OECD AI Principles

Applies To

Overview

Adopted by the OECD Council on 22 May 2019 and subsequently endorsed by G20 leaders in June 2019, the OECD AI Principles represent the foundational intergovernmental consensus on responsible AI development and deployment. The Principles emerged from extensive multi-stakeholder consultation and were developed by the OECD's Expert Group on AI (AIGO), drawing on input from governments, civil society, academia, and the private sector across 36+ member and partner nations. The framework is organized into two tiers. The first tier articulates five principles for trustworthy AI: (1) inclusive growth, sustainable development, and well-being; (2) human-centered values and fairness; (3) transparency and explainability; (4) robustness, security, and safety; and (5) accountability. The second tier sets out five recommendations directed at governments covering investment in AI R&D, fostering a digital ecosystem for AI, shaping an enabling policy environment, building human capacity, and pursuing international cooperation. The OECD AI Principles do not carry binding legal force in themselves but serve as a normative reference architecture that has been directly incorporated or mirrored in numerous binding and non-binding instruments worldwide, including the EU AI Act, the US Executive Order on Safe, Secure, and Trustworthy AI, and the G7 Hiroshima AI Process. The OECD maintains a live AI Policy Observatory (oecd.ai) that tracks national implementation and policy developments against these principles. A significant operational development is the OECD Framework for the Classification of AI Systems, published as a companion document, which provides a structured methodology for categorizing AI systems by context of use, data modality, and autonomy level-a taxonomy increasingly referenced by regulators globally when delineating risk tiers.

Key Requirements

• •AI systems must be designed to be robust, secure, and safe throughout their lifecycle, with continuous risk assessment and mitigation.
• •Organizations deploying AI must ensure transparency and provide meaningful explanations of AI system outputs to affected stakeholders.
• •AI actors must be accountable for the proper functioning of AI systems and for respect of the other principles, based on their roles.
• •AI systems must respect the rule of law, human rights, democratic values, and diversity, and must include appropriate safeguards against misuse.
• •AI must be designed to foster inclusive growth and sustainable development and must not exacerbate inequality.
• •Governments are recommended to invest in AI research and development that addresses societal challenges.
• •Governments are recommended to develop agile policy and regulatory frameworks that respond to evolving AI capabilities.
• •International cooperation among governments and across stakeholders is explicitly recommended to share knowledge and develop compatible standards.

What Your Organization Must Do

• →Map your organization's AI portfolio against the OECD AI Classification Framework to assign each system a context-of-use, data modality, and autonomy level, establishing a risk tier baseline that satisfies downstream regulators referencing OECD taxonomy.
• →Appoint a named AI accountability owner (such as a Chief AI Officer or designated senior compliance lead) for each material AI system, documenting their role and responsibilities in a governance register that can be produced to regulators in jurisdictions that have adopted OECD-aligned rules.
• →Implement a continuous lifecycle risk assessment process covering robustness, security, and safety for all deployed AI systems, with formal review checkpoints at deployment, major update, and at minimum annually, assigning remediation ownership to business unit heads.
• →Develop and maintain transparency documentation for each AI system affecting external stakeholders, including plain-language explanations of outputs and escalation paths for affected individuals, ensuring materials are updated whenever system logic or training data materially changes.
• →Audit existing AI policies and controls against all five OECD principles and produce a gap analysis within 90 days, prioritizing any gaps in human rights safeguards or misuse prevention that may create exposure under binding downstream instruments such as the EU AI Act.
• →Engage proactively with the OECD AI Policy Observatory (oecd.ai) and relevant industry bodies to monitor national implementation updates, ensuring your governance program remains aligned as member-state regulators translate OECD principles into binding requirements.

Playbook Guidance

Step-by-step implementation guidance for compliance teams.

Frequently Asked Questions

Are the OECD AI Principles legally binding on companies?

No. The OECD AI Principles are a non-binding intergovernmental framework. However, they carry significant practical weight because binding regulations in the EU, US, and G7 jurisdictions directly incorporate or mirror them, meaning non-compliance with the Principles often signals exposure under those downstream instruments.

Which binding regulations are directly based on the OECD AI Principles?

The EU AI Act, the US Executive Order on Safe, Secure, and Trustworthy AI, and the G7 Hiroshima AI Process all explicitly reference or mirror the OECD AI Principles. Organizations using the Principles as a baseline governance framework will find significant overlap with these binding requirements.

Does the OECD AI Classification Framework create risk tiers that regulators actually use?

Yes. The OECD Framework for the Classification of AI Systems categorizes AI by context of use, data modality, and autonomy level. Regulators globally are increasingly referencing this taxonomy when defining risk tiers, making it a practical starting point for any enterprise AI risk assessment process.

Do the OECD AI Principles apply to private sector companies or only to governments?

Both. The framework has two tiers: five principles that apply to all AI actors including private sector developers and deployers, and five recommendations directed specifically at governments. Enterprises in financial services, healthcare, and critical infrastructure are explicitly within scope as AI actors.

What does accountability mean under the OECD AI Principles for an enterprise deploying AI?

AI actors are expected to be accountable for their AI systems functioning in accordance with all five principles, based on their role in the value chain. In practice this means designating a named accountability owner for each material AI system and documenting their responsibilities in a governance register.

How do the OECD AI Principles compare to the UNESCO Recommendation on the Ethics of AI?

Both are non-binding intergovernmental frameworks adopted around the same period, but they differ in scope and emphasis. The OECD Principles focus on trustworthy AI for economic and democratic contexts across 36-plus member states, while the UNESCO Recommendation is broader in cultural scope and places stronger emphasis on human dignity and environmental sustainability.