Provider-specific configurations governing crawler access or content use for AI training vs live search discovery.
AI access controls are the provider-specific settings and technical mechanisms used to manage how automated systems access or use content. They can address different purposes, including search discovery and training-related collection. There is no single switch whose meaning is identical across all AI providers.
The first step is to define the desired outcome. Keeping confidential content private requires actual access control. Expressing a crawling preference for a public page is a different task, and limiting a search preview is different again. A rule designed for one purpose should not be assumed to accomplish the others.
Implementations can involve crawler-specific robots.txt rules, provider-supported directives or infrastructure controls. Their effectiveness and side effects depend on the system. A broad firewall block may prevent a useful search crawler as well as unwanted traffic, while a voluntary instruction does not force every third party to comply.
Takeaway: Decide which content, provider and use you want to control before changing settings. Document the intent and test the actual effect rather than relying on a generic AI-blocking label.
Example
A training company wants public course descriptions discoverable but keeps paid lesson materials behind authentication. It handles those as separate requirements. It does not expose the lesson files publicly and assume a crawler preference will provide the same protection as a login.
What to check
Review the provider’s current documentation and the site’s hosting rules together. Preserve a record of changes and check that normal visitors and intended search services still work. Avoid assuming an opt-out removes previously collected information or controls sources hosted on other websites.
For more detail, see OpenAI crawler controls.