First-order effects

• The reported increase makes AI inference demand more visible to Chinese cloud operators, model providers and infrastructure planners, showing that workloads are rising sharply rather than remaining limited to early experimentation.
• For the National Data Administration, the metric supplies evidence that its data-sector agenda is being expressed in actual AI-service usage, not only user counts or policy targets.

Second-order effects

• Higher token volumes raise the premium on available compute, power and data-center capacity, reinforcing the rationale for providers such as Tencent to expand infrastructure as China-designed AI chips become more available.
• AI developers and cloud platforms will face stronger incentives to improve model efficiency and monetization, since rapidly growing inference traffic increases operating demand even when individual requests are inexpensive.

Third-order effects

• If consumption continues to compound, AI competition in China is likely to hinge increasingly on dependable domestic infrastructure and supply chains, not solely on model releases or consumer reach.
• The pattern supports a shift toward treating AI capacity as utility-like industrial infrastructure; whether that translates into durable returns will depend on how efficiently new capacity matches real workload demand.