What readers will get
A comparative view of how AI in education is unfolding across the United States, Kenya, China, the United Arab Emirates and Switzerland.
A practical map of the main implementation bottlenecks: teacher readiness, policy clarity, trust, infrastructure and assessment reform.
Concrete signals for AI practitioners, education leaders and policy actors seeking grounded lessons rather than hype.

Signals, bottlenecks, and practical moves for AI practitioners, educators, and policy leaders

AI in Education Across Five Countries: Implementation Signals, Policy Gaps, and What Comes Next

Artificial intelligence is transforming education, but its benefits remain out of reach for many of the communities that could benefit most. Drawing primarily from an hour-long public interview with Dr. Seiji Isotani and secondarily from the OECD Digital Education Outlook 2026 interview chapter, this memo argues that policymakers should stop treating infrastructure build-out as a precondition for AI in education. Instead, they should design around the infrastructure that already exists—especially mobile phones, intermittent connectivity, and teacher-led delivery models. The Brazil case discussed by Dr. Isotani shows that this approach can work at scale: 500,000 students across 7,000 schools and 20,000 teachers received materially faster feedback on writing, with statistically significant improvement and no meaningful urban-rural or resource-based gap in gains.

Based primarily on an policy dialogue with Dr. Seiji Isotani

AI in Education Unplugged: Closing the Access Gap Through Education-Driven Design

This brief synthesizes evidence and expert dialogue on scaling AI literacy and governance beyond pilots. It argues for treating AI literacy as baseline infrastructure, aligning responsible-use policy with cybersecurity maturity, and preparing for workforce change as task-displacement first.

AI Workforce Transformation

Latest workforce analysis

From BlackRock to UNESCO: AI’s Next Challenge Is Institutional Design

AI Workforce Transformation Is Not a Tool Problem. It Is a Human and Organizational One

Policy releases

Exiting the AI Pilot Trap: Responsible Scale for AI Literacy, Governance, and Workforce Readiness

Implementation playbooks

Workplace AI Governance (RACI + Guardrails)

Role/Task Mapping Method

Training Architecture (Role-Based Pathways)

Adoption & Risk Measurement Framework

Explore the rest of the Observatory

AI in Education

Institutional AI Transition