Brief Note · AI in Education
What AI in Education Needs Next: Lessons from Youth Leaders Across Five Countries
Field signals from five countries, translated into what education systems and funders should do next.
This note synthesises what youth leaders and practitioners are seeing in classrooms, unions, and ministries — and what it implies for the next phase of AI in education policy.
What changes when implementation leads
The most durable lessons are not about tools alone. They are about trust, evaluation capacity, and the redesign of assessment when generative models are ubiquitous.
For institutional readers
Use this as a checklist for where to invest next: governance, teacher judgement, procurement, and cross-sector dialogue.
This is original commentary related to the World Economic Forum article on youth leaders and AI in education.
About the author
Qiqing He is an AI workforce transformation strategist and founder of the independent Global AI Governance & Workforce Transformation Policy Observatory. His research draws on evidence from China and Asia.