Artificial Intelligence & Machine Learning

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.

This note examines how agentic AI may affect payment systems, focusing on authorization, liquidity, settlement, compliance, and resilience. It highlights a key tension between probabilistic AI behavior and the deterministic requirements of payment infrastructures.

Explore impactful innovations across 45 UN Entities!

This UNU Rector AI Lecture Series episode shows how knowledge institutions and the UN advance responsible AI governance.

Driving progress and hope through innovation in humanitarian response

UNESCO and the Thomson Reuters Foundation are launching today a global report "Responsible AI in practice" based on information gathered from 3,000 companies about the Artificial Intelligence-related adoption and strategies. It finds that, as AI development and adoption accelerates rapidly in the private sector, nearly half of the companies (44%) reported having an AI strategy. One in ten companies is also publicly committed to adhering to an AI governance framework.

This session spotlights AI Initiatives featured in the recently launched UN AI Resource Hub, a collaborative effort by UNDP, ITU, and UNESCO.

Leveraging artificial intelligence (AI) for crowd monitoring can help law enforcement officers and related authorities identify threats to public safety more efficiently, support human operators in making quicker, more informed decisions, improve response times and reduce workload. Yet, AI-enhanced surveillance raises critical ethical, societal, and human rights considerations. The AI4citizens: Responsible AI for Citizen Safety in Future Smart Cities project, funded by the Research Council of Norway, brings together a multidisciplinary team to explore how an AI system for crowd monitoring and anomaly detection can be designed and deployed responsibly by anonymizing CCTV footage.

The Digital agriculture and AI innovation roadmap crystallizes a shared vision: an agrifood future where innovation is inclusive, trusted, and relentlessly focused on impact.

The UNU Global AI Network announces the publication of its 2025 Report, a comprehensive review of its inaugural year as a global platform dedicated to operationalizing the Global Digital Compact. This report highlights key milestones in multi-stakeholder collaboration aimed at advancing ethical and inclusive AI for sustainable development.

This session spotlighted AI Initiatives featured in the soon to be launched UN AI Resource Hub, a collaborative effort by UNDP, ITU, and UNESCO.

UNESCO developed the new Guidelines for the Use of AI Systems in Courts and Tribunals in response to the rapid, uneven adoption of AI across justice systems worldwide. The Guidelines provide practical principles, safeguards and recommendations to ensure AI strengthens, rather than undermines, human-led justice.

AI can lift growth, expand opportunities, improve public services, and strengthen resilience. The same technologies, however, can accelerate exclusion, undermine governance, and raise human insecurity. This report links AI to global inequality, labor market disruption, gender gaps in access, and differences in state capacity and trust. In Asia and the Pacific, AI readiness exceeds 70% in advanced economies but falls below 20% in fragile states, highlighting how uneven the starting line already is.

The UNICC AI Hub, in collaboration with the Frugal AI Hub at Cambridge Judge Business School, is pleased to share a new paper presenting a practical and standardized framework for measuring the true value of an organization’s AI portfolio.