Accessible does not mean authoritative

Would you trust an AI answer if it cited the wrong version of your policy? The answer might be clearly written, the source might look familiar and the user might have permission to read it. None of those things proves that the information is current.

As enterprise AI becomes easier to connect to business information, organisations need to ask a practical question: which sources deserve to inform an answer?

Access is only one part of trust

Permissions determine what a person is allowed to see. Information quality determines whether what they see is useful and dependable. These need separate checks.

An accessible policy can be outdated. Two approved files can contradict each other. A relevant passage can leave out the context needed to interpret it. An AI application may retrieve all of them without knowing which one the business considers authoritative.

Making retrieval simpler is valuable, but it does not remove the need to prepare and validate the information being retrieved.

Test the source, as well as the answer

For CIOs and AI delivery partners, source validation should be part of acceptance testing. Start with a business question that matters, such as an employee asking about a current policy or a sales team checking an approved product claim.

1. Identify the authoritative information. Agree who owns it and which version is current.
2. Include difficult examples. Add a superseded policy, a conflicting file or a passage that needs surrounding context.
3. Check what the application retrieves. Does it find the current source, and does the answer make that source clear?
4. Review uncertainty. When sources disagree, does the application flag the conflict rather than present a confident conclusion?

These checks complement permission testing. Passing an access check does not prove that the application is using reliable information.

Give information preparation a clear owner

AIAssure focuses on preparing enterprise information before AI uses it: making information readable, removing duplicate and unnecessary files, and identifying and removing personal and sensitive content.

That preparation supports a better information foundation. The organisation still needs owners who decide which policies, guidance and other sources are authoritative and keep them current. Testing and verification remain necessary because better information cannot eliminate hallucinations.

Before connecting another knowledge source, ask: who owns the authoritative answer when two sources disagree? A clear answer to that question can make the next AI project easier to test and more useful in practice.

Adapted from Stewart Connors’ LinkedIn post. Read the original post ↗