How might low- and middle-income countries reimagine the purpose and ways of learning in the age of AI with the foresight to do things differently from previous tech waves?
EdTech Hub’s AI Observatory is exploring how education systems can renew the purpose of learning — which means rethinking what education is for in a world shaped by AI, with the aim of narrowing the learning divide.
This week, in Issue No. 33 of the #WaypointWednesday, we spotlight ways education systems are rethinking what assessment is for, broadening the purpose of education, and using foresight strategies to scenario plan for possible futures.
Early signals
Rethinking what assessment is for in the age of AI
If AI systems can produce essays, solve problems, or generate code that resembles student work, long-standing methods for evaluating learning may begin to look less certain. We’re seeing efforts to rethink what assessment is meant to achieve in the age of AI.
- South Africa – A Practical Guide for Lecturers:A recent guide from Stellenbosch University asks whether thoughtfully designed assessment still produces the learning gains educators expect in an AI-saturated environment. It explores how assessments can remain valid, intentional and pedagogically meaningful when students have ready access to AI tools. (Adendorff et al., 2026)
- Global – Global Review of AI in Assessment Design: A report by the Digital Education Council and Pearson maps emerging AI-integrated assessment practices in higher education. Drawing on 101 case studies from around the world, it outlines how institutions can redesign assessment systems to account for the presence of AI tools while maintaining meaningful measures of learning. (Digital Education Council, 2025)
Reimagining what skills humans need to thrive in the age of AI
In the EdTech Hub AI Observatory’s Trend Report: Learners in the Age of AI, we note that the growing emphasis on closing the “AI skills gap” may quietly narrow the purpose of education by framing it mainly as preparation for an AI-ready workforce (Weatherall, 2026). At the same time, emerging signals point to a deeper reconsideration of what learners need in order to thrive in the age of AI.
- Global – Relational intelligence: Hau argues that as AI systems take on more cognitive and analytical tasks, the capabilities that become most valuable may be relational. Writing in the Stanford Social Innovation Review, Isabelle Hau describes relational intelligence as the human capacity to build trust, navigate conflict, and create shared understanding with others. (Stanford Social Innovation Review, 2026)
- Global South – Learning ecosystems: The Learning Planet Institute has mapped more than one hundred learning ecosystems in the Global South and conducted deeper studies of 11. Many of these community-driven educational models place explicit emphasis on helping learners thrive within their communities, proposing a broader objective for education. (Learning Planet Institute, 2024)
Using foresight to imagine different futures for education
AI introduces uncertainty about how learning systems might evolve. Rather than attempting to predict a single trajectory, foresight approaches attempt to map multiple plausible futures and use them to support reflection and planning.
- Global – Future Child Persona Development Toolkit:Developed in collaboration with the Dubai Future Foundation and the Artefact Group, UNESCO proposes a method for co-creating personas that help policymakers, practitioners, and young people imagine futures with children, not just for them. (UNESCO, 2026)
- Global – A Collective Reflection from the Educational Landscape: In one collaborative study, education scholars each wrote short fictional narratives describing how generative AI might evolve within educational settings. The paper argues that, as AI becomes capable of doing more educational tasks, it is essential to rethink what should remain the responsibility of human educators versus what might be automated or supported by AI. (Bozkurt et al, 2023)
Reflections
- The concern about students using AI to accelerate assignment completion often focuses on academic integrity issues such as plagiarism. Yet, the phenomenon also points to a deeper structural question within education systems: why has passing become more valuable to many students than learning itself? Why aren’t many students intrinsically motivated to learn?
- Various structural conditions in education may be contributing to students’ prioritisation of passing over learning: systems that reward grades and credentials more than deep understanding, assessment designs that evaluate the final product rather than the learning process, increasing economic and social pressures that frame education instrumentally as a pathway to employment over intellectual exploration, and learning experiences that feel disconnected from students’ interests or realities.
