Artificial Intelligence & Machine Learning

This report explores the skills, attitudes and knowledge that children in five African countries see as important for an AI-influenced world.

This webinar explores whether AI-generated survey responses can help understand human behaviour and inform policy

This policy brief introduces the Data-to-AI Value Chain, a framework for building inclusive language AI that reflects the world's linguistic and cultural diversity.

Ten country stories showing how UNDP-supported digital public infrastructure, data systems and AI-enabled solutions are delivering measurable results for people.

Read the co-chairs summary on the inaugural Global Dialogue on AI Governance.

This report exames technology-facilitated child sexual abuse and exploitation across 21 countries, drawing on children's testimonies and large-scale survey data.

The Preliminary Report of the Independent International Scientific Panel on AI: Evidence-based assessment of opportunities, risks and impacts of AI is a first-of-its-kind independent scientific assessment of the capabilities, emerging opportunities and risks of artificial intelligence. The Panel, composed of independent scientists and experts from all 5 UN regions, outlines trends in AI. Its central warning: current safeguards cannot keep pace with the growth of AI’s capabilities.

This report draws on 26 AI Landscape Assessments to rethink AI readiness for countries where adoption is already underway.

This report draws on work with eleven countries and territories to show how AI trust, safety and governance are shaped in practice, not just in policy.

This special edition of the UN 2.0 Digital and Data Solutions Expo introduces the winners and select honorable mentions of the first UN 2.0 Award.

UNICEF’s AI Strategy 2025–2030: AI for Every Child, sets out the roadmap to ensure AI works in the best interests of children everywhere. The strategy highlights how AI can strengthen programme impact, improve operational readiness, and ensure children’s rights, voices and safety shape Al governance.

A UNU-INWEH report quantifying AI's environmental footprint across carbon, water and land, showing that AI is a material system with measurable environmental costs.

Learning today demands more than access to information. It requires opportunities to engage, practice, and apply knowledge in realistic contexts. Yet one key challenge remains: creating safe environments where learners can experiment, make decisions, and learn from experience—without real-world consequences. To address this gap, the Learning Innovation Programme (LIP) launched a series of pilot projects in 2025 focused on the design and use of AI Avatars.

The Readiness Assessment Methodology (RAM) includes a range of quantitative and qualitative questions designed to gather information about different dimensions related to a country’s AI ecosystem, including the legal and regulatory, social and cultural, economic, scientific and educational, and technological and infrastructural dimensions.

Harnessing AI to more effectively and efficiently enhance protection and solutions for forcibly displaced and stateless people and to deliver improved, data-driven responses across humanitarian contexts – people-centred and guided by principles of safety and accountability.

"Where do you start when preparing a country for the AI era?" This is a question more governments and investors are asking. The World Bank Group's new handbook, Accelerating Artificial Intelligence Investment in Emerging Markets, offers exactly that: a practical roadmap for building an AI ecosystem from the ground up that drives growth and jobs.