Recently, the third batch of government funds for the "old-for-new" replacement program was officially allocated, expanding the scope of subsidies to include AI (Artificial Intelligence) educational hardware. Products such as learning devices and smart lamps were introduced into the "old-for-new" subsidy category. As educational enterprises accelerate their exploration of AI applications, attempt to transform, and leverage policy support, the educational hardware market has rapidly expanded. However, challenges have arisen: Will smart education challenge traditional education models? How should individualized education be balanced with standardized education? And how can educational hardware overcome issues of product homogeneity?
Amid these dynamics, Laura, Executive President of TAL, was interviewed by "National Business Daily." Laura pointed out that AI is reshaping educational models. The inclusion of AI educational hardware into the subsidy program marks a shift from generalized subsidies to structural optimization in the educational hardware market. With the further development of artificial intelligence and big data models, smart education will not entirely replace traditional education and teachers but will enhance teaching efficiency and promote educational equity. At the same time, challenges such as hardware product homogenization and balancing human-machine relationships must also be addressed.
Image: Xueersi Smart Learning Devices Tablet
With the school season approaching, parents seeking learning "gear" have more choices than ever before. Reportedly, this year's subsidy program now includes learning devices in the "old-for-new" replacement scope. When asked about the impact of incorporating learning devices into the subsidy program on the industry, Laura told "National Business Daily" that this adjustment signifies a shift from inclusive subsidies to structural optimization in the educational hardware market. Through big data feedback and tiered subsidy strategies, policies are precisely aligning with market demands.
"From a short-term perspective, on the one hand, lowering the consumption threshold for learning hardware directly stimulates purchasing demand. On the other, policy subsidies further push us to optimize AI-based personalized learning features, thereby forming a positive cycle of 'technology upgrade—consumer demand—policy support,'" Laura stated. Enterprises are both beneficiaries and supporters of the subsidy program. She noted, "'National subsidy will significantly boost consumer enthusiasm, unlocking consumption capacity, while simultaneously accelerating the development and upgrading of AI educational hardware industries.'"
Many industry insiders echo Laura's views, suggesting that AI large models provide educational hardware with an opportunity to upgrade from functional devices to smart ones. This opportunity is closely tied to the speed of AI development. Since the rapid rise of artificial intelligence represented by large models toward the end of 2022, manufacturers have increasingly integrated AI functions into products, thus heralding a new wave of replacements, particularly for learning devices. According to statistics from LOTUS Technology, domestic sales of learning devices increased from 3,342,000 units in 2021 to 5,923,000 units in 2024, with a compound annual growth rate (CAGR) of 21%.
However, as learning devices and other educational hardware become "intelligent," a new challenge has emerged: AI functionality homogenization. "This situation is not limited to educational smart hardware; it's a universal issue across industries. For us, the focus lies in creating differentiation," Laura said.
Laura also mentioned that while many manufacturers’ learning devices may exhibit homogenized AI features, efforts toward differentiation and positioning can still be observed. "Some devices have particularly strong hardware capabilities, meaning advanced AI features; others excel in content, focusing on their own strengths." She emphasized.
It is worth noting that the phenomenon of homogenization is also linked to intensified competition due to the entry of more players into this market. Starting from 2023, many educational companies have ventured into the learning device segment, leveraging course strengths to compete with long-established major players for market share. "Market competition is indeed fierce because everyone may have seen the similar demand," Laura noted. "In the future, the educational hardware market will show clear trends towards industry leaders; however, there may also be surprising challengers, much like when AI large models initially came into the market," Laura added.
Image: Xueersi Smart Learning Devices Tablet ,Source https://xpad.xueersi.com/?source_id=61
Despite the current buzz surrounding the learning device market, Laura believes that educational hardware is merely a microcosm of smart education. Zooming out, the development of smart education and AI applications in education are pivotal to education reform, which is reshaping traditional educational models.
Laura asserted that in offline education contexts, significant strides have been made. Based on field studies, a large number of schools, from teachers to students, have adopted creative methods such as personalized learning plans and project-based teaching to transform traditional educational models. This includes experimenting with smart hardware, AI tools, AI teachers, or AI-enriched lesson planning, as part of smart educational ventures.
As for hot debates over whether smart education will challenge traditional education, particularly in balancing individualized education and standardized approaches, as well as technology’s influence in redefining teachers' roles, Laura offered her perspective. She stated that smart education is not about replacing human teachers with machines; rather, it assists teachers by automating routine tasks such as grading assignments, dictation, or gathering pre-class materials, allowing teachers to focus their energy on personalized student education. Hence, AI’s standardized solutions and the need for individualized education are not inherently conflicting. For instance, applying intelligent agents in educational settings can substantially reduce marginal costs of education and improve learning efficiency.
Laura further highlighted a critical benefit of smart education: the promotion of equitable access to educational resources. With the progress of big data, high-quality educational resources and courses will become increasingly open and accessible. Moreover, students, with their generally early exposure to digital environments, exhibit stronger adaptability to new technologies, often surpassing parents in adopting AI tools, catering to diverse age groups’ learning needs.
Like many educational practitioners, Laura is confident that AI will drive significant transformation in the education sector. "Artificial intelligence will inevitably bring tremendous changes to education, and these changes will occur at a relatively rapid pace," Laura asserted.
Source: National Business Daily https://m.nbd.com.cn/shendu/2025-08-29/4041340.html
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