Huawei Technologies projects China’s industrial AI inference market will surpass 700 billion yuan as enterprises boost digital spending by up to 40 percent by 2026, signaling a new phase of quantifiable returns on AI investment.
Huawei Technologies forecasts China’s industrial AI market will generate over 700 billion yuan ($96.6 billion) in infrastructure spending as enterprise AI adoption moves from pilot projects to large-scale deployment, a senior executive said. The tech giant projects corporate spending on digitalization will climb from 2.5 percent of revenue to as high as 3.5 percent by 2026, a 40 percent increase that reflects the growing ability of firms to measure direct returns from AI.
“In 2025, the value of Industry + AI has been market-validated; it is no longer a concept or a pilot,” Guo Zhenxing, Vice President of Huawei’s China Enterprise Business, said at the AI+ Manufacturing Industry Summit in Shanghai on May 15.
The forecast is underpinned by a broader acceleration in AI investment across China. Research firm IDC projects the nation’s total AI spending will exceed $110 billion by 2029. Huawei’s projection isolates the opportunity in inference—the use of trained AI models to generate answers and power applications—which is becoming a primary driver of infrastructure build-outs as companies move beyond the initial training phase.
The shift from AI-as-concept to AI-as-P&L-driver is forcing a capital-intensive arms race among China’s tech giants. Alibaba Group Holding Ltd. recently disclosed an 84 percent drop in its core commerce profit for fiscal 2025, largely due to redirecting cash flow to a $50 billion, three-year AI and cloud infrastructure plan. For investors, Huawei’s forecast sharpens the focus on the companies building the digital backbone—from chipmakers to cloud providers—as the primary beneficiaries of this next investment wave.
From ‘Concept’ to Quantifiable ROI
Guo outlined three major shifts for 2026: rising investment in digitalization, an upgrade of the underlying digital infrastructure, and an increase in the value of AI-driven industry solutions. The core change, he argued, is that businesses can now calculate the financial benefits of AI in areas like manufacturing, finance, and logistics. For a company with 100 billion yuan in revenue, the expected increase in digital spending translates to an investment of up to 3.5 billion yuan.
This trend is not happening in a vacuum. Alibaba’s Cloud Intelligence Group saw revenue grow 38 percent in its last fiscal year, even as the costs of its AI build-out weighed heavily on group profitability. The competitive pressure extends to Baidu, Tencent, and ByteDance, all of which are making multi-billion dollar investments to build proprietary large language models and the data centers to run them. More than 30 percent of large-scale manufacturing enterprises in China have already established dedicated AI-related organizations to manage this transition, according to Guo.
The focus on inference hardware also aligns with global market trends. While Nvidia has dominated the market for AI training chips, share prices for companies whose semiconductors enable inference—like Intel, Samsung, and Taiwan Semiconductor Manufacturing Company—have surged in 2026, as noted in a recent New York Times analysis. The Philadelphia Semiconductor Index (SOX), which tracks global chip companies, has climbed over 70 percent this year.
A Talent Bottleneck Amid Surging Demand
The primary obstacle to this expansion is not capital but talent. Guo highlighted a severe shortage of 复合型人才 (fùhéxíng réncái), or interdisciplinary talent, who understand both AI technology and specific industry processes.
He cited the intelligent driving sector as a stark example, where the number of new job postings exploded 28-fold in 2025. The supply-to-demand ratio for core algorithm positions was just 0.79, representing a net talent shortfall of 44,000 people. This human capital constraint could become the main limiting factor on the growth that Huawei and IDC forecast, putting a premium on companies that can attract and retain these scarce experts.
This article is for informational purposes only and does not constitute investment advice.
