AI Governance Library
AI Audit Checklist By: Kamran Iqbal

AI Audit Checklist By: Kamran Iqbal

A comprehensive, practitioner-friendly checklist covering 100+ AI audit questions across governance, ethics, security, bias, explainability, and compliance. It aligns with standards like ISO 42001, GDPR, and the EU AI Act, making it a strong operational guide for risk assessments.

Building trusted AI in the enterprise

Building trusted AI in the enterprise

Anthropic’s guide for enterprises adopting generative AI blends real-world deployment insights with a clear, staged strategy. From AI governance to technical scaling, it outlines how organizations can responsibly and effectively operationalize AI like Claude.

Al Value Creators

Al Value Creators

This practical, executive-level guide helps business leaders and technologists reframe how they approach generative AI—shifting from mere users to true value creators.

The Adoption of Artificial Intelligence in Firms

The Adoption of Artificial Intelligence in Firms

This expansive report draws on a new survey of 840 enterprises in G7 countries and 167 in Brazil to reveal how firms are using AI, where they struggle, and what kind of public support they value. It’s an evidence-rich resource for shaping practical AI policy.

20 Cognitive Biases everyone should know

20 Cognitive Biases everyone should know

A compact, practical guide to understanding the most influential cognitive biases in everyday thinking, decision-making, and AI design—plus a bonus chapter on algorithmic bias. A must-read for anyone working at the intersection of technology, governance, and ethics.

Making AI Self-Regulation Work

Making AI Self-Regulation Work

Amlan Mohanty’s report, Making AI Self-Regulation Work, offers a comprehensive framework for deploying self-regulation as a foundational piece of India’s AI governance.

Open Source Technology in the Age of AI

Open Source Technology in the Age of AI

Open source AI is no longer fringe—it’s becoming essential. Based on a global survey of over 700 tech leaders, this report shows how open source AI is reshaping tech stacks, boosting developer satisfaction, and challenging proprietary dominance.

Multi-Agentic system Threat Modelling Guide

Multi-Agentic system Threat Modelling Guide

A highly structured guide showing how to apply OWASP’s Agentic AI Threat Taxonomy to real-world multi-agent systems (MAS), introducing the MAESTRO framework to surface layered vulnerabilities and new attack paths unique to agent-to-agent coordination environments.

AI Governance Library Newsletter #4: Build to Last

AI Governance Library Newsletter #4: Build to Last

This issue is about the foundations no one celebrates—but everyone depends on. Solid spreadsheets, clean templates, tools that won’t break under pressure. Plus: models planning backwards, AI apps built in a weekend, and how a book cover can teach you everything about framing AI risk.

AI Risk Assessment Template (TrustArc, 2025)

AI Risk Assessment Template (TrustArc, 2025)

The AI Risk Assessment Template provides a structured, highly practical checklist for evaluating AI system risks across development, deployment, and operation phases. It aligns with NIST AI RMF and EU AI Act requirements, aiming to boost trustworthy AI practices.

AI Governance Library Newsletter #3: Show, don't tell

AI Governance Library Newsletter #3: Show, don't tell

This week we look at how visual design can make or break AI governance, review the first real playbook for agent oversight, and highlight why Tom Scott’s YouTube channel might teach you more about systems failure than most compliance workshops ever could.

AI Agents Governance – A Field Guide

AI Agents Governance – A Field Guide

This guide explores how to govern autonomous AI agents—systems capable of planning and acting with minimal instruction. It presents a structured approach to agent risks and interventions, pushing the conversation beyond foundation models toward emergent systems.

AI Ethics and Governance in Practice

AI Ethics and Governance in Practice

This workbook is a facilitator’s guide to delivering AI ethics training across public institutions. It covers AI fundamentals, public sector use cases, and governance models—paired with activities grounded in UK government experience and policy frameworks.

Understanding Responsibilities in Al Practices

Understanding Responsibilities in Al Practices

This guidance from New South Wales outlines role-specific responsibilities for implementing responsible AI. It supports public agencies in assigning accountability using ISO-aligned frameworks and practical RACI structures. A useful anchor for everyday governance.

A blueprint for modern digital government

A blueprint for modern digital government

This UK government strategy outlines a six-point digital reform plan focused on service redesign, AI integration, shared infrastructure, and leadership reform. It introduces a new digital centre of government and pushes for transparency, efficiency, and public trust.

European Union Artificial Intelligence Act: a guide

European Union Artificial Intelligence Act: a guide

The Bird & Bird guide to the EU AI Act offers a deep dive into the Act’s legal obligations, scope, governance model, and technical standards. It walks readers through implementation timelines, roles across the AI value chain, and penalties for non-compliance.

AI Privacy Risks & Mitigations – Large Language Models

AI Privacy Risks & Mitigations – Large Language Models

This report, produced under the EDPB’s Support Pool of Experts (SPE) programme, offers structured guidance on managing privacy risks in LLM systems. It lays out risk identification, evaluation, and control strategies tailored to GDPR and AI Act obligations, supporting both developers and deployers.

AI Governance Library

Curated Library of AI Governance Resources

AI Governance Library

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