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The report is a market-level overview of industrial AI in China, covering adoption rates, a projected market size, and bottlenecks in data, reliability, cost, and talent. Its growth figures come from a media outlet's own estimates, with an IDC survey cited for adoption, so readers should treat the forecasts as directional rather than settled. The most useful point for AI practitioners is the argument that purely data-driven models struggle in process industries, which pushes deployment toward hybrid approaches that combine domain physics with machine learning.
36Kr Research Institute | 2026 China Industrial AI Industry Development Research Report
China's manufacturing sector is now at a critical window for transformation toward high-end, intelligent, and green development. Industrial AI, as a key lever for addressing manufacturing's core demands for quality improvement, cost reduction, efficiency gains, safety, and green development, is seeing market application demand continue to accelerate. According to IDC survey data, the share of Chinese industrial enterprises applying large models and AI agents rose rapidly from 9.6% in 2024 to 47.5% in 2025, a sharp increase in application penetration. This explosive demand growth is directly driving industry expansion. According to 36Kr Research Institute estimates, China's industrial AI market size that can be implemented will reach RMB 116.3 billion in 2026 and is expected to exceed RMB 300 billion by 2030, with a compound annual growth rate of over 25%. At the same time, scarce high-quality data, insufficient model reliability, high upfront investment costs, and a shortage of interdisciplinary talent are intertwined, forming systemic barriers to large-scale industrial AI deployment. Traditional single-point trial-and-error and bolt-on enablement models are no longer adequate for the stringent requirements of industrial settings. Against this backdrop, 36Kr Research Institute has released the 2026 China Industrial AI Industry Development Research Report, which systematically reviews the industry's development trajectory and analyzes the bottlenecks and breakthrough paths for industrial AI deployment, providing practical reference for the full-scale penetration of industrial AI.
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