# Want AI to find your site, but not train on it? Keep those choices separate. OpenAI announced support for a shared training-preference signal on 30 October. Implementation is still ahead. Here is what website owners can check now. Published: 2026-10-31 | Updated: 2026-10-31 Author: /init editorial Method: AI-assisted, source-checked Canonical: https://init.news/notes/ai-training-preferences-search-access/ For: Business website owners, independent publishers and studios responsible for AI discovery and content-use preferences. Question: AI training opt out without blocking ChatGPT search ## The answer Do not replace working crawler rules with a new draft signal. OpenAI's 30 October 2026 announcement says it plans to implement a shared training-preference signal in the coming months while retaining its existing controls. Its current documentation treats OAI-SearchBot search access and GPTBot training preferences independently. Decide the two purposes separately, review the actual robots.txt and access rules, and wait for implementation details before relying on the proposed shared signal. ## What you will leave with A dated distinction between an announced commitment, a draft specification and deployed crawler controls, with a small website-policy review worksheet. - Search access and training preferences are different decisions. - The shared signal is a draft with implementation still planned by OpenAI. - Keep current controls and verify support before relying on the supplementary signal. ## A simpler signal is coming, not a new ranking shortcut You want customers to find the work you publish. That does not automatically settle whether you want the same work used for model training. On 30 October, OpenAI committed to honoring a common robots.txt training-preference signal. It aims to implement it in the coming months and says existing crawler controls will continue. This is an announcement of intended support, not evidence that the new behavior is already operating. [1] The practical change is a possible reduction in policy-maintenance work across participating providers. It is not a promise of search inclusion, citations or higher rankings. ## Three things that should not share one checkbox Purpose | What the inspected sources say | Owner decision --- | --- | --- Search discovery | OAI-SearchBot controls automatic crawling for ChatGPT search. [2] | Should these public pages be eligible for discovery? Foundation-model training | GPTBot expresses a separate training preference. [2] | What content-use preference does the publisher choose? User-requested fetching | ChatGPT-User acts on user requests; robots.txt may not apply. [2] | Which information should be public at all? OpenAI's documentation explicitly permits allowing its search crawler while disallowing its training crawler. That describes OpenAI's controls, not a universal contract for every AI application. Private information still belongs behind actual access controls, not in a public page with a crawler instruction. [2] ## What the draft adds The linked 30 October individual Internet-Draft proposes the policy token __usage_ai-training in a User-Agent group, using ordinary robots.txt path rules. Its status page explicitly says it is not IETF-endorsed. Treat it as work in progress, not an adopted standard or a legal determination about content rights. [3] Read the draft's Introduction and Independence from Crawler Rules section. They explain why a usage preference is distinct from permission to fetch. You do not need to rewrite the site this afternoon to follow the development. ## Make the next review small - Write down the desired policy separately for public search and training. - Record the current robots.txt URL, relevant groups, CDN rules, approval owner and inspection date. - Identify any mismatch between the intended policy and current configuration. Do not infer access from the file alone. - Keep a copy of the previous configuration and a rollback owner for any approved change. - Recheck the provider's implementation announcement before treating the new signal as effective. If discovery is the problem, first ask whether the public page can be fetched and whether it answers a real question. A policy change will not repair a missing answer, an inaccessible page or an unclear offer. ## What would count as evidence? After an authorized change, inspect the actual served policy and available access logs. Measure search appearances and visits separately. A successful fetch is not proof of citation; a citation is not proof of a customer enquiry. No crawler-policy experiment or visibility gain was measured for this note. ## Try one thing Ask your website maintainer for the current robots.txt and a two-row record: the desired search policy and the desired training policy. Confirm who may approve changes before touching production. ## Sources [1] [OpenAI: Making it easier for websites to express AI training preferences, 30 October 2026](https://openai.com/index/helping-websites-express-ai-training-preferences/): Announced future implementation and preservation of existing crawler controls.; checked 2026-10-31 [2] [OpenAI: Overview of OpenAI Crawlers](https://developers.openai.com/api/docs/bots): Independent search/training settings and the separate user-initiated fetching role.; checked 2026-10-31 [3] [Machine-Readable Training Preference Signal, individual Internet-Draft 00](https://datatracker.ietf.org/doc/draft-kelley-aipref-training-preference-signal/): 30 October draft status, policy-token mechanism and separation from crawler rules.; checked 2026-10-31 ## Related guides - https://init.news/notes/seo-aeo-geo-implementation/ - https://init.news/notes/ai-citation-observation-protocol/ - https://init.news/notes/website-handoff-ownership-maintenance/