# AI Governance Library
> A library of trusted AI governance resources — reports, laws, guides, and frameworks on accountability, risk, compliance, ethics, and regulation. Curated by Jakub Szarmach
Public Ghost content for AI and LLM tooling. Use `/llms-full.txt` for consolidated page and post context.
Append `.md` to any post or page URL to get the content in Markdown (for example, `/example-post.md`).

## Pages
- [About AI Governance Library](https://www.aigl.blog/about.md) - This Library was created with a goal to promote higher standards in how we teach, share, and apply AI governance. Too many resources out there are either too academic to act on, too vague to trust, or quietly built to push a product or consulting service. I aim to make this library different. AIGL…
- [HOME](https://www.aigl.blog/home.md) - Hey! This is AIGL It is soo cool, I am testing if I can setup a custom homepage.
- [Privacy Policy](https://www.aigl.blog/privacy-policy.md) - Last updated: September 09, 2025 This Privacy Policy describes Our policies and procedures on the collection, use and disclosure of Your information when You use the Service and tells You about Your privacy rights and how the law protects You. We use Your Personal data to provide and improve the Se…

## Posts
- [AIGL Newsletter #26: OWASP Special](https://www.aigl.blog/aigl-newsletter-26-owasp-special.md) - Explore the OWASP AI security ecosystem in one curated collection: from LLM and agentic AI risks to MCP security, threat modeling, governance, and incident response. Discover practical frameworks, standards, and tools built through global collaboration.
- [AIGL Newsletter #25: The Right Shadow](https://www.aigl.blog/aigl-newsletter-25-measure-what-matters.md) - What looks like a fresh start may carry the consequences of what came before. From bouncing universes to agentic AI, the hard governance problem is increasingly what survives across the boundary.
- [Cybersecurity Budgets Are Growing Fast. AI Threats Are Growing Faster](https://www.aigl.blog/cybersecurity-budgets-are-growing-fast-ai-threats-are-growing-faster.md) - BCG report, dated August 2026, drawing on its CISO surveys of 2025 and 2026 to track cybersecurity budget growth, AI-enabled threats, adoption of AI-specific security controls and vendor consolidation.
- [The Offensive Frontier: AI as the Attacker: A New Cyber Weapon Index and the Strategic Imperative to Accelerate Agentic AI Offense and Defense](https://www.aigl.blog/the-offensive-frontier-ai-as-the-attacker-a-new-cyber-weapon-index-and-the-strategic-imperative-to-accelerate-agentic-ai-offense-and-defense.md) - Booz Allen Hamilton's Cyber Weapon Index benchmark scores 18 U.S. and Chinese frontier AI models on autonomous offensive cyber capability, with an addendum re-testing newly released models days later.
- [AI Risk Management Toolkit: guidance](https://www.aigl.blog/ai-risk-management-toolkit-guidance.md) - UK government guidance from DSIT that helps public sector teams identify, assess, score and treat AI risks across the AI lifecycle, with risk appetite levels, quantification scales, identification questions and treatment suggestions in four appendices.
- [AIGL Newsletter #24: What Survives the Boundary?](https://www.aigl.blog/aigl-newsletter-24-from-approval-to-control.md) - What looks like a fresh start may carry the consequences of what came before. From bouncing universes to agentic AI, the hard governance problem is increasingly what survives across the boundary.
- [AIGL v 2.0](https://www.aigl.blog/aigl-v-2-0.md) - Thank you for being here. Thank you for reading, sharing, contributing, and most of all, for actually using this library. You visiting this space is what keeps me going. And you deserve the best. You deserve a library with proper filters and no orphaned duplicates. Like, you know, an actual catalog…
- [European Union Artificial Intelligence Act: a guide](https://www.aigl.blog/european-union-artificial-intelligence-act-a-guide.md) - A law firm guide to Regulation (EU) 2024/1689, dated 7 April 2025, mapping the AI Act's scope, prohibited practices, high-risk and general-purpose AI obligations, transparency duties, sandboxes, enforcement and governance by article and application date.
- [A Taxonomy of Trustworthiness for Artificial Intelligence: Connecting Properties of Trustworthiness with Risk Management and the AI Lifecycle](https://www.aigl.blog/a-taxonomy-of-trustworthiness-for-artificial-intelligence-connecting-properties-of-trustworthiness-with-risk-management-and-the-ai-lifecycle.md) - CLTC white paper introducing a taxonomy of 150 properties of trustworthiness for AI, organised by the seven NIST AI RMF lifecycle stages, each with guiding questions and relevant NIST AI RMF subcategories.
- [The 12 Essential Questions for Responsible AI Governance: Unifying EU AI Act & NIST AI RMF](https://www.aigl.blog/the-12-essential-questions-for-responsible-ai-governance-unifying-eu-ai-act-nist-ai-rmf.md) - A TechBetter white paper that distils the EU AI Act and the NIST AI Risk Management Framework into four governance pillars and 12 essential questions, each mapped to the relevant articles and RMF items, with a five-level maturity model.
- [The AI Impact Navigator: A guide for leaders to steward AI impact — socially, environmentally, and economically](https://www.aigl.blog/the-ai-impact-navigator-a-guide-for-leaders-to-steward-ai-impact-socially-environmentally-and-economically.md) - A framework from Australia's National AI Centre that helps company leaders assess, measure and report the social, environmental and economic impact of their AI use, through four dimensions, a 20-indicator survey and planning and reporting templates.
- [The State of AI Safety in China: Spring 2024 Report](https://www.aigl.blog/the-state-of-ai-safety-in-china-spring-2024-report.md) - Concordia AI's Spring 2024 report surveys frontier AI safety in China, covering technical research trends and key groups, international and domestic governance developments, and lab and industry practices from October 2023 to May 2024.
- [Top 10 operational impacts of the EU AI Act](https://www.aigl.blog/top-10-operational-impacts-of-the-eu-ai-act.md) - A compiled ten-part IAPP article series on the operational impacts of the EU AI Act, covering scope and definitions, risk categories, obligations for providers and non-providers of high-risk systems, general-purpose AI models, governance, assurance, enforcement and GDPR alignment.
- [Outlook Study on Artificial Intelligence and Gender](https://www.aigl.blog/outlook-study-on-artificial-intelligence-and-gender.md) - UNESCO's Women for Ethical AI outlook study presents evidence on women's underrepresentation in AI, gender gaps in AI policy and AI risks to gender equality, and sets out nine recommendations tied to the UNESCO Recommendation on the Ethics of AI.
- [USPTO Artificial Intelligence Strategy](https://www.aigl.blog/uspto-artificial-intelligence-strategy.md) - The USPTO's January 2025 AI strategy sets out its AI vision, mission and five focus areas—covering AI-related IP policy, agency AI capability, responsible use, workforce expertise and collaboration—with concrete actions under each.
- [Navigating the AI Frontier: A Primer on the Evolution and Impact of AI Agents](https://www.aigl.blog/navigating-the-ai-frontier-a-primer-on-the-evolution-and-impact-of-ai-agents.md) - A World Economic Forum white paper, produced with Capgemini, defining AI agents, tracing their evolution from rule-based systems to multi-agent systems, and setting out technical, socioeconomic and ethical risks with possible mitigation measures.
- [What Should be Internationalised in AI Governance](https://www.aigl.blog/what-should-be-internationalised-in-ai-governance.md) - A research paper asking which AI policy issues need international coordination, with a framework that separates the demand for internationalisation from its supply and applies it to data, compute and frontier AI governance.
- [Workplace AI in China: The changing profile of work and labour](https://www.aigl.blog/workplace-ai-in-china-the-changing-profile-of-work-and-labour.md) - A Chatham House research paper by Nikki Sun on how AI tools are used across recruitment, management, evaluation and dismissal in Chinese workplaces, and how algorithmic management shifts power to employers. Based on over 50 interviews and a review of more than 20 AI products.
- [The Defence AI Playbook](https://www.aigl.blog/the-defence-ai-playbook.md) - A Ministry of Defence playbook from the Defence AI Centre illustrating eight areas where AI is under development or in use across UK Defence, each paired with a solution and a common challenge such as data quality, edge processing or assurance.
- [AI Governance around the world – Country Profile: China](https://www.aigl.blog/ai-governance-around-the-world-country-profile-china.md) - A country profile from The Alan Turing Institute tracing China's primary-source AI policy, regulation and standardisation from the 2017 New Generation AI Development Plan to July 2026, including provincial initiatives.
- [AI governance around the world: Country profile: Canada](https://www.aigl.blog/ai-governance-around-the-world-country-profile-canada.md) - Country profile from The Alan Turing Institute's AI governance around the world series, describing Canada's regulatory approach and standardisation system, from the halted AI and Data Act to the Standards Council of Canada's ISO 42001 pilot.
- [Trustworthy and Ethical Assurance of Digital Health and Healthcare: Supporting an assurance ecosystem for data-driven technologies in health and healthcare](https://www.aigl.blog/trustworthy-and-ethical-assurance-of-digital-health-and-healthcare-supporting-an-assurance-ecosystem-for-data-driven-technologies-in-health-and-healthcare.md) - A report introducing Trustworthy and Ethical Assurance (TEA), an argument-based method and open-source platform for documenting assurance cases, applied to fairness and health equity in digital health and healthcare, with two case studies and next steps.
- [AI Governance around the world: Country Profile: European Union](https://www.aigl.blog/ai-governance-around-the-world-country-profile-european-union.md) - A country profile of the European Union's approach to AI regulation and standardisation, covering the EU AI Act, the GPAI Code of Practice, the AI Pact and the European standardisation system. Published by The Alan Turing Institute.
- [AI governance around the world: Country profile: India](https://www.aigl.blog/ai-governance-around-the-world-country-profile-india.md) - Country profile of India's approach to AI governance, published by The Alan Turing Institute, covering national policy initiatives, laws, sectoral measures and the standardisation system.
- [AI Agents in Action: Foundations for Evaluation and Governance](https://www.aigl.blog/ai-agents-in-action-foundations-for-evaluation-and-governance.md) - A World Economic Forum white paper, produced with Capgemini, offering foundations for evaluating and governing AI agents: technical architecture, a functional classification, evaluation criteria, a five-step risk assessment and progressive governance.
- [GenAI Incident Response Guide](https://www.aigl.blog/genai-incident-response-guide.md) - A guide from the OWASP Gen AI Security Project on preparing for, detecting, containing and recovering from incidents involving generative AI. It defines AI incidents and gives event-specific guidance for attacks on AI systems, supply chains and third-party model providers.
- [Guidelines on the Responsible Implementation of Artificial Intelligence Systems in Journalism](https://www.aigl.blog/guidelines-on-the-responsible-implementation-of-artificial-intelligence-systems-in-journalism.md) - Council of Europe guidelines, adopted by the CDMSI in November 2023, on how media organisations, technology providers, platforms and States should implement AI in journalism in line with human rights, from decision-making and procurement to oversight, disclosure and a procurement checklist.
- [Governing with Artificial Intelligence: Are governments ready?](https://www.aigl.blog/governing-with-artificial-intelligence-are-governments-ready-2.md) - OECD policy paper examining the benefits, risks and governance of AI use in the public sector, based on 71 use cases from 31 countries, and proposing a preliminary framework of enablers, guardrails, engagement and impact.
- [Taxonomy of Failure Mode in Agentic AI Systems](https://www.aigl.blog/taxonomy-of-failure-mode-in-agentic-ai-systems.md) - A Microsoft AI Red Team taxonomy of safety and security failure modes in agentic AI systems, combining a failure mode and effects analysis with mitigation guidance and a memory poisoning case study.
- [State of AI Policy in Africa 2025](https://www.aigl.blog/state-of-ai-policy-in-africa-2025.md) - A twelve-point rubric assessment of AI policy maturity across twenty African countries as of October 2025, scoring policy design, implementation capacity, governance and accountability, and external engagement out of 24.
- [Frontier Safety Framework Version 2.0](https://www.aigl.blog/frontier-safety-framework-version-2-0.md) - Google DeepMind's Frontier Safety Framework version 2.0 sets out protocols for detecting Critical Capability Levels in frontier models and applying security and deployment mitigations, with tables pairing misuse and deceptive alignment thresholds to mitigations.
- [Frontier Safety Framework](https://www.aigl.blog/frontier-safety-framework-2.md) - Google's Frontier Safety Framework Version 3.1 sets out Critical Capability Levels and Tracked Capability Levels for misuse (CBRN, cyber, harmful manipulation) and ML R&D and misalignment risks, with security and deployment mitigations, a risk management process and governance.
- [Microsoft Responsible AI Standard, v2: General Requirements for External Release](https://www.aigl.blog/microsoft-responsible-ai-standard-v2-general-requirements-for-external-release.md) - Microsoft's second version of its Responsible AI Standard, setting out the general requirements its AI systems must meet across accountability, transparency, fairness, reliability and safety, privacy, security and inclusiveness goals.
- [AI Assurance: A Repeatable Process for Assuring AI-enabled Systems](https://www.aigl.blog/ai-assurance-a-repeatable-process-for-assuring-ai-enabled-systems.md) - MITRE executive summary of a technical paper setting out a four-step AI assurance process—discovering assurance needs, characterizing and prioritizing risks, evaluating risks, and managing risks—that produces an AI Assurance Plan.
- [AI Assurance – Challenges, Maturity, and Paths Forward](https://www.aigl.blog/ai-assurance-challenges-maturity-and-paths-forward.md) - MITRE policy wrapper summarising its 6 June 2024 AI Assurance Summit, where more than 150 federal attendees discussed AI assurance challenges, technical capability maturity and paths forward including assurance labs and automation.
- [A Sensible Regulatory Framework for AI Security](https://www.aigl.blog/a-sensible-regulatory-framework-for-ai-security.md) - MITRE paper proposing elements of a US regulatory framework for AI security, organised around three categories of AI application — subsystem, human augmentation and agency — with twelve recommendations on assurance, auditability, transparency and critical infrastructure.
- [The AI Assurance Landscape (v1.0): Toward a Standardized Framework of Unique and Differentiated AIA Concepts](https://www.aigl.blog/the-ai-assurance-landscape-v1-0-toward-a-standardized-framework-of-unique-and-differentiated-aia-concepts.md) - MITRE report (v1.0) presenting the AI Assurance Landscape, a concept map of 11 AIA categories and 66 specific assurance needs synthesised from roughly 50 existing AI assurance frameworks and reports, with an accompanying glossary of definitions and cross-framework mappings.
- [Assuring AI Security and Safety Through AI Regulation](https://www.aigl.blog/assuring-ai-security-and-safety-through-ai-regulation.md) - MITRE Center for Data-Driven Policy presidential transition memo proposing nine data-driven recommendations for a US regulatory framework covering AI assurance, auditability, transparency, incident sharing and governance.
- [Risk Sources and Risk Management Measures in Support of Standards for General-Purpose AI Systems](https://www.aigl.blog/risk-sources-and-risk-management-measures-in-support-of-standards-for-general-purpose-ai-systems.md) - An arXiv preprint from the AI Standards Lab presenting a catalog of risk sources and risk management measures for general-purpose AI systems across development, evaluation, deployment, cybersecurity and impact stages.
- [Risk Discovery Protocol for AI Assurance (v1.0): Guidance for Administering the Protocol](https://www.aigl.blog/risk-discovery-protocol-for-ai-assurance-v1-0-guidance-for-administering-the-protocol.md) - MITRE guidance for administering the Risk Discovery Protocol for AI Assurance (RDP-AIA), a four-phase interview-based methodology that helps teams unpack a mission problem and AI solution, elicit AI assurance needs, and prioritize them by assessed risk in a Priority Report.
- [Strategic review of the whole of Australian Government single seller arrangements](https://www.aigl.blog/strategic-review-of-the-whole-of-australian-government-single-seller-arrangements.md) - Independent strategic review prepared by SolsticeIT for the Digital Transformation Agency, assessing whether the Australian Government's Single Seller Arrangements with AWS, IBM, Microsoft, Oracle, Rimini Street and SAP remain fit-for-purpose and deliver value.
- [Policy for the responsible use of AI in government](https://www.aigl.blog/policy-for-the-responsible-use-of-ai-in-government.md) - Australian Government policy setting out how agencies adopt and use AI, with an 'enable, engage and evolve' framework, mandatory requirements on accountable officials, high-risk use case notification and AI transparency statements, plus a risk matrix.
- [Policy for the responsible use of AI in government](https://www.aigl.blog/policy-for-the-responsible-use-of-ai-in-government-2.md) - Australian Government policy (version 2.0) setting principles and mandatory requirements for agencies' use of AI, covering strategy and oversight, preparedness and operations, and AI use case impact assessment.
- [Responsible AI in the automotive industry: Techniques and use cases](https://www.aigl.blog/responsible-ai-in-the-automotive-industry-techniques-and-use-cases.md) - A joint Accenture and DFKI paper on Responsible AI in the automotive industry. It sets out Accenture's seven Responsible AI principles, links them to AI maturity, introduces neuro-explicit AI and works through seven autonomous driving use cases.
- [National framework for the assurance of artificial intelligence in government: A joint approach to safe and responsible AI by the Australian, state and territory governments](https://www.aigl.blog/national-framework-for-the-assurance-of-artificial-intelligence-in-government-a-joint-approach-to-safe-and-responsible-ai-by-the-australian-state-and-territory-governments.md) - A framework from the Australian, state and territory governments setting out a nationally consistent approach to assuring government use of AI. It defines cornerstones of assurance and maps practices to Australia's eight AI Ethics Principles.
- [Explanatory Report to the Council of Europe Framework Convention on Artificial Intelligence and Human Rights, Democracy and the Rule of Law](https://www.aigl.blog/explanatory-report-to-the-council-of-europe-framework-convention-on-artificial-intelligence-and-human-rights-democracy-and-the-rule-of-law.md) - Article-by-article commentary on the Council of Europe Framework Convention on Artificial Intelligence and Human Rights, Democracy and the Rule of Law (CETS 225), published by the Council of Europe.
- [Guidance for AI adoption: implementation guidance](https://www.aigl.blog/guidance-for-ai-adoption-implementation-guidance.md) - Australian Government implementation guidance setting out six responsible AI adoption practices for developers and deployers, covering accountability, risk management, transparency, testing and human control, with definitions and a VAISS crosswalk.
- [Governing with Artificial Intelligence: The State of Play and Way Forward in Core Government Functions](https://www.aigl.blog/governing-with-artificial-intelligence-the-state-of-play-and-way-forward-in-core-government-functions-2.md) - An OECD report analysing how governments develop and use AI across core public functions, based on 200 use cases and dozens of governance approaches. It sets out opportunity areas, five risk types specific to government, and a framework of enablers, guardrails and engagement.
- [Red Teaming Artificial Intelligence for Social Good: The PLAYBOOK](https://www.aigl.blog/red-teaming-artificial-intelligence-for-social-good-the-playbook.md) - A UNESCO playbook, written with Humane Intelligence, that guides organizations and communities through designing and running red teaming exercises on generative AI models to expose bias, stereotypes and technology-facilitated gender-based violence.
- [Digital Government Outlook 2026: From Foundations to Transformational Impact](https://www.aigl.blog/digital-government-outlook-2026-from-foundations-to-transformational-impact.md) - First OECD Digital Government Outlook, assessing digital government across 36 OECD members and 8 accession candidate countries through the 2025 Digital Government Index and OURdata Index. Covers digital public infrastructure, data governance, investment, skills, AI adoption and service delivery.
- [AI Governance Alliance Briefing Paper Series](https://www.aigl.blog/ai-governance-alliance-briefing-paper-series.md) - The AI Governance Alliance Briefing Paper Series bundles three January 2024 briefing papers on safe generative AI models, responsible enterprise transformation, and international AI governance, interoperability and equitable access.
- [Unlocking Value from Generative AI: Guidance for Responsible Transformation](https://www.aigl.blog/unlocking-value-from-generative-ai-guidance-for-responsible-transformation.md) - World Economic Forum briefing paper, produced with IBM Consulting, on how organizations can capture value from generative AI use cases while managing downstream impacts. It sets out three evaluation gates for selecting use cases and four functions for responsible transformation.
- [Making Agentic AI Work for Government: A Readiness Framework](https://www.aigl.blog/making-agentic-ai-work-for-government-a-readiness-framework.md) - An insight report from the World Economic Forum with Capgemini that maps 70 core government functions against agentic AI potential and implementation complexity, offering a readiness framework, scored topography and a six-step process for local roadmaps.
- [Privacy Governance Report 2024](https://www.aigl.blog/privacy-governance-report-2024.md) - One-page at-a-glance infographic from the IAPP's Privacy Governance Report 2024, published December 2024, summarising survey findings on privacy budgets, staffing, training, breaches and the growing share of privacy professionals tasked with AI governance.
- [The AI Governance Journey: Development and Opportunities](https://www.aigl.blog/the-ai-governance-journey-development-and-opportunities.md) - A World Economic Forum insight report from October 2021 tracing the development of AI governance and setting out priorities for turning ethical principles into practice through risk-based, multistakeholder and agile approaches.
- [Preparedness Framework](https://www.aigl.blog/preparedness-framework.md) - OpenAI's Preparedness Framework (Version 2) sets out how the company identifies frontier AI capabilities that could cause severe harm, defines High and Critical thresholds, and describes the evaluations, safeguards, security controls and governance used to manage those risks.
- [Deploying AI Systems Securely: Best Practices for Deploying Secure and Resilient AI Systems](https://www.aigl.blog/deploying-ai-systems-securely-best-practices-for-deploying-secure-and-resilient-ai-systems.md) - Joint cybersecurity information sheet from the NSA's AI Security Center, CISA, the FBI and partner agencies in Australia, Canada, New Zealand and the UK, setting out best practices for deploying and operating externally developed AI systems securely.
- [Frontier Governance Framework](https://www.aigl.blog/frontier-governance-framework.md) - OpenAI's Frontier Governance Framework sets out how the company identifies, analyses and mitigates systemic risks from frontier models, and how it meets requirements under California's TFAIA and the EU General-Purpose AI Code of Practice.
- [AI assurance? Assessing and mitigating risks across the AI lifecycle](https://www.aigl.blog/ai-assurance-assessing-and-mitigating-risks-across-the-ai-lifecycle.md) - Ada Lovelace Institute report surveying methods for assessing, monitoring and mitigating risks from AI systems across the lifecycle, in literature, industry practice and emerging legislation, and proposing a UK assessment ecosystem.
- [Practical AI for CEOs: When it really matters. A playbook for realizing value from your AI initiatives](https://www.aigl.blog/practical-ai-for-ceos-when-it-really-matters-a-playbook-for-realizing-value-from-your-ai-initiatives.md) - A playbook from AlixPartners for chief executives on realising value from AI initiatives, organised around strategy, execution and technical and organisational foundations, with client stories and an AI maturity self-assessment.
- [Going pro? Considerations for the emerging field of AI assurance](https://www.aigl.blog/going-pro-considerations-for-the-emerging-field-of-ai-assurance.md) - A discussion paper from the Ada Lovelace Institute and the Center for Democracy & Technology that draws on 15 practitioner interviews to examine how the emerging AI assurance field could professionalise, presenting four findings and seven recommendations.
- [Agentic AI addendum to the AI technical standard for Australian Government](https://www.aigl.blog/agentic-ai-addendum-to-the-ai-technical-standard-for-australian-government.md) - Digital Transformation Agency addendum extending the AI technical standard for Australian Government, setting out best-practice statements AGT.1–AGT.8 for the governed implementation of agentic AI across governance, design, data, training, evaluation, integration, monitoring and decommissioning.
- [Policy Alignment on AI Transparency: Analyzing Interoperability of Documentation Requirements across Eight Frameworks](https://www.aigl.blog/policy-alignment-on-ai-transparency-analyzing-interoperability-of-documentation-requirements-across-eight-frameworks.md) - Partnership on AI report comparing documentation requirements for foundation models across eight policy frameworks from the US, EU, UK and multilateral bodies, mapping where they align and where divergence could emerge, with recommendations on thresholds, standards and AI Safety Institutes.
- [Assessing Risk Relative to Competitors: An Analysis of Current AI Company Policies](https://www.aigl.blog/assessing-risk-relative-to-competitors-an-analysis-of-current-ai-company-policies.md) - A GovAI policy brief analysing how frontier AI companies assess marginal risk relative to competitors' models, why that approach may be flawed, and how it could erode safety standards and raise total risk.
- [Guidance for the artificial intelligence impact assessment tool](https://www.aigl.blog/guidance-for-the-artificial-intelligence-impact-assessment-tool.md) - DTA guidance for completing the Australian Government AI impact assessment tool, taking teams section by section through scope criteria, inherent risk rating, fairness, reliability and safety, privacy, transparency, contestability and accountability.
- [Position: Comprehensive AI governance requires addressing non-model capability gains](https://www.aigl.blog/position-comprehensive-ai-governance-requires-addressing-non-model-capability-gains.md) - A position paper from authors affiliated with Google DeepMind and the Centre for the Governance of AI arguing that model-level AI governance must be complemented by system, entity, agent and cloud governance as non-model capability gains grow.
- [From Turing to Tomorrow: The UK’s Approach to AI Regulation](https://www.aigl.blog/from-turing-to-tomorrow-the-uks-approach-to-ai-regulation.md) - A preprint book chapter from the Centre for the Governance of AI that traces UK AI regulation from the 2010s through the Bletchley and Seoul summits to early 2025, and proposes a principles-based regulator for frontier AI developers.
- [CSET 2025 Annual Report](https://www.aigl.blog/cset-2025-annual-report.md) - Annual report of the Center for Security and Emerging Technology at Georgetown University, summarising the organization's 2025 research, testimony, events and public tools on AI, national security and US–China technology competition.
- [Don’t Panic! Getting Real About AI Governance](https://www.aigl.blog/dont-panic-getting-real-about-ai-governance.md) - Cloud Security Alliance white paper arguing that AI governance can build on established risk management norms because useful AI systems implement human judgment, and recommending a risk-based approach measured on a maturity scale.
- [AI Organizational Responsibilities: AI Tools and Applications](https://www.aigl.blog/ai-organizational-responsibilities-ai-tools-and-applications.md) - Third white paper in the Cloud Security Alliance AI Organizational Responsibilities series, examining the practical implementation of AI tools and applications: LLM and GenAI security, third-party and supply chain management, and AI operations.
- [Artificial Intelligence and Human Rights: The Council of Europe Framework Convention on Artificial Intelligence](https://www.aigl.blog/artificial-intelligence-and-human-rights-the-council-of-europe-framework-convention-on-artificial-intelligence.md) - A nine-page Council of Europe deck introducing the Framework Convention on Artificial Intelligence as the first international treaty to keep AI systems consistent with human rights, democracy and the rule of law, with a status snapshot of signatories and ratifications.
- [Conclusion of the Artificial Intelligence Board on the Assessment of the Code of Practice on Transparency of AI-generated Content pursuant to Article 50(7) of Regulation 2024/1689](https://www.aigl.blog/conclusion-of-the-artificial-intelligence-board-on-the-assessment-of-the-code-of-practice-on-transparency-of-ai-generated-content-pursuant-to-article-50-7-of-regulation-2024-1689.md) - The European Artificial Intelligence Board's adequacy assessment of the Code of Practice on Transparency of AI-generated content, reviewing its eight commitments on marking, detection and labelling under Article 50 of the AI Act.
- [Commission Opinion of 1.8.2025 on the assessment of the General-Purpose AI Code of Practice within the meaning of Article 56 of Regulation (EU) 2024/1689](https://www.aigl.blog/commission-opinion-of-1-8-2025-on-the-assessment-of-the-general-purpose-ai-code-of-practice-within-the-meaning-of-article-56-of-regulation-eu-2024-1689.md) - European Commission opinion assessing whether the General-Purpose AI Code of Practice adequately covers the obligations in Articles 53 and 55 of the AI Act and meets the aims of Article 56. It maps the Code's commitments and measures to those obligations.
- [Code of Practice for General-Purpose AI Models Transparency Chapter](https://www.aigl.blog/code-of-practice-for-general-purpose-ai-models-transparency-chapter.md) - The Transparency Chapter of the Code of Practice for General-Purpose AI Models, setting out the documentation measures that signatories commit to under Article 53(1), points (a) and (b), of the AI Act, and including a Model Documentation Form.
- [Code of Practice for General-Purpose AI Models: Copyright Chapter](https://www.aigl.blog/code-of-practice-for-general-purpose-ai-models-copyright-chapter.md) - Copyright Chapter of the Code of Practice for General-Purpose AI Models, setting out objectives, recitals and five measures by which signatories can demonstrate compliance with Article 53(1)(c) of the EU AI Act on copyright and related rights.
- [Approval of the content of the draft Communication from the Commission – Guidelines on the scope of the obligations for general-purpose AI models established by Regulation (EU) 2024/1689 (AI Act)](https://www.aigl.blog/approval-of-the-content-of-the-draft-communication-from-the-commission-guidelines-on-the-scope-of-the-obligations-for-general-purpose-ai-models-established-by-regulation-eu-2024-1689-ai.md) - European Commission Communication of 18 July 2025 asking the College to approve the content of draft Guidelines on the scope of the obligations for general-purpose AI models under Regulation (EU) 2024/1689, ahead of their application from 2 August 2025.
- [Code of Practice for General-Purpose AI Models Safety and Security Chapter](https://www.aigl.blog/code-of-practice-for-general-purpose-ai-models-safety-and-security-chapter.md) - The Safety and Security Chapter of the EU Code of Practice for General-Purpose AI Models, setting out ten Commitments and Measures for systemic risk assessment, mitigation, reporting and governance by providers of models with systemic risk.
- [Assessing Potential Future Artificial Intelligence Risks, Benefits and Policy Imperatives](https://www.aigl.blog/assessing-potential-future-artificial-intelligence-risks-benefits-and-policy-imperatives.md) - OECD Artificial Intelligence Papers No. 27: a review of research and expert perspectives on potential future AI benefits, risks and policy actions, drawing on the OECD Expert Group on AI Futures and ranking ten priority items in each category.
- [Guidelines on the implementation of the transparency obligations for certain AI systems under Article 50 of Regulation (EU) 2024/1689 (the 'AI Act')](https://www.aigl.blog/guidelines-on-the-implementation-of-the-transparency-obligations-for-certain-ai-systems-under-article-50-of-regulation-eu-2024-1689-the-ai-act.md) - European Commission guidelines interpreting the Article 50 transparency obligations of Regulation (EU) 2024/1689 for interactive AI systems, synthetic content marking, emotion recognition and deep fakes, with conditions, exceptions and worked examples.
- [Frontier AI Product Liability Act: A Model Bill](https://www.aigl.blog/frontier-ai-product-liability-act-a-model-bill.md) - A model state bill from the Future of Life Institute that designates frontier AI models as products and their developers as manufacturers, authorises joint and several liability across the AI value chain and lists factors for judging defectiveness.
- [NIST AI RMF to ISO/IEC FDIS 42001 AI Management system Crosswalk](https://www.aigl.blog/nist-ai-rmf-to-iso-iec-fdis-42001-ai-management-system-crosswalk.md) - A crosswalk mapping the subcategories of the NIST AI Risk Management Framework's GOVERN, MAP, MEASURE and MANAGE functions to the clauses and Annex B controls of ISO/IEC FDIS 42001, the AI management system standard.
- [AI Responsibility for Catastrophic Harm Act ("ARCH Act"): A Model Bill](https://www.aigl.blog/ai-responsibility-for-catastrophic-harm-act-arch-act-a-model-bill.md) - A model state bill from the Future of Life Institute that would impose strict liability on frontier AI developers for catastrophic harms, treating frontier model development as an ultra-hazardous activity.
- [[State] AI Child Safety Act](https://www.aigl.blog/state-ai-child-safety-act.md) - A model state bill from the Future of Life Institute that would require independent pre-deployment safety testing of conversational AI systems used by minors, impose a duty of care, set operational and data safeguards for minors, and create strict liability and a private right of action.
- [EU NIS2 Directive: 101](https://www.aigl.blog/eu-nis2-directive-101.md) - An IAPP one-page explainer on the EU NIS2 Directive: which organisations and sectors are in scope, the Article 21 cybersecurity requirements, Article 23 incident-reporting obligations and timeline, enforcement powers, penalties and key dates.
- [Feedback on the Draft Implementing Regulation on Evaluations and Enforcement Proceedings under the AI Act](https://www.aigl.blog/feedback-on-the-draft-implementing-regulation-on-evaluations-and-enforcement-proceedings-under-the-ai-act.md) - Feedback submission from the Future of Life Institute on the Commission's draft implementing regulation for GPAI model evaluations and enforcement proceedings under Articles 92 and 101 of the EU AI Act, supporting key provisions and setting out seven recommendations.
- [Supplementary Materials for Managing extreme AI risks amid rapid progress](https://www.aigl.blog/supplementary-materials-for-managing-extreme-ai-risks-amid-rapid-progress.md) - Supplementary material to the article Managing extreme AI risks amid rapid progress, credited to Yoshua Bengio and co-authors. It reproduces the article text with 73 additional citations and adds an extended reference list on extreme AI risks, technical safety R&D and frontier AI governance.
- [Key terms for AI Addendums: Six clauses to include in your AI Addendum](https://www.aigl.blog/key-terms-for-ai-addendums-six-clauses-to-include-in-your-ai-addendum.md) - A best-practices slide deck setting out six clauses for an AI addendum to a vendor agreement, each with sample Pro-Customer and Pro-Vendor wording on consent, data ownership, model training, legal compliance, ethical use and liability.
- [Leveraging Generative AI for Job Augmentation and Workforce Productivity: Scenarios, Case Studies and a Framework for Action](https://www.aigl.blog/leveraging-generative-ai-for-job-augmentation-and-workforce-productivity-scenarios-case-studies-and-a-framework-for-action.md) - World Economic Forum insight report, published with PwC, on how generative AI can augment jobs and raise workforce productivity, offering four scenarios, interview insights from more than 20 early adopters and a framework for action.
- [Responsible AI Transparency Report 2026](https://www.aigl.blog/responsible-ai-transparency-report-2026.md) - Microsoft's 2026 Responsible AI Transparency Report describes how the company governs the AI it develops, releases, operates and uses, covering its re-engineered Responsible AI Standard, NIST AI RMF-aligned risk management, agent governance tooling and ecosystem engagement.
- [TrustX Agent Risk Classification Framework (ARC): Risk-Tiering Internally Created Agentic AI Systems](https://www.aigl.blog/trustx-agent-risk-classification-framework-arc-risk-tiering-internally-created-agentic-ai-systems.md) - A paper from the Responsible AI Institute presenting the TrustX Agent Risk Classification Framework, a twelve-dimension rubric, GPA + IAT checklist and five-level autonomy scale that tier agentic AI systems into three risk levels with mapped controls, plus a coding assistant extension.
- [ISO/IEC 42001:2023 AI Management System Standard, Part 2: Core Requirements – Deep Dive into Clauses 4 through 10](https://www.aigl.blog/iso-iec-42001-2023-ai-management-system-standard-part-2-core-requirements-deep-dive-into-clauses-4-through-10.md) - Part 2 of a four-part LinkedIn series on ISO/IEC 42001:2023, summarising clauses 4 to 10 of the AI management system standard as tables of requirement areas and organisational actions, with a closing map of clauses to templates and tools.
- [A Comprehensive Survey and Classification of Evaluation Criteria for Trustworthy Artificial Intelligence](https://www.aigl.blog/a-comprehensive-survey-and-classification-of-evaluation-criteria-for-trustworthy-artificial-intelligence.md) - A systematic literature review of evaluation criteria and metrics for Trustworthy AI, mapped to the seven EU principles, with a proposed classification per principle and a mortgage lending case study.
- [A Frontier AI Risk Management Framework: Bridging the Gap Between Current AI Practices and Established Risk Management](https://www.aigl.blog/a-frontier-ai-risk-management-framework-bridging-the-gap-between-current-ai-practices-and-established-risk-management.md) - SaferAI paper proposing a four-part frontier AI risk management framework — risk identification, analysis and evaluation, treatment and governance — built around an explicit risk tolerance operationalized into KRI and KCI thresholds linked by if-then rules.
- [A GCC leader’s guide for driving Generative AI adoption](https://www.aigl.blog/a-gcc-leaders-guide-for-driving-generative-ai-adoption.md) - Published by Deloitte India, this guide helps Global Capability Centre leaders assess readiness for generative AI, identify, qualify and prioritise use cases, run proofs of concept, scale to production and apply trustworthiness and governance checks.
- [International AI Safety Report: The International Scientific Report on the Safety of Advanced AI](https://www.aigl.blog/international-ai-safety-report-the-international-scientific-report-on-the-safety-of-advanced-ai.md) - Synthesis of the scientific evidence on the safety of general-purpose AI: capabilities, risks from malicious use, malfunctions and systemic effects, and technical risk management. Produced by 96 experts ahead of the AI Action Summit.
- [A playbook for crafting AI strategy](https://www.aigl.blog/a-playbook-for-crafting-ai-strategy.md) - A sponsored MIT Technology Review Insights report, based on a March 2024 survey of 205 executives and expert interviews, on moving enterprise AI from pilots to scale: data foundations, costs and ROI, vendor partnerships, risk, security and regulation.
- [Acceptable Use Policies for Foundation Models](https://www.aigl.blog/acceptable-use-policies-for-foundation-models.md) - Analysis of the acceptable use policies of 30 foundation model developers, coding 127 prohibited use categories and examining enforcement, fragmentation across the AI supply chain and effects on the foundation model market.
- [Adopting generative AI in banking](https://www.aigl.blog/adopting-generative-ai-in-banking.md) - Kodex AI white paper on adopting generative AI in banking: a three-stage use-case roadmap, quality determinants and benchmarks, GenAI risks with mitigants, and implementation recommendations for regulated financial firms.
- [Adoption of AI, Blockchain and other emerging technologies within the European public sector](https://www.aigl.blog/adoption-of-ai-blockchain-and-other-emerging-technologies-within-the-european-public-sector.md) - The second Public Sector Tech Watch report from the European Commission analyses 1,617 cases of AI, blockchain, virtual worlds, AR/VR and quantum computing in European public administrations, and closes with six policy recommendations.
- [Agentic AI – the new frontier in GenAI: An executive playbook](https://www.aigl.blog/agentic-ai-the-new-frontier-in-genai-an-executive-playbook.md) - A PwC Middle East executive playbook on agentic AI, covering definitions, the evolution to multimodal agents, service-as-a-software and copilot-to-autopilot models, cross-industry case studies, agent tool comparisons, a six-step adoption roadmap and do's and don'ts.
- [Agents](https://www.aigl.blog/agents.md) - A whitepaper from Google explaining how generative AI agents combine a model, tools and an orchestration layer, covering Extensions, Functions and Data Stores, reasoning frameworks such as ReAct, and implementation with LangChain and Vertex AI.
- [Inescapable AI: The Ways AI Decides How Low-Income People Work, Live, Learn, and Survive](https://www.aigl.blog/inescapable-ai-the-ways-ai-decides-how-low-income-people-work-live-learn-and-survive.md) - A report from TechTonic Justice by Kevin De Liban that estimates how many low-income people in the United States are subject to AI decision-making in benefits, housing, employment, education, child welfare and domestic violence, and sets out advocacy recommendations.
- [AI 2027](https://www.aigl.blog/ai-2027.md) - A dated forecast scenario from the AI Futures Project tracing how superhuman AI could arrive between mid-2025 and 2030, with two endings: a race to AI takeover and a slowdown that keeps humans in control.
- [AI Agents and Ecosystems Contestability](https://www.aigl.blog/ai-agents-and-ecosystems-contestability.md) - CERRE issue paper assessing whether the EU's digital acquis — the P2B Regulation, DMA, Data Act, AI Act, DSA, competition law and net neutrality rules — is prepared for AI agents, covering their definition, bottleneck inputs, contestability concerns and applicable obligations.
- [AI and ESG: An introductory guide for ESG practitioners](https://www.aigl.blog/ai-and-esg-an-introductory-guide-for-esg-practitioners.md) - An introductory guide from the Australian Government's National Artificial Intelligence Centre on how AI relates to ESG work, mapping AI ethics principles to ESG topics and pointing to frameworks, examples and next steps.
- [Incident Tracker - June 2025 Update](https://www.aigl.blog/incident-tracker-june-2025-update.md) - A June 2025 release note for an incident tracker, listing changes dated 23 June 2025: AI Incident Database incidents up to ID #1116, revised LLM analysis, a 1–5 harm severity scale, national security impact assessment and fishbone cause diagrams.
- [AI as a Public Good: Ensuring Democratic Control of AI in the Information Space](https://www.aigl.blog/ai-as-a-public-good-ensuring-democratic-control-of-ai-in-the-information-space.md) - Policy framework from the Forum on Information and Democracy recommending democratic control of AI in the information space, covering safe AI development and deployment, liability and accountability regimes, incentives for ethical AI, and governance and oversight.
- [How to boost innovation through effective AI Governance?](https://www.aigl.blog/how-to-boost-innovation-through-effective-ai-governance.md) - A PwC slide deck for Data Day 2025 that explains the EU AI Act's timeline, risk classes and penalties and sets out an implementation model: lifecycle controls mapped to articles, a registered AI inventory, defined accountabilities and five key takeaways.
- [AI Governance Resource Repository](https://www.aigl.blog/ai-governance-resource-repository.md) - A curated compilation of free AI governance resources — newsletters, podcasts, courses, books, tools, repositories, jurisdictional standards, legislation trackers, communities and certifications — organised under Learn, Try, Volunteer and Train.
- [AI in Education: An EU AI Act Guide](https://www.aigl.blog/ai-in-education-an-eu-ai-act-guide.md) - A practical guide for schools on what the EU AI Act requires, written by educator Matthew Wemyss. It explains the Act's risk levels, prohibited and high-risk uses in education, penalties, and steps to assess, review and comply.
- [AI Incidents: Key Components for a Mandatory Reporting Regime](https://www.aigl.blog/ai-incidents-key-components-for-a-mandatory-reporting-regime.md) - A CSET issue brief proposing a standardized list of key components for AI incidents — event type, harm dimensions, technical data, context and post-incident data — as a template for mandatory AI incident reporting regimes.
- [AI Inventories: Practical Challenges for Organizational Risk Management](https://www.aigl.blog/ai-inventories-practical-challenges-for-organizational-risk-management.md) - A Responsible AI Institute guide on building and maintaining inventories of AI use cases for organizational risk management, covering definitional challenges, third-party AI integrations, risk identification, mitigation, and how regulations and standards can help.
- [Global AI Law and Policy Tracker](https://www.aigl.blog/global-ai-law-and-policy-tracker-2.md) - The IAPP's Global AI Law and Policy Tracker records AI laws, policies, national strategies and responsible authorities across 25 jurisdictions on six continents, plus multilateral initiatives. Last updated May 2025.
- [AI Policy Template](https://www.aigl.blog/ai-policy-template.md) - A fill-in-the-blank organizational AI policy template from the Responsible AI Institute, with fourteen sections covering governance, principles, data, risk, procurement and compliance, aligned to ISO/IEC 42001 and the NIST AI RMF.
- [AI safety and the US-China arms race: Implications of safety regulation on innovation, economic growth, and military technologies](https://www.aigl.blog/ai-safety-and-the-us-china-arms-race-implications-of-safety-regulation-on-innovation-economic-growth-and-military-technologies.md) - A Center for AI Policy paper by Claudia Wilson arguing that mandatory pre-deployment evaluations for the most powerful closed-source AI models would not slow US innovation, economic growth or military capability in competition with China.
- [Leading AI Progress: Policy Insights and a U.S. Vision for AI Adoption, Responsible Innovation, and Governance](https://www.aigl.blog/leading-ai-progress-policy-insights-and-a-u-s-vision-for-ai-adoption-responsible-innovation-and-governance.md) - Report of the Bipartisan House Task Force on Artificial Intelligence setting out a U.S. vision for AI adoption, responsible innovation and governance, with 66 key findings and 89 recommendations across 15 policy chapters.
- [Global Frameworks and Standards Working Group Annual report – July 2024](https://www.aigl.blog/global-frameworks-and-standards-working-group-annual-report-july-2024.md) - Annual report of the Global Privacy Assembly's Global Frameworks and Standards Working Group covering its 2023-24 work on promoting global data protection standards and on cross-border transfer mechanisms, with comparative tables of contractual clauses.
- [AI Vendor Security and Safety Assessment Guide](https://www.aigl.blog/ai-vendor-security-and-safety-assessment-guide-2.md) - A question-based guide by Dennis Ah-king for evaluating AI vendors on security, safety, privacy and ethics, covering governance, data handling, model robustness, auditability and supply chain risk.
- [AI, Data Governance and Privacy: Synergies and Areas of International Co-operation](https://www.aigl.blog/ai-data-governance-and-privacy-synergies-and-areas-of-international-co-operation.md) - OECD Artificial Intelligence Paper No. 22 mapping the OECD Privacy Guidelines to the OECD AI Principles, taking stock of privacy enforcement authorities' guidance and enforcement actions on AI, and identifying areas for international co-operation.

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