomes a business commitment. The operator should see the customer, affected order, value and source, with ambiguous details separated from confirmed ones. This is especially useful when a sentence mentions several people or more than one amount.

List the details that would cause trouble if wrong. Start with customer identity, quantity, amount, deadline and delivery address. Then test an ambiguous message and a correction.

Staff should find the resulting record easy to inspect and repair. Keep enough source information to explain why it changed.

Try to break one believable workflow

In an illustrative case, a customer says, “Received the sample. Will send 12,000 tomorrow.” A system must not record money as settled simply because the amount is clear.

Now change the message to “Sent 12,000” and attach an unrelated screenshot. The evidence still requires checking against the appropriate financial record.

Next, submit the same update twice. Finally, correct the customer.

These tests expose errors that a friendly demo rarely shows. Record what the operator sees and what another employee can retrieve afterward.

Inspect the destination with an ordinary account

Use the account of the employee who will do the work. An administrator demonstration can conceal missing access or give an assistant authority that normal staff should not have. After approval, open the destination record directly and check it.

This verifies the business result directly. It also reveals whether staff can investigate their own mistakes.

Use risk to decide how much automation belongs here

NIST’s AI Risk Management Framework provides a general structure for managing AI risks. Match the checks to the consequences of a wrong action. Give consequential changes an explicit owner and a clear correction path.

A draft internal summary and a supplier payment have very different consequences. Start with low-impact capture and retrieval, then expand only when responsibilities are clear. Do not equate fewer clicks with better operation if the saved record becomes harder to inspect.

1. Name the exact business fact or action the software should produce.
2. Write down one correct example and three plausible failures.
3. Check the final record, not only the assistant’s confirmation message.
4. Test a correction with a second employee before expanding the workflow.
5. Keep financial settlement and external communication under the appropriate authority.