Examples of countries using OECD AI Principles for M&E framework
Countries Using OECD AI Principles for M&E Frameworks: Global Examples
Several OECD adherents integrate the OECD AI Principles into national AI strategies and governance frameworks that directly support monitoring and evaluation (M&E) practices. While explicit "M&E frameworks" branded under the principles are rare, countries like Italy, Korea, the United Kingdom, Japan, and Canada operationalize accountability, transparency, and robustness provisions—creating oversight bodies, algorithmic registries, and policy evaluation tools that M&E professionals can adapt for development contexts.
Introduction
The OECD AI Principles, adopted by all OECD members and other adherents, establish normative standards for trustworthy AI. As of 2024, 41 countries have national AI strategies that reference or align with these principles. While few countries have published documents explicitly titled "M&E frameworks for AI," many have embedded the principles' core values—accountability, transparency, robustness, fairness—into governance mechanisms that enable systematic monitoring and evaluation of AI systems in public administration. This article documents notable country examples and their relevance for M&E practitioners in international development.
OECD AI Principles adherents: All 38 OECD members plus Argentina, Brazil, Egypt, Malta, Peru, Romania, Singapore, and Ukraine. Over 70 jurisdictions reference the principles in policy development, creating a global baseline for AI governance that M&E professionals can leverage.
Which countries integrate OECD AI Principles into M&E-relevant governance?
National AI Strategy (2022–2024) explicitly draws from OECD AI Principles as foundational pillars. The strategy includes governance mechanisms for monitoring AI use in public administration, with accountability and transparency provisions enabling systematic auditing of AI systems in government services. The Italian Digital Agency (AGID) oversees implementation, publishing annual reports on AI adoption and performance—directly supporting M&E of public-sector AI.
National AI Strategy (2019, updated 2022) integrates OECD principles, particularly accountability and transparency. Korea's "AI Government" initiative mandates algorithmic impact assessments for public-sector AI systems, creating traceability and audit trails that enable M&E of AI-driven policy tools. The Korea Information Society Development Institute (KISDI) tracks implementation metrics aligned with OECD standards.
The UK's cross-sectoral AI principles reflect OECD standards. The Alan Turing Institute's "Women in Data Science" program applies fairness and robustness principles to evaluate AI's societal impacts, including gender equity metrics relevant to development M&E. The Centre for Data Ethics and Innovation (CDEI) conducts AI assurance and monitoring pilots across public services, publishing evaluation frameworks aligned with OECD accountability requirements.
Japan's AI Strategy Council explicitly references OECD Principles in its guidelines and deliberations. The government has implemented algorithmic transparency registries for municipal AI tools, enabling citizens and evaluators to monitor AI performance and fairness. The "Digital Agency" oversight framework includes M&E components—risk assessments, periodic reviews, and public reporting—modelled on OECD robustness and safety provisions.
Canada's proposed Artificial Intelligence and Data Act (AIDA) leverages OECD principles, mandating transparency and risk assessments for high-impact AI systems. Public awareness groups conduct workshops to monitor AI policy effectiveness, directly applicable to M&E in federal programs. The Treasury Board's "Algorithmic Impact Assessment" tool—required for all government AI deployments—operationalizes OECD accountability and fairness principles for ongoing evaluation.
Lithuania's National AI Strategy (2019) explicitly aligns with OECD AI Principles, focusing on public-sector AI governance. The strategy created an AI oversight body that monitors AI systems in social services and taxation, publishing evaluation reports on fairness, accuracy, and accountability—directly applicable to M&E of development-relevant programs.
Türkiye's National AI Strategy (2021–2025) integrates OECD principles, establishing a monitoring and evaluation framework for AI in public administration. The strategy mandates periodic reviews of AI systems' compliance with transparency, accountability, and human rights provisions—creating M&E infrastructure that can be applied to development programs.
How can M&E professionals use these country examples?
For monitoring and evaluation specialists in international development, these implementations offer:
- Benchmarking tools: Use national AI strategies and oversight frameworks as models for designing AI governance in development programs.
- Indicator repositories: Extract metrics from algorithmic impact assessments (Canada), gender equity evaluations (UK), and public-sector audits (Korea) to inform M&E indicator development.
- Stakeholder engagement templates: Adapt public awareness and workshop models (Canada, UK) for community-based M&E of AI systems in low- and middle-income countries.
- Risk assessment methodologies: Apply algorithmic impact assessment tools (Canada, Korea) to evaluate AI components in development interventions.
OECD.AI Policy Observatory: Tracking national implementations
The OECD.AI Policy Observatory maintains a live database of over 850 AI policies and strategies from 60+ countries, including detailed country profiles. M&E practitioners can:
- Compare national approaches to AI accountability and monitoring.
- Access case studies on public-sector AI evaluation.
- Download indicators and framework documents for adaptation.
- Track updates on regulatory sandboxes and oversight bodies.
Key takeaways: Country examples for M&E practitioners
- Italy & Korea: Accountability and transparency provisions in national AI strategies enable systematic auditing of AI in government services.
- United Kingdom: Fairness and robustness principles applied to gender equity evaluation and public service monitoring.
- Japan: Algorithmic transparency registries support municipal-level M&E of AI tools.
- Canada: Algorithmic Impact Assessment tool operationalizes OECD principles for federal program evaluation.
- Lithuania & Türkiye: Oversight bodies and compliance reviews create M&E infrastructure for social services and public administration.
- OECD.AI Observatory: Central repository for benchmarking and adapting national M&E frameworks.
Frequently asked questions
Are there countries with explicit "M&E frameworks for AI" based on OECD principles?
Few countries use that exact terminology, but many have embedded M&E-relevant mechanisms—algorithmic impact assessments, oversight bodies, public registries, and performance audits—within their national AI strategies, all aligned with OECD principles.
How can I access these countries' M&E tools and indicators?
The OECD.AI Policy Observatory provides country profiles, policy documents, and links to national strategy texts. Many countries publish their algorithmic impact assessment templates (e.g., Canada's Treasury Board) and oversight reports online.
Which country's approach is most relevant for low-income countries?
Lithuania and Türkiye's strategies—both focused on public administration and social services—offer adaptable models for countries with less mature AI governance infrastructure. Canada's Algorithmic Impact Assessment tool is also widely used as a template.
How do these examples relate to international development M&E?
They provide tested methodologies for evaluating AI systems in health, social protection, and public services—directly applicable to development programs. M&E specialists can adapt their indicators, audit protocols, and stakeholder engagement models.
Authoritative resources
- OECD.AI Policy Observatory – live database of national AI strategies, policies, and M&E-relevant case studies.
- OECD AI Policy Areas – track country progress on accountability, transparency, and robustness provisions.
- Canada's Algorithmic Impact Assessment Tool – operational framework aligned with OECD principles.
- UK National AI Strategy and Action Plan – includes fairness and evaluation components.
- Japan's AI Strategy Council documents – transparency registries and municipal monitoring.
- OECD AI Principles – full text and implementation guidance
Conclusion
While no country has yet published a document explicitly titled "M&E Framework for AI Based on OECD Principles," a growing number of OECD adherents—including Italy, Korea, the UK, Japan, Canada, Lithuania, and Türkiye—have embedded the principles' core values into governance mechanisms that directly support monitoring and evaluation of AI systems in public administration. For M&E professionals working in international development, these national implementations offer a rich source of methodologies, indicators, and templates that can be adapted to evaluate AI-enabled programs in health, social protection, education, and other sectors. The OECD.AI Policy Observatory serves as the central hub for tracking these evolutions and accessing country-level resources.
