Introduction

General Secretary Xi Jinping has profoundly pointed out that “artificial intelligence is a strategic technology leading this round of technological revolution and industrial transformation, with a strong ’leading goose’ effect.” AI is not merely a linear iteration of a single technology or a partial upgrade of a certain industry; rather, it represents a comprehensive and disruptive reconstruction of the underlying logic of economic and social operations. To assess its development level and trends, we must break free from traditional technology evaluation and industry analysis frameworks, and conduct a comprehensive analysis from dimensions such as technological capability, industry scale, factor support, and integrated applications to glimpse the full scope and direction of this profound transformation.

Technological Capability

From the perspective of technological capability, AI technology led by open-source has achieved breakthroughs, forging new standards within the global developer network. During a survey at a laboratory, we observed that the research team introduced an AI self-criticism mechanism, eliminating the need for human intervention. After multiple rounds of self-play, the model’s accuracy in solving complex programming problems significantly improved. AI has progressed from “being able to listen and see” to “thinking, reasoning, and planning,” and now to “mastering how to learn.” Overall, China has continuously narrowed the gap with international top levels in key indicators such as model performance, training efficiency, and multimodal integration, with some fields achieving parity or even leading. By 2025, China’s share of global downloads of open-source models is expected to reach 17.1%. Recent statistics show that among the top 10 open-source models globally, 8 are from China. The performance of the DeepSeek—V4 model is on par with the world’s top models, while its API pricing is below 1% of that of the GPT—5.5 model. The deeper significance lies in breaking the technological monopoly of a few tech giants, enabling millions of developers worldwide to conduct secondary development based on Chinese open-source models. Open-source not only provides benefits but also harnesses collective strength, as knowledge accelerates its flow and spillover in an open ecosystem, continuously forging self-evolution capabilities for China’s AI technology.

Industry Scale

From the perspective of industry scale, the AI industry has experienced nonlinear explosive growth, with significant value spillover effects behind the trillion-dollar blue ocean. By 2025, the global AI market size is expected to reach $757.58 billion, while China’s core AI industry scale has surpassed 1.2 trillion yuan. The value of this 1.2 trillion yuan lies not just in the number itself but in the growth logic behind it. Traditional industries follow the iron law of linear input and diminishing marginal returns, whereas AI breaks this curse, with technological breakthroughs and application diffusion mutually reinforcing, forming a positive feedback loop of “the more it is used, the stronger it becomes.” Research shows that Beijing, as an innovation source, will achieve a core AI industry scale of 450 billion yuan by 2025. A batch of mature algorithm models acts like a “digital technology pump,” continuously delivering intellectual energy to factories in Hebei, ports in Tianjin, and pastures in Inner Mongolia. Shanghai is building an ecological attraction field through the “Mold and Speed Space” initiative, while Shenzhen aims to create a highly concentrated enterprise ecosystem that precisely serves the real economy. Ultimately, the AI industry exhibits a multiplier effect of “investing one yuan to leverage several yuan,” with a trillion-scale industry chain emerging from underlying computing power to upper-level applications, from core algorithms to intelligent terminals, giving rise to new services, new divisions of labor, and new markets.

Factor Support

From the perspective of factor support, China’s core AI resources have achieved a strategic leap, with institutional innovation accelerating the release of factor vitality. The competition in AI’s later stages depends not only on how fast models run but also on how solid the computing power foundation is and how smoothly data flows. In these two core resources, China has established significant scale advantages. In terms of computing power, 42 intelligent computing clusters have been built, and as of the first quarter of this year, the scale of intelligent computing power reached 188.2 quintillion floating-point operations per second, ranking among the world’s top. Regarding data, there are over 100,000 high-quality datasets nationwide, with a total volume exceeding 890 petabytes, equivalent to 310 times the total digital resources of the National Library of China. Moreover, institutional advantages are gradually emerging. In Beijing’s data foundational system pilot area, a “regulatory sandbox” mechanism has effectively broken the deadlock concerning enterprises’ reluctance to open their resources. This mechanism allows companies to enter a protected “experimental field” for integrated training without transferring data ownership. A technical leader from a company remarked, “Previously, training with our small data led to increasingly biased models; now, the sandbox gathers real data from over 10 industries, significantly improving accuracy, and data becomes more valuable the more it is used.”

Integrated Applications

From the perspective of integrated applications, China’s AI is accelerating its penetration into various industries, with the breadth of applications and depth of integration establishing new global competitive advantages. By the end of 2025, the CNC rate of key processes in major industries in China is expected to reach 68.6%, with AI integration applications transitioning from “spot blooming” to “full-chain intelligence.” First, the penetration fields continue to expand, covering most major categories of the national economy, forming a number of benchmark applications in manufacturing, healthcare, transportation, finance, and energy. Second, the empowerment level has significantly increased, advancing from auxiliary roles to core processes such as R&D design, production, and operational management. In a heavy equipment manufacturing company in Shandong, an industrial large model system comprehensively takes over the entire chain process from blueprint analysis, process planning to quality inspection, compressing the time for new process design from several weeks to under 72 hours, with a 5% increase in yield rate. Third, new business formats and models are emerging rapidly, with intelligent connected vehicles, AI pharmaceuticals, and embodied intelligent robots flourishing, continuously forming new trillion-level industrial tracks. In the research, it is deeply felt that in this global intelligent competition, whoever has the richest application scenarios, the tightest integration, and the most concentrated industry feedback holds the standards and application paradigms defining how AI is used, where it is applied, and how deeply it is integrated, thus gaining the initiative in the intelligent era.