Is AI a scapegoat for destroying education and learning?

“Debates surrounding AI in education often reflect broader technological anxieties. Hitoshi Nishimura , Ranmaru Kishitani and Yudai Sakamoto argue that it is not AI itself that undermines learning but its use primarily to accelerate task completion rather than for strengthening teaching-learning cycles. While the challenge is exacerbated by insufficient AI literacy, it could be overcome by improving soft skills in educational roles. One discussion about generative artificial intelligence that has swept across academic, business and media discussions is whether AI is destroying education and learning. Studies like MIT’s Your Brain on ChatGPT offer preliminary insights into the cognitive effects of AI use. Such studies are potentially useful for understanding the issue, but complications arise when implications are extrapolated far beyond the researchers’ claims , fuelling public anxiety and shaping discussions. Indeed, panic about AI in education is not new and AI has revealed weaknesses rather than caused destruction. We recommend thoughtful reflection to consider both the benefits and challenges of AI in education. Re-examining education and learning “Learning” is the process by which individuals acquire new knowledge , skills, attitudes and values. And “education” refers to the structured process of teaching and learning that typically occurs within institutional settings. Effective education bridges the zone of proximal development , the gap between what learners can do independently and what they can achieve with skilled guidance. Understanding education as a system that supports teaching and learning, two roles become visible: the educator and the learner. As illustrated in Figure 1, learning is a continuous cycle between the two, in which the educator prepares and delivers materials and training opportunities and the learners work to master them. This generates feedback on progress, which the educator uses to analyse and design subsequent guidance. This cycle depends on a reliable feedback loop between these two parties. When that loop is distorted, the value of education weakens. Figure 1. The teaching-learning cycle in education for effective learning . AI provides a scapegoat for education’s long-existing fragility AI adoption can lead to concerning disruption of the teaching-learning cycle. When people utilise the tools merely to complete assigned tasks it may increase task efficiency but not align with the core objective of providing and receiving education. Educators may earn greater financial or personal benefits while failing to provide materials and opportunities that genuinely support learners. Similarly, when using AI, learners may fail to acquire the knowledge and skills they need. Instead, they may take shortcuts that save time and effort and be credited, ultimately undermining the purpose of education. But AI is not the cause here. The purposes of providing and receiving education had diversified long before AI emerged. Workarounds, such as using ghostwriters to write essays, were already in place. What has changed is the ease and prevalence of such workarounds, driven by greater accessibility and the reduced perceived risk of detection. For individuals whose engagement with education is primarily instrumental, for example focused on earning credits or qualifications, AI can be used to appropriately help them achieve their goals, but it is not used to enhance learning outcomes. In this sense, AI has simply revealed and accelerated the extent to which learning in education had already become secondary for some learners. Nevertheless, it is being blamed for a problem it did not initiate. Public concerns over the educational impacts of new technologies are not new . Learning has been transformed, for instance, by computers and calculators, and earlier concerns about them mirror today’s anxieties. Such anxieties follow a recurring, Sisyphean cycle of technology panics , with AI as the latest entry. What may be different is that greater instability and unpredictability, rising from AI’s capabilities and its agentic presence in interaction. It is crucial to respond to these developments with composure and an understanding that society may be experiencing a new form of technological panic. How AI can enhance education for educators and learners How AI-literate educators and learners can enhance the teaching learning cycle with AI becomes clearer when the cycle is decomposed (as illustrated in Figure 1). From educator to learner, AI enables educators to create and customise high-quality, personalised materials for learners at various levels, reducing time and expertise requirements. For learners, when they struggle to understand something, AI eases practical and psychological barriers associated with searching the internet or asking others, and offers patient, adaptive explanations instantly, even when learners themselves are not clear about where they are struggling. From learner to educator, AI streamlines feedback by giving immediate, detailed assessments that detect subtle patterns human evaluators might miss. For example, feedback on second-language speaking practices previously relied on skilled assessors, cross-checking and high costs; AI now measures factors such as pause duration and sentence complexity more efficiently. For educators analysing learning status, rather than simply checking the accuracy of the answer, they can examine how learners reached that answer, where they hesitated, which errors recur and which types of intervention are likely to be most effective. Consequently, when learners are genuinely motivated to acquire knowledge and skills rather than merely to secure grades, AI can enhance learning outcomes and may even support forms of “ hyper-learning ”, unusually rapid or intensified learning driven by highly responsive, information dense interaction. How AI can enhance educational businesses For educational organisations seeking profits, the strategic challenge is to integrate AI in ways that support both organisational efficiency and long-term learner development. The traditional education business, which relied on limited access to educational content as a source of value, is now fundamentally destabilised. The source of value shifts from what is taught to how the learning experience is designed. AI-literate educators can reduce administrative burdens and focus on higher-value work and new responsibilities to administer the learning experience. But these advantages must be sought with the understanding that AI tools often intensify work rather than reduce it. Although it initially appears to yield a productivity gain, this can become unsustainable without safeguards. AI increases the “quality × frequency × speed” of each step in the learning cycle, but humans remain responsible for auditing content, supporting learners and making judgment calls. For this reason, the institutions that will thrive are those that harness AI’s efficiencies while protecting and empowering humans from work overload. The evolving role of the provider The technological transformation in education has significant implications for the value of human educators. While AI may optimise personalised planning and facilitate the implementation of gamification , the full role of the human educator does not appear to be easily replaceable. In real learning contexts, the biggest bottleneck is motivation. Educators are often committed by professional expectations or compensation, whereas learners are under no such obligation to engage. Learners may easily ignore an AI study reminder, but they are far less likely to skip a schedule with a human teacher. Here the essential functions of an educator extend beyond traditional teaching to include maintaining engagement, creating a sense of accountability, understanding each learner’s personal context and offering a human connection. This reality underscores a strategic need to invest not only in tools but also in humans to strengthen the soft skills that complement and enhance the AI-enhanced teaching and learning cycle. A strategic path forward The strategic question is not whether to embrace or reject AI, but how to find the space between purposeful integration and reactive adoption. Although AI affects every component of the learning cycle to an extent that qualitatively outstands previous innovations, claims that AI is “destroying education and learning” are analytically imprecise and unnecessarily alarmist. For educational institutions and enterprises adopting AI, these changes create opportunities rather than threats. AI invites a re-examination of the skills and structures needed for the future of work and encourages a return to the essence of education: supporting people who genuinely want to learn, while helping others discover that motivation through guidance rather than shortcuts – and strengthening the foundations for better human learning. This article gives the views of the author, not the position of LSE Business Review or the London School of Economics. You are agreeing with our comment policy when you leave a comment. Image credit: Visual Generation provided by Shutterstock. 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