China's Core AI Industry Surpasses ¥1.2 Trillion, Two Sessions Set AI+ Strategy

China's Core AI Industry Surpasses ¥1.2 Trillion, Two Sessions Set AI+ Strategy

Overview

China's core AI industry has exceeded ¥1.2 trillion (~$174 billion) with over 6,200 AI enterprises. During the "Two Sessions" political meetings, the government laid out a clear AI-centric economic development strategy.

Policy Signals

The government set a 4.5-5% GDP growth target for 2026 and announced ¥200 billion in ultra-long-term special bonds dedicated to AI infrastructure and equipment upgrades. The 15th Five-Year Plan (2026-2030) prioritizes breakthroughs in AI algorithms, advanced chips, and humanoid robots.

Industry Landscape

The ¥1.2 trillion market positions China firmly as the world's second-largest AI market. Over 6,200 AI companies span the full chain from foundational research to commercial deployment. In the large model space, companies like DeepSeek have demonstrated competitiveness with Silicon Valley giants.

Strategic Transformation

This marks an acceleration of China's shift from "AI follower" to "AI self-innovator." The ¥200 billion bond allocation signals that the government treats AI as a national strategic priority alongside clean energy and semiconductors. In the context of US-China tech competition, this positioning carries profound geopolitical implications.

In-Depth Analysis and Industry Outlook

From a broader perspective, this development reflects the accelerating trend of AI technology transitioning from laboratories to industrial applications. Industry analysts widely agree that 2026 will be a pivotal year for AI commercialization. On the technical front, large model inference efficiency continues to improve while deployment costs decline, enabling more SMEs to access advanced AI capabilities. On the market front, enterprise expectations for AI investment returns are shifting from long-term strategic value to short-term quantifiable gains.

However, the rapid proliferation of AI also brings new challenges: increasing complexity of data privacy protection, growing demands for AI decision transparency, and difficulties in cross-border AI governance coordination. Regulatory authorities across multiple countries are closely monitoring these developments, attempting to balance innovation promotion with risk prevention. For investors, identifying AI companies with truly sustainable competitive advantages has become increasingly critical as the market transitions from hype to value validation.

From a supply chain perspective, the upstream infrastructure layer is experiencing consolidation and restructuring, with leading companies expanding competitive barriers through vertical integration. The midstream platform layer sees a flourishing open-source ecosystem that lowers barriers to AI application development. The downstream application layer shows accelerating AI penetration across traditional industries including finance, healthcare, education, and manufacturing.