The Readiness Gap: Why Most Education Systems Aren’t Equipped for AI Adoption
By Faith Ombewa | Digital Policy Strategist & AI Research Analyst
Artificial Intelligence in education is a new epistemology that reshapes how learning is structured, delivered and governed. Yet across the world, institutions are expected to integrate AI tools into already strained systems without addressing the deep structural gaps that compromise readiness.
The result? A dangerous acceleration of AI diffusion into ecosystems unprepared to govern its consequences (Pham & Sampson, 2022; UNESCO, 2021).
Drawing on emerging academic research, global policy literature and private sector case studies, this research brief argues that without foundational preparedness, AI adoption becomes performative at best and harmful at worst.
Frameworks Without Groundwork: The Strategic Failure of AI-First Policy in Education
By Faith Ombewa | Digital Policy Strategist & AI Research Analyst
AI is arriving in education faster than most systems are prepared for. While vendors pitch smart classrooms and predictive grading, few institutions have paused to ask, are we actually ready for this?
This brief explores the critical readiness gap between AI hype and the structural, ethical and policy foundations that education systems need in order to adopt these tools responsibly.
Drawing on emerging academic research and grounded systems thinking, this analysis outlines five institutional blind spots undermining equitable AI adoption governance infrastructure. The core recommendation? Frameworks before features. Diagnostics before deployment.
Algorithmic Authority in the Classroom: Reclaiming Human Judgment in the Age of AI
By Faith Ombewa | Digital Policy Strategist & AI Research Analyst
AI tools in education today go far beyond automating grading or administrative tasks and are increasingly shaping decisions about who learns what, how they are assessed and even what they are deemed capable of. In doing so, these systems introduce a new, largely invisible form of authority into classrooms, algorithmic authority.
This shift has outpaced public debate and policy oversight. According to Precedence Research (2025), the global AI-in-education market is already valued around $7 billion in 2025 with projected annual growth over 36%. Applications of AI and big data in education have made “significant headways” in areas like assessment, personalized learning and early-warning systems, yet governance, transparency and ethical safeguards have lagged behind this rapid adoption.
This brief interrogates the rise of algorithmic decision-making in educational settings, especially in contexts with limited digital literacy or weak regulatory protections.