Who Is AI Learning to Serve? EdTech That Closes Gaps, Not Widens Them
About the session
AI could help close some of education’s most persistent gaps, from foundational literacy and numeracy to access to learning in places where teachers, resources and opportunities are scarce. But it could just as easily deepen them.
AI tools are only as good as the data, assumptions and experiences that shape them. Children with disabilities, learners in lower-resource settings, and young people navigating informal credentials, unstable incomes and non-linear pathways are often exactly the people technology fails to anticipate.
So what would it take to design AI for the learners most likely to be left out? This session will explore how AI and education technology can expand access rather than reinforce existing inequalities, drawing on perspectives from Africa, Latin America and other lower-resource settings. It will also ask who gets to build these solutions, and what funders and international organisations need to do differently so locally led innovations can move from promising pilots to adoption at scale.
Discussion Group Leaders
Manushi Yadav is Head, Strategy and Global Partnerships at Pratham, strengthening strategy and partnerships that expand opportunities in education and skills development.
Matt Zeqiri is Head of Fundraising and Communications at Chance for Childhood, advancing inclusive education and locally led solutions for children across Africa, particularly those with disabilities.
What to expect
A practical conversation about where AI could genuinely expand educational opportunity, where exclusion is already being built into new tools, and what more inclusive design and deployment look like.
Participants will bring perspectives from education, technology, disability inclusion, workforce development and locally led innovation, with an emphasis on the learners and contexts that mainstream AI products too often overlook.
Who this is for
This session is for educators, funders, technologists, policymakers, researchers, disability advocates and social entrepreneurs interested in using AI to expand access to learning and opportunity without leaving the hardest-to-reach learners further behind.
What you will get out of it
A clearer view of where AI could help close gaps in education and where it risks widening them
Practical principles for designing technology around learners typically overlooked by mainstream products
Perspectives from lower-resource education systems and locally led innovators
Insights into taking inclusive, locally developed solutions from pilot to adoption at scale
Connections across education, technology, workforce development and inclusion