The imposition of edtech: When market hype ignores pedagogical need

Martin Debattista, lecturer at ITS, lecturing on Digital Media, Digital Heritage Interpretation, Digital Tourism and ICT.

This forms part of a multipart blog series focusing on how academics are perceiving and dealing with the impact of generative AI on the education system.

The notion that education must evolve in response to a changing world is uncontroversial. Indeed, a healthy education system should not only reflect societal shifts but actively contribute to shaping them. The introduction of computers into the classroom from the 1990s onward was, in this sense, inevitable and necessary: students could not plausibly have left school with zero exposure to the technology reshaping the world outside it. The problem was never the principle but the execution. Hardware was rolled out faster than pedagogy could absorb it, and the presence of machines became a proxy for modernisation rather than a vehicle for learning. That pattern has not gone away.

The one-laptop-per-child programmes, the introduction of tablets in schools, and the interactive whiteboard procurement cycles, each wave has arrived with the same implicit promise that the technology itself constitutes the reform. The current discourse surrounding educational technology (edtech), particularly the frantic integration of artificial intelligence (AI) into learning environments, suggests that this cycle is accelerating: evolution dictated less by genuine pedagogical requirements than by market momentum and corporate sales narratives, with the added complication that the stakes of getting implementation wrong are now considerably higher.

Same old story

This pattern is hardly new. In the 1980s and 1990s, computers were celebrated as a cure‑all for educational problems, yet critical historians have shown how they were often ‘oversold and underused’. Nevertheless, the Internet and the computer have, over the decades, decisively changed the education landscape for the better, with far more accessible learning opportunities. It is impossible to imagine education in the 21st-century developed world without the use of computers and the Internet somewhere along the process of pedagogical planning and implementation.

However, some computing devices were pushed through as the ‘definite’ educational tool. In Malta, no organised educator’s lobby requested one tablet for every child in compulsory education. It was the politicians who, in 2013, at the height of the tablet craze, made an electoral promise, and educators had to adapt and try to make the best use of them. Malta’s performance in the OECD’s PISA evaluation of Maltese teenagers does not yet reflect the tens of millions spent in the One Tablet Per Child Project.

Smartphones raise the stakes even further because they blur the boundary between ‘school technology’ and students’ personal, always‑connected devices. Governments and agencies are now debating and in many cases implementing restrictions or outright bans on phones in classrooms, acknowledging that distraction, surveillance capitalism, and social pressures hitchhike on the same screens that could, in theory, support learning. That is, schools are once again reacting to a technology that arrived on students’ desks from the consumer market, not from an educational vision.

Solutions for non-existing problems?

What we frequently ignore is the political economy of edtech. University leaders and school administrators routinely describe being inundated with vendor pitches for platforms and analytics tools that solve problems they never identified, while genuinely needed, low‑glamour tools struggle to attract investment. In such a landscape, it is hardly surprising that AI is entering classrooms as a product category to be sold and integrated at speed, rather than as a potential ‘game-changer’ to the very notion of knowledge acquisition and traditional ‘learning outcomes’ that needs to be deliberated with educators and students. The latter did not need much thought to start exploiting this new wonder, to the chagrin of academics.

Students have been using ChatGPT and other generative AI tools for well over eighteen months; the deliberation that should have accompanied this shift has barely begun. Academia is notoriously slow to catch up with anything new, and in this case, the delay has meant that the terms of AI’s entry into education are being set not by educators or learners but by the vendors already in the room.

Venture capital plays a central role in this story. Specialist edtech investors do not just fund products; they actively imagine and promote particular futures of education, then try to make those futures real by backing the platforms that fit their vision. Recent work on the political economy of edtech investment shows how venture capital firms act as both economic and political actors, helping to restructure education as a growth market and normalising narratives of disruption, scalability, and data‑driven optimisation.

International educational organisations are starting to name this tension explicitly. The 2023 UNESCO Global Education Monitoring Report on technology in education warns that private commercial interests can clash with public goals around equity, quality, and democratic control, and stresses that technology must remain a means, not an end in itself. Yet the current AI boom in education investment is reminiscent of previous experiences in technology determinism.

The AI Juggernaut in Academia

This excitement is often coupled with a sense of inevitability, as exemplified by prominent investors and tech figures who frame AI’s arrival as an imminent, irreversible force. Matt Shumer is one of the latest examples, creating a tidal wave with an ‘essay’ on AI posted on X (formerly Twitter) in February 2026.

As AI capabilities become more sophisticated, they fundamentally challenge traditional assessment methods, as shown by emerging work on academic integrity in the era of ChatGPT and generative AI. The question is not if education should react to this change—it is essential that it does—but how. Is the current reaction a measured, pedagogically sound response, or a panicked scramble to accommodate powerful technological forces?

The narrative often leans toward the latter, fuelled by hyperbolic forecasts for the edtech sector. A glance at industry predictions reveals a market poised for explosive growth, with the global edtech and AI‑in‑education markets projected to expand dramatically over the next decade, according to recent market outlooks for edtech and AI in education.

Resistance to Change

This market-driven panic, which often ignores practical realities, becomes a primary mechanism for technological imposition. Sometimes educators do not even have time to ask the right questions.  Meta, formerly Facebook, pivoted towards AI in 2023 after promoting the Metaverse as the future of the internet just two years earlier.

Yet educators have long been characterised as resistant to change. Some of what reads as resistance is a rational response to decades of top-down reform imposed without consultation, resourced without continuity, and evaluated by metrics that bear little relation to what happens in a classroom. But some of it is exactly what it looks like. Two years after generative AI became a mass consumer tool, a significant proportion of educators have still not used it meaningfully, let alone integrated it into their teaching. Many are still treating ChatGPT as primarily a plagiarism problem rather than engaging with what it actually does. Students, meanwhile, have built sophisticated workflows around these tools using them to draft, revise, brainstorm, debug code, and prepare for exams while their lecturers debate whether to ban them or whether to flag an assignment as written by AI.

The gap is not flattering. And the honest difficulty needs acknowledging too: even willing educators face a genuine burden. Redesigning assessments, rethinking what constitutes original work, learning to use the tools well enough to teach with them rather than just about them, all of this is real, time-consuming labour, piled on top of already demanding workloads. For older educators especially, the cognitive and practical costs of continuous technological adaptation are substantial, and institutions have been far too comfortable expecting this work to happen in people’s own time, without compensation, recognition or structural support. AI sharpens all of this further.

Never an end in itself

There is a way out of this. The European Commission’s EmpowerED initiative has developed EdTech Ecosystem Roadmap. Estonia makes sustained investment in teacher digital competence alongside advanced infrastructure, not acquire the hardware first and then ask the pedagogical questions later. UNESCO’s 2023 Technology in Education report cited earlier has a recommendation for educators: the best interests of learners, not vendors or investors, should systematically eclipse commercial considerations when governments and institutions make edtech decisions, and that technology must remain a means, never an end in itself.