Five Chinese Ministries Launch "AI+Education" Action Plan

To implement the State Council’s Guiding Opinions on Deepening the "AI+" Initiative, the Ministry of Education, National Development and Reform Commission, Ministry of Industry and Information Technology, Ministry of Science and Technology, and National Data Administration have jointly issued the "AI+Education" Action Plan (hereinafter referred to as the "Plan"). The Plan aims to advance AI talent development and application innovation in tandem, coordinate the construction of foundational environments and innovative ecosystems, and systematically build an education system fit for the intelligent era. Key provisions are summarised below.

The Plan sets out four key tasks for the 15th Five-Year Plan period (2026–2030). First, advancing AI talent development and literacy enhancement. In basic education, schools must offer AI courses fully, appropriately and effectively, cultivating students’ intelligent thinking. At higher education institutions, AI will be integrated into the general foundational curriculum. In vocational education, traditional disciplines will undergo intelligent transformation to cultivate high-skilled personnel adaptable to industrial change. In lifelong education, high-quality AI learning resources will be aggregated and developed to ensure equitable access for all learners. Teachers’ digital literacy and competencies will also be comprehensively upgraded to stimulate their intrinsic motivation to innovate pedagogical models using AI. Second, promoting deep integration of AI and education. AI will empower student learning—supporting holistic development across moral, intellectual, physical, aesthetic and labour education; meeting diverse, personalised learning needs; and advancing educational quality, equity and inclusion. It will empower teaching—enabling intelligent applications across pre-class, in-class and post-class phases. It will empower institutional governance—facilitating convenient services, precise management and evidence-based decision-making. It will empower research—driving paradigm shifts in scholarly inquiry through AI. Third, strengthening foundational infrastructure for "AI+Education". This includes building a national intelligent education computing platform (the “Education Intelligence Internet”), delivering high-quality computing power, data services, model capabilities and agent tools; nurturing an application ecosystem through multi-stakeholder co-creation; establishing an AI application capability evaluation system to identify mature, high-quality tools; and developing future-oriented educational spaces—including future classrooms, schools, learning centres and training centres. Fourth, building an open ecosystem for "AI+Education". This entails deepening interdisciplinary research and innovation; establishing a collaborative “government–industry–academia–research–finance” mechanism to foster high-quality intelligent education products; reinforcing policy, regulatory and institutional support aligned with AI development; expanding international cooperation to promote Chinese public goods and standards abroad; and strengthening security safeguards to uphold AI safety boundaries.

The Plan stresses that Party leadership must permeate all stages of the "AI+Education" initiative, with strengthened organisational leadership, strategic planning, guidance, supervision and resource support. The Ministry of Education will coordinate with the NDRC, Ministry of Science and Technology, MIIT and National Data Administration to jointly advance implementation. Local authorities and institutions must incorporate "AI+Education" into their development plans, launch application demonstrations, pilot AI-enabled education initiatives, and promptly share exemplary practices.

Full text of the Plan follows:

"AI+Education" Action Plan

This Plan is formulated in accordance with the strategic deployment of the Outline for Building an Education Powerhouse (2024–2035) and the requirements set forth in the State Council’s Guiding Opinions on Deepening the "AI+" Initiative.

I. General Principles

Guided by Xi Jinping Thought on Socialism with Chinese Characteristics for a New Era, and implementing the spirit of the 20th National Congress of the Communist Party of China, its subsequent plenary sessions, and the National Education Conference, this Plan fully implements the Party’s educational policy and the fundamental task of fostering virtue through education. It advances the national education digitalisation strategy, upholding people-oriented education, literacy-first development, application-driven design and ethically grounded intelligence. It leverages AI as a catalyst for educational transformation, promoting full-element integration, end-to-end connectivity and all-scenario coverage of intelligent technologies in education. It coordinates AI talent development and application innovation, synergises foundational environment and innovation ecosystem construction, and accelerates the formation of a new, intelligent education paradigm characterised by human–machine collaboration, virtual–physical integration and ubiquitous accessibility. It seeks to harmonise mass education with individualised cultivation, knowledge transmission with competency development, and technological application with humanistic care—thereby cultivating high-calibre talents equipped for the intelligent era and providing strong impetus for building an education powerhouse and delivering education that satisfies the people.

By 2030, deep integration of AI and education will be largely achieved. A vertically coherent and horizontally connected AI education system spanning all academic levels and extending to society-wide general literacy will be established. The scale and quality of AI talent development will improve markedly, and a long-term mechanism for cultivating universal AI literacy will be institutionalised. Teaching methodologies, research paradigms and governance models will undergo systemic transformation; education service delivery capacity and modernisation levels will rise significantly; foundational support environments will become more streamlined and efficient; the innovation ecosystem will grow more open and collaborative; AI applications will become more inclusive, secure and effective; and a series of high-value, scalable, replicable application scenarios will emerge. A new intelligent education paradigm will be essentially formed, ranking among the world’s best in global influence.

II. Advancing AI Talent Development and Literacy Enhancement

(1) Accelerating AI Education for Primary and Secondary School Students. The Guidelines for General AI Education in Primary and Secondary Schools will be continuously refined, ensuring AI-related courses are offered fully, appropriately and effectively. AI education will be comprehensively integrated into local curricula, with guidance provided to regions on developing subject-specific AI curriculum guidelines—including clear learning objectives, content and time allocations per stage. Interdisciplinary AI instruction will be encouraged, and AI education incorporated into after-school services and experiential learning programmes. Scientific and humanistic education will be combined, focusing on intellectual stimulation and emotional development, guiding students to understand and use intelligent technologies responsibly, enhancing AI literacy, nurturing curiosity and innovative thinking, and improving cognitive reasoning and complex problem-solving abilities. AI education demonstration bases will be strengthened, supporting rural and remote-area schools in delivering AI courses via the national platform.

(2) Cultivating High-Level Talent for the Intelligent Era. AI will be introduced as a compulsory foundational course across universities, with discipline-specific textbooks developed. All students will be supported to acquire core AI knowledge. Short, practical and cutting-edge innovation courses will be designed to reflect AI’s technical characteristics. Traditional disciplinary training frameworks will be optimised, with AI-integrated interdisciplinary courses and cross-disciplinary course clusters enriched to cultivate compound, interdisciplinary talent. Disciplinary and professional structures will be adjusted to align with AI-driven industrial upgrading, and new disciplines and majors responsive to emerging technologies, industries and business models will be launched. World-class research universities, leading technology enterprises and national laboratories will collaborate to deepen interdisciplinary research, industry–education integration and science–education synergy, exploring novel models for cultivating top-tier AI innovators.

(3) Upgrading and Transforming Vocational Education Programmes. The structural impact of AI on vocational education will be continually assessed, and skill-based talent requirements updated accordingly. Traditional programmes will undergo intelligent upgrading, with scientifically designed “AI+” disciplinary systems, curricula and pedagogical frameworks enhancing alignment between programme offerings and industrial development. In response to national AI industry demands and the need to nurture emerging and future industries, a cluster-based high-skilled talent development programme for AI fields will be implemented. Collaborative talent development schemes will be co-developed with industry partners, curricula updated, and shared internship, training and practice bases established to target emerging occupational roles.

(4) Promoting AI General Literacy Across Society. Digital resources on the national platform will be continuously enriched, aggregating and developing AI general literacy materials. Universities and enterprises will be encouraged to develop discipline-specific AI resources, made openly available to students and lifelong learners. AI will be included in universities’ “Dual-Thousand” initiative for graduate employability enhancement, with micro-specialisations and micro-certification programmes promoted to support high-quality employment. Universities and Open Universities will tailor AI literacy and skills courses for priority groups, offering personalised continuing professional development and enabling credit accumulation in the national credit bank. Continuing education degree programmes will be restructured and curricula revised, and self-taught examination programmes expanded to include AI-related disciplines.

(5) Enhancing Teachers’ AI Literacy and Competencies. Standards for teachers’ AI literacy will be established, specifying required competencies. Tiered, role-specific AI literacy training will be delivered through multiple channels to achieve full coverage. Contextualised assessment systems and intelligent, progressive evaluation tools will be developed; large-scale literacy assessments will be encouraged at regional and institutional levels, with targeted interventions based on results. Teacher education reform will integrate frontier technologies—including AI—into curricula and knowledge frameworks. AI will be incorporated into teacher qualification examinations and certification processes, and AI-focused projects added to national and provincial teaching achievement awards to stimulate innovation.

III. Promoting Deep and Extensive Integration of AI and Education

(6) Empowering Student Learning with AI. To support holistic development across moral, intellectual, physical, aesthetic and labour education, intelligent learning companions will be developed. Large language models for ideological and political education will be built to enrich smart ideological education applications and establish immersive, all-domain, all-stakeholder, real-time ideological education models. Student digital profiles will be created to dynamically optimise learning pathways according to individual aptitudes, traits and interests—better meeting diverse learning needs. Effective pathways for AI-enabled physical education, aesthetic education, labour education and science education will be explored to support personalised growth. AI applications will be promoted in central and western regions and rural schools to facilitate autonomous learning, popularise standard Mandarin, and advance educational equity. Intelligent assistive devices will be developed to support monitoring, assessment and rehabilitation for students with special educational needs, promoting inclusive education.

(7) Empowering Teaching with AI. Intelligent teaching systems will be applied across the entire teaching cycle—pre-class, in-class and post-class—to reduce teacher workload and enhance effectiveness. Pre-class preparation will be supported through learning analytics, multimodal teaching resource generation, lesson plan optimisation and teaching simulation, enabling human–machine co-creation. Human–machine collaborative teaching models will be piloted, incorporating intelligent systems into classroom activities, developing highly interactive virtual simulations, and enhancing immersive experiences and personalised feedback to improve pedagogical quality. Post-class assignment management will be assisted through intelligent marking, Q&A and tutoring. Classroom teaching behaviours will be analysed using AI to conduct evidence-based teaching research and build teacher professional development models suited to the intelligent era, helping educators improve instructional quality.

(8) Empowering Educational Governance with AI. An “Education Intelligence Brain” will be built to deliver convenient services, precise management and scientific decision-making. A national talent supply–demand big-data platform will be established to conduct surveys, predictive analysis and evaluation feedback on talent demand. AI will be used to forecast demographic and industrial trends scientifically, refining mechanisms for resource allocation and discipline adjustment. Applications such as intelligent test item setting, paper assembly, invigilation and marking will be advanced. Intelligent tools for educational evaluation will be developed to explore longitudinal assessment of students’ learning processes and horizontal assessment across all domains of moral, intellectual, physical, aesthetic and labour development. An intelligent employment service system will be built to recommend jobs to university graduates, promoting high-quality, full employment. Massive, multimodal monitoring data will be efficiently analysed to enhance real-time campus safety risk warnings and emergency response capabilities, supporting safe campus development.

(9) Empowering Scientific Research with AI. In natural sciences, engineering and philosophy/social sciences, scientific AI agents and intelligent tools will be developed and promoted—e.g., through challenge-based project funding—to help researchers discover and synthesise patterns and solve complex problems. Interdisciplinary AI innovation platforms will be built to strengthen AI-led convergence across disciplines, expand knowledge frontiers, and accelerate exploration of new research paradigms for the intelligent era. Foundational research platforms and scientific infrastructure will undergo intelligent upgrades, including intelligent laboratories and autonomous experimental clusters capable of automated experimental design, execution and data analysis—enhancing research innovation efficiency. The intelligent features of the university scientific achievements trading platform “KeHuiJiao” will be deepened to enable intelligent perception of enterprise needs and matching of research outcomes, fostering new productive forces.

IV. Strengthening Foundational Infrastructure for "AI+Education"

(10) Building an Integrated, Efficient Intelligent Education Foundation. A national education intelligent computing platform will be constructed to consolidate computing power, data, models and tools. The China Education and Research Network will connect national computing training facilities, computing hubs, enterprises and universities, integrating intelligent, general-purpose and supercomputing resources. Provincial education authorities will be encouraged to leverage the national integrated computing network to ensure AI application support. National foundational corpora will be developed for ideological education, disciplinary knowledge and scientific research; region- and university-specific domain datasets will be encouraged. The National Education Big Data Centre will be strengthened, establishing cross-departmental, cross-regional and cross-platform data networks, and exploring dynamic updating mechanisms based on platforms, journals and terminals. Nationally coordinated R&D will produce AI education large language models tailored to each education stage, prioritising value alignment, logical reasoning and ethical safety to support local and institutional applications and avoid redundant or low-level development.

(11) Fostering a Co-Creation and Sharing Intelligent Application System. The national platform will undergo intelligent upgrading to enable personalised resource delivery, intelligent service processing and intelligent data analysis. A collaborative mechanism linking universities and primary/secondary schools will be established to jointly develop AI curricula and applications. National AI (Education) Application Pilot Bases will be built to provide public goods—including student knowledge, competence and quality maps—to lower innovation barriers, nurture application service systems, and accelerate intelligent product and service deployment. AI learning communities will be established to aggregate open-source courses, provide innovation resources, conduct outcome certification, and encourage faculty and students to participate in open-source ecosystem development—enabling corpus co-construction, model co-testing and application co-creation to sustainably cultivate high-quality intelligent education applications. An intelligent application capability evaluation system will be established to select and certify AI agents for different educational roles and scenarios, with top-performing tools deployed on the national platform. AI pilot application scenario projects will be organised to create high-value benchmark applications.

(12) Building Future-Oriented, Virtual–Physical Integrated Educational Spaces. Future classrooms, schools, learning centres and training centres will be developed to bridge the “last mile” of AI application. Teaching and practice capability centres will be established in key disciplines to develop high-quality AI-integrated courses and projects, supporting intelligent disciplinary upgrading. Digital textbooks will be piloted; next-generation intelligent MOOCs launched; and virtual simulation experiments deepened to enrich digital resource formats, construct immersive teaching spaces and establish new human–machine collaborative pedagogical models. Intelligent terminal applications will be promoted, using big-data analytics to build student user profiles and allocate learning resources centred on the learner—supporting personalised learning within mass education. Education large language models and intelligent agent tools will be integrated to build thematic learning scenarios, promoting project-based, inquiry-based and scenario-based pedagogy to guide students in critical thinking and cultivate competencies for the intelligent era.

V. Optimising the Development Ecosystem for "AI+Education"

(13) Conducting Research and Innovation in "AI+Education". Interdisciplinary collaboration will be promoted across AI, cognitive science, neuroscience, psychology and pedagogy to innovate educational research paradigms and deepen understanding of educational principles and cognitive development. Ongoing AI social experiments will be conducted, AI ethics research deepened, and the societal impact of AI on education scientifically assessed. A technological innovation system for "AI+Education" will be built, with joint research platforms and educational practice research bases strengthened. Common, critical technology R&D will be organised, encouraging universities, enterprises and research institutes to participate in ecosystem development. Long-term, patient and strategic capital from state and private sources will be channelled into educational technology innovation, ensuring advanced technologies serve human development.

(14) Strengthening Conditions and Support for "AI+Education". Policies and regulations covering AI training, application innovation, technology R&D and security assurance will be reinforced to build an education policy framework aligned with AI development. Education institutions, enterprises and research units will be encouraged to develop standards and norms for AI applications in education, large language model evaluation and data security. Talent team development models will be innovated, attracting experts from universities and enterprises to join development efforts and cultivating a high-calibre, multidisciplinary engineering team. Innovative investment models—including service procurement—will be supported, establishing a diversified funding mechanism led by government and involving universities, society and enterprises.

(15) Promoting International Cooperation in "AI+Education". Major international conferences—including the World Digital Education Conference, World MOOC and Online Education Conference, and International Conference on AI and Education—will continue to be hosted. The AI Open Alliance, World Digital Education Alliance and World MOOC and Online Education Alliance will be strengthened as flagship international exchange platforms. Bilateral and multilateral mechanisms will be leveraged to advance country- and region-specific educational cooperation, sharing multilingual AI courses, education large language models and AI agents, and facilitating mutual learning and experience exchange. China will actively engage in global education governance, participating deeply in international agenda-setting, rule-making and standard development for AI in education through key international organisations such as UNESCO, thereby enhancing China’s global influence in digital education.

(16) Strengthening Security Safeguards for "AI+Education". A security protection system for AI educational applications will be established, with tiered, classified security standards defined. A rigorous review mechanism for education large language models will be deepened to ensure generated content is positive, healthy and constructive. A security evaluation standard for AI educational applications will be established, safeguarding the security of models, algorithms, data resources, infrastructure and application systems in an integrated manner—and ensuring technological applications conform to educational principles. Software legalisation will be promoted to guarantee AI applications are secure, trustworthy and controllable. AI use in schools will be strictly regulated, with clear norms for intelligent products and terminals. Mechanisms for AI application evaluation, registration, technical monitoring, risk warning and emergency response will be improved to effectively prevent AI-enabled fraud, academic misconduct, exam-oriented pressure, privacy breaches and other risks.

VI. Implementation and Organisation

Party leadership must be upheld throughout the implementation of the "AI+Education" initiative, with strengthened organisational leadership, strategic planning, guidance, supervision and resource support. The Ministry of Education will formulate and coordinate implementation of the Plan; the NDRC will strengthen coordination and support eligible projects; the Ministry of Science and Technology will reinforce research layout in key areas; and the MIIT and National Data Administration will provide policy support to promote open-source development and data interoperability. Local authorities and institutions must incorporate "AI+Education" into their development plans, devise institution-specific implementation schemes, and actively launch application demonstrations. Think tanks and advisory bodies will be strengthened to support policy research, frontline guidance and strategic advice. Thematic training will be organised to enhance AI leadership among education administrators. AI-enabled education pilot initiatives will be deeply implemented, establishing a data-informed, routine application supervision mechanism, and exemplary practices will be promptly summarised and disseminated.

Source｜Weiyang Education