GLOSSARY TERM
AIPREF
AIPREF (AI Preferences) is a structured file format that allows publishers to express machine-readable preferences about how AI systems may use their content. It enables policy discovery for training, attribution, licensing, and usage restrictions.
What AIPREF defines
- Training permissions - Whether content may be used for model training
- Attribution requirements - How content must be credited when used
- Usage restrictions - Limitations on how content may be accessed or processed
- Licensing terms - Commercial vs non-commercial use policies
- Payment requirements - Pricing for content access or usage rights
How AIPREF works
Publishers place an aipref.txt file in their /.well-known/ directory. AI agents and crawlers can discover and parse this file to understand content usage policies before accessing or processing content.
# Example /.well-known/aipref.txt
training: no
attribution: required
commercial-use: license-required
payment-url: https://example.com/license
contact: rights@example.comAIPREF vs robots.txt
robots.txt
- Controls crawler access
- Binary allow/disallow
- Web indexing focused
AIPREF
- Defines usage policies
- Granular permissions
- AI/ML training focused
Relation to PEAC Protocol
AIPREF focuses on discovering content policies, while PEAC provides the infrastructure for enforcing those policies through payment flows and verifiable receipts. Together, they enable publishers to express preferences and agents to respect them with proof.
Learn more
- Publishers solution - Protect and monetize content with AIPREF
- PEAC Protocol - Verifiable receipts for policy enforcement
- Agentic Web - Infrastructure for autonomous agents