An Inflection Point
Artificial Intelligence (AI), and more recently generative AI, has captured public attention for its transformative potential across nearly every sector. Yet perhaps nowhere is its impact more profound and underappreciated than in the realm of education. For developing and developed economies alike, AI offers an opportunity to personalise learning, improve outcomes at scale, and better equip the next generation for a world shaped by rapid technological change.
But there is a caveat. The benefits of AI in education are not automatic. Without the right infrastructure, policies, and safeguards, AI will exacerbate inequality, compromise educational integrity, and deepen the global skills gap. With thoughtful design and urgent action, AI-enabled education can be a real force for national competitiveness and social equity.
What the Research Tells Us
Recent studies demonstrate clear and measurable benefits from integrating AI into education.
In 2024, a World Bank-backed pilot in Nigeria used a gen AI tutor (based on GPT technology) in after-school English classes. The results were striking, with pupils achieving learning gains equivalent to two years of traditional schooling within just six weeks. Girls, in particular, closed previous gender gaps, and teachers reported renewed enthusiasm for their roles.
An economic model published by the Tony Blair Institute projected that a national rollout of AI-powered personalised tutoring in the UK could increase GDP by 6% over the long term.
In countries such as South Korea and Singapore, AI is being embedded across primary and secondary education systems. South Korea is developing AI-powered digital textbooks and training thousands of teachers to deliver AI-enhanced lessons. Singapore has announced a national initiative to build AI literacy in all students and equip all teachers with AI-pedagogy skills by 2026.
In the United States, President Trump’s 2025 Executive Order, Advancing Artificial Intelligence Education for American Youth, mandates that all pupils be taught about AI, supported by national funding and the creation of a White House Task Force. Though it stops short of mandating the use of AI in teaching, it marks a policy shift that will likely accelerate broader adoption.
Globally, there is now widespread recognition that AI is not a passing trend, but a foundational shift in how learners engage with content, how teachers deliver instruction, and how education systems measure and support progress.
Converting Challenges into Opportunities
Despite these gains, the use of AI in education presents challenges. But each downside, if managed well, can be converted into an advantage:
- Academic Integrity and the Shape of Assessment
One of the most immediate concerns about AI in education is its impact on academic honesty. With tools that can generate essays or solve problems in seconds, students may be tempted to sidestep the learning process altogether. But banning AI or ramping up surveillance misses the point.
We need to rethink how we assess learning. Oral exams, collaborative projects and applied tasks make cheating harder and encourage deeper engagement. These approaches reward not just answers, but the thinking behind them. When students are also asked to declare and reflect on their use of AI, we promote transparency instead of secrecy.
Of course, not every school has the capacity to adopt new assessment methods at scale. Defining what counts as legitimate AI use is also complex. Clear policy, staff training and ethical literacy must accompany any shift in assessment. If we get this right, we protect integrity and embed it more deeply in education.
- Over-Reliance and the Erosion of Thinking
AI makes it easy for students to become passive users rather than active learners. Why wrestle with a problem when an app can answer it instantly?
This is where teaching practice must evolve. “Human-in-the-loop” strategies, where students critique, improve or explain AI-generated outputs, can help them build judgement and independence. Assignments that begin with AI but demand human reasoning steer students towards deeper understanding.
This actively improves learning. Students gain not only knowledge but also the skills to challenge, refine and question what they are given. But this takes time and support. Without that, we risk swapping shallow learning for something even more hollow.
AI-augmented learning must also be built on a strong foundation of knowledge. A ‘knowledge-rich’ curriculum remains essential. Students need structured, sequenced content knowledge to scaffold critical thinking and long-term understanding. AI can amplify this, but it cannot replace it. Deep learning depends on human memory, schema-building, and coherent worldviews that AI alone cannot provide.
- Inaccuracy, Bias and the New Digital Literacy
AI can produce false or biased information with an air of authority. From factual errors to cultural assumptions, these systems reflect the data they’re trained on, and can mislead.
Students need to learn how to deal with this. Teaching them to fact-check, use tools that cite sources and verify claims through cross-checking turns a problem into a learning opportunity. Reviewing AI-generated content together helps students see where bias and error creep in, and who gets left out. The skills they learn in this way provide benefits well beyond just AI and technology.
This isn’t just about digital skills. It is about forming critical, informed thinkers who can navigate an environment where the line between true and false is increasingly blurred.
AI systems can also subtly shape how learners understand the world. Left unchecked, they may reinforce homogenised or dominant cultural narratives. For this reason, AI tools in classrooms must align with national curricula and support pluralistic, inclusive worldviews.
- Data, Privacy and Building Trust
AI tools often collect large amounts of data from students. Without safeguards, that data can be misused or stored insecurely. Schools must lead on this. They should choose systems that limit data collection, store information locally or within legal jurisdictions, and comply with AI, privacy, and data regulations. Just as importantly, they should explain clearly to students and parents how data is collected and why.
This is not just a compliance issue. Strong data governance helps build trust, which is essential for responsible and sustainable use of technology in schools.
- The Human Connection in AI-Augmented Classrooms
Some worry that AI tutors could replace teachers. In fact, they offer a chance to free teachers from routine tasks like marking and admin, allowing more time for mentoring and support.
But this shift is not automatic. If technology replaces rather than supports human interaction, students may feel isolated or neglected. Emotional and social development depends on human relationships, especially in younger learners.
The real opportunity lies in using AI to strengthen, not replace, the human core of teaching. Teachers become even more vital as mentors, role models and guides. Importantly, their subject expertise is irreplaceable. Currently, only skilled educators can sequence knowledge, contextualise complex ideas, and respond to learners’ cognitive and emotional needs in real time.
- Equity, Access and the Risk of Exclusion
AI could entrench educational inequality. Well-funded schools will adopt cutting-edge tools, while others risk being left behind. Policymakers need to act. That means investing in infrastructure like broadband and low-cost devices and using open-source models in local languages. But access alone is not enough. Teachers in disadvantaged areas must also be trained and supported to use AI effectively.
Done well, this creates the chance for some to leap ahead, bypassing traditional constraints. It could be a catalyst for inclusive, high-quality education at scale.
The Case for Urgency
The urgency to act is not just about potential gains. It is also about the risk of falling behind.
AI productivity gains are already flowing disproportionately to wealthier nations. If developing economies fail to adopt AI in education within the immediate future, they risk locking in a generational skills gap that will be expensive, or impossible, to reverse.
On the flip side, countries that embrace AI-enabled education can build a future-ready workforce faster and cheaper than ever before. Just as Ireland and Singapore invested early in education to become global knowledge hubs, developing countries today can position themselves as competitive, tech-savvy economies.
Human capital is still the bedrock of national competitiveness. AI does not replace that; it accelerates it. But only for those who build the rails for it to run on.
A Five-Pillar Framework for Action
To convert AI in education into a national advantage, governments should pursue the following:
- Ensure universal access to broadband, and basic devices. Prioritise edge models or locally hosted AI where connectivity is weak.
- Embed AI literacy in teacher training, and offer ongoing support in prompt engineering, supervision, and ethical oversight.
- Customise AI models to reflect national curricula, minority languages, and local cultural contexts.
- Adopt global best practice on ethical AI use and enforce transparency, explainability, and safety standards.
- Link AI learning to national sector goals, e.g. digital health, fintech, or manufacturing, so students graduate into relevant, growing industries.
AI as a National Education Dividend
AI is not a silver bullet. But it may be the most powerful lever available today to close the learning gap between rich and poor, urban and rural, mainstream and marginalised. The technology exists, the research is growing, and costs are falling. Too often what is missing is urgency.
Countries that act now to responsibly integrate AI into education will equip a generation to thrive in the economies of the future. Those that delay may find themselves caught in a widening chasm of skills, relevance, and competitiveness.
This is not something that should be left only to the private sector (although it has a huge role to play). It is something that must be addressed urgently at national level, just as we have seen in South Korea, Singapore, China and elsewhere.