Every reviewed AI governance resource in one place — reports, standards, guidance and regulation.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
Curated Library of AI Governance Resources
