OpenAI Outlines Standards for the Next Phase of AI

On September 21, 2026, OpenAI described its priorities for the next phase of AI progress, including automated AI research, scientific benefits and more capable personal AI.

As systems become more powerful, shared methods for evaluation and safety become increasingly important. Without comparable standards, customers may struggle to assess risks across products and vendors.

THE PURPOSE OF THE STATEMENT: On September 21, 2026, OpenAI outlined priorities for a more capable generation of AI. Its ambitions include automated AI research, broader scientific benefits and highly capable personal AI. These are forward-looking objectives, not a claim that every capability has already been achieved.

WHAT AI STANDARDS CAN COVER: Standards may address performance measurement, safety evaluation, incident reporting and interoperability. Two vendors can both claim strong performance while testing under different conditions. Shared methods could make results easier to compare.

REPRODUCIBLE EVALUATIONS: AI results may change with datasets, prompts and execution environments. A single successful benchmark run does not guarantee stable performance in production. Documenting test conditions and enabling independent replication can help both researchers and buyers.

CAPABILITY AND RISK TESTING: More advanced systems may use tools, plan tasks and handle specialized knowledge. These capabilities require evaluation beyond writing quality or question answering. Measures of usefulness and measures of potential harm should not be treated as interchangeable.

AUTOMATED AI RESEARCHERS: OpenAI identifies more automated scientific research as an important goal. Such systems could help explore hypotheses, design experiments and synthesize literature. Yet AI-generated ideas still require empirical testing and independent scrutiny.

TURNING SCIENCE INTO PUBLIC BENEFIT: Faster research does not automatically mean widely shared benefits. Validation, dissemination and practical deployment matter. Some findings may need restricted access because of intellectual property or safety concerns, creating a difficult balance between openness and protection.

MORE CAPABLE PERSONAL AI: Powerful assistants could support learning, creative work and organization. Greater ability also increases the importance of understandable limitations and user intervention. Trustworthy systems should make it possible to review and correct consequential actions.

WHY INTERNATIONAL COOPERATION MATTERS: AI services and research cross national borders. Common terminology and comparable testing practices could reduce fragmentation. Countries still differ in legal systems and priorities, so cooperation does not necessarily imply identical regulation.

WHAT BUSINESSES GAIN: Shared evaluation criteria can make procurement comparisons more meaningful. A buyer could ask vendors for similar evidence about reliability, safety and performance. Conformance to a standard, however, does not prove that a product fits a specific workflow.

STANDARDS VERSUS LAW: Technical standards may be developed by industry groups or standards bodies. Laws are enacted through governmental processes and can create binding duties. OpenAI's support for standards should not be mistaken for the adoption of a complete international rulebook.

OPENNESS AND SENSITIVE FINDINGS: Safety testing may reveal weaknesses that would be risky to disclose in full. Excessive secrecy, however, can prevent independent verification. A credible framework needs procedures for responsible information sharing.

WHAT COMES NEXT: The important questions are who develops standards, which measures become comparable and how evaluation evidence is shared. The value of standardization depends on whether its principles become practical methods that researchers, developers and customers can use.

The statement outlines a direction for standards and cooperation; it does not mean a complete set of international standards has already been adopted.