Responsible AI

A Taxonomy of Trustworthiness for Artificial Intelligence: Connecting Properties of Trustworthiness with Risk Management and the AI Lifecycle

The AI Impact Navigator: A guide for leaders to steward AI impact — socially, environmentally, and economically

Outlook Study on Artificial Intelligence and Gender

USPTO Artificial Intelligence Strategy

AI Governance around the world – Country Profile: China

Trustworthy and Ethical Assurance of Digital Health and Healthcare: Supporting an assurance ecosystem for data-driven technologies in health and healthcare

Guidelines on the Responsible Implementation of Artificial Intelligence Systems in Journalism

Governing with Artificial Intelligence: Are governments ready?

State of AI Policy in Africa 2025

Microsoft Responsible AI Standard, v2: General Requirements for External Release

The AI Assurance Landscape (v1.0): Toward a Standardized Framework of Unique and Differentiated AIA Concepts

Responsible AI in the automotive industry: Techniques and 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

Guidance for AI adoption: implementation guidance

Red Teaming Artificial Intelligence for Social Good: The PLAYBOOK

Digital Government Outlook 2026: From Foundations to Transformational Impact

AI Governance Alliance Briefing Paper Series

Unlocking Value from Generative AI: Guidance for Responsible Transformation

The AI Governance Journey: Development and Opportunities

Guidance for the artificial intelligence impact assessment tool

Artificial Intelligence and Human Rights: The Council of Europe Framework Convention on Artificial Intelligence

Leveraging Generative AI for Job Augmentation and Workforce Productivity: Scenarios, Case Studies and a Framework for Action

Responsible AI Transparency Report 2026

A GCC leader’s guide for driving Generative AI adoption