
2026 is widely regarded as the “Year Zero of Global AI Education” [1, 11], marking that artificial intelligence (AI), especially generative AI, has evolved from sporadic technology introductions into a core force driving the profound reconstruction of the global education system [ 4 ]. Governments and international organizations around the world have introduced special policies with unprecedented strategic determination, incorporating AI literacy into the core of national education, forming an educational reform race that concerns the future national strength [2, 9, 17]. However, the rapid iteration and large-scale application of technology have also exposed systemic dilemmas in the education field, such as insufficient governance framework, lagging teacher training, impact on assessment systems, and difficulty in regulating ethical risks [3, 5, 28]. This paper aims to respond to this era and, from an “inclusive” perspective, cover all stages from basic education to lifelong learning, to conduct a balanced and integrated analysis of the current “policy governance” and “teaching practice” of AI education. This paper first reviews the AI education strategic layout of major global economies (China, the US, Taiwan, South Korea, Japan, etc.) around 2026, presenting a development model where "national will-driven" and "diversified autonomous exploration" coexist [1, 9, 29]. Secondly, it delves into the "real problems" and "pseudo-prosperity" at the teaching practice level, exploring the core debates regarding AI's role positioning (assistant vs. substitute), application scenarios (administrative burden reduction vs. thought-provoking), and human-machine collaboration models [5, 14]. The paper pays particular attention to the evolution of AI literacy from "tool use" to "coexisting wisdom," and discusses its fundamental requirements for curriculum design and assessment reform [1, 3, 6]. Finally, this paper integrates policy and practical insights, proposing a systematic governance framework encompassing "top-level design, support system, ethical safeguards, and ecological collaboration," arguing that only by adhering to "technology for good and education as the foundation," and upholding the original aspiration of education amidst the technological wave, can we ensure that AI truly empowers the comprehensive development of individuals [5, 10].
The first year of AI education, generative AI, AI literacy, education governance, human-machine collaboration, policy framework, teaching practice, lifelong learning
The first year of AI education, generative AI, AI literacy, education governance, human-machine collaboration, policy framework, teaching practice, lifelong learning
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