Helping build shared standards for advanced AI

For AI practitioners and learners, this move signals that the era of isolated safety testing is coming to an end in favor of interoperable, third-party verification. Establishing a shared technical language is essential for mitigating systemic risks like cyber threats and biological misuse while ensuring that innovation does not outpace our ability to secure these systems. By aligning national and international assessment criteria, the industry is creating a more predictable landscape for developers and regulators alike.

OpenAI has helped launch the Appia Foundation, hosted by the Linux Foundation, to translate international standards into practical, modular assessment criteria across the AI value chain. This initiative aims to create a missing trust layer where third parties can verify model conformity using reusable, evidence-based data. This effort complements existing governance blueprints and partnerships with institutions like the U.S. CAISI and UK AISI, effectively formalizing how frontier risks are evaluated and reported.

Organizations should prioritize aligning their internal safety protocols with emerging interoperable standards to ensure long-term compliance and credibility. Leadership teams must move beyond internal testing by integrating independent, third-party assessment frameworks into their development lifecycle. Practitioners should familiarize themselves with these evolving evaluation harnesses and reporting requirements to ensure their systems remain compatible with the global infrastructure currently being built.