The short answer
Decide crawler access from the product and purpose you actually intend to support. Search discovery, assistant retrieval and model-training controls are not necessarily the same. Review each relevant provider's current documentation rather than applying a universal 'AI access' rule inferred from a tool name.
A worked example
A fictional business wants its public help articles discoverable but keeps accounts and unpublished drafts private. The team inventories actual endpoints and controls before changing crawler rules. It does not assume that a robots directive provides access control or that adding an AI text file authorizes private content to be retrieved.
A practical checklist
- List the public content and the discovery products that matter to the business. Keep private account and admin data outside the public-content plan.
- Read the applicable provider documentation and identify the stated role of each crawler or control. Record the documentation date for changing policies.
- Test the deployed rules and authentication boundaries. Document the intended behavior separately from actual discovery observations.
What to avoid
Avoid describing robots.txt as a security barrier or claiming that a special file guarantees AI inclusion. Google's AI features documentation does not require a new AI text file or special schema for those features. Other products need their own current review.
A useful follow-up
Can I use one generic AI rule for every platform?
Do not assume so. Determine the product, purpose and current documented control for each platform you intend to support.
