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OECD.AI Wonk · July 16, 2026

HAIP is transforming transparency from a compliance burden to a competitive advantage

analysis AI ComplianceAgent Security
Why it matters

Salesforce’s Paula Goldman argues on the OECD.AI blog that the Hiroshima AI Process Reporting Framework can give organizations a common language for public AI-risk disclosures across jurisdictions and the expanding agentic-AI value chain.

My takeaway: This is an industry viewpoint rather than an OECD policy position. The practical value is a reusable reporting taxonomy: map each public commitment to an owner, evidence source, model or agent scope, update cadence, and jurisdiction-specific obligation.
Keep exploring

More curated notes connected through AI Compliance and Agent Security.

OpenAI News · framework

OpenAI’s Frontier Governance Framework

OpenAI's 22-page Frontier Governance Framework maps its frontier-model processes to California's Transparency in Frontier AI Act and the EU AI Act's general-purpose AI code. It documents lifecycle risk assessment, cyber-offense and other risk tiers, mitigation and residual-risk decisions, critical-incident handling, security risk management, model reporting, external review, responsibility allocation, and change control.

OWASP GenAI Security Project · guide

OWASP Top 10 for Agentic Applications for 2026

OWASP's community guide organizes agentic-system risk into ten categories, including goal hijacking, tool misuse, identity and privilege abuse, memory poisoning, insecure inter-agent communication, cascading failures, and rogue-agent behavior. It provides a shared taxonomy and mitigation starting point rather than a certification checklist or evidence that a deployed system is secure.

OECD.AI Wonk · guide

A five-step roadmap to closing the AI evaluation gap

The roadmap addresses evaluation results that overstate real-world performance or fail to transfer across deployment contexts. Its five steps balance standardized and local tests, evaluate throughout the lifecycle, build qualified assurance and communication capacity, tailor tests to each value-chain actor and technology, and use a coordinated, trusted process for updating methods.