China analysis frames 2026 as breakout year for scaled AI adoption

This Chinese‑language analysis captures a sentiment that is quickly becoming consensus in boardrooms: the experimental phase of generative AI is ending, and 2026 is when scaled deployment really begins. By framing 2026 as the "year of AI at scale" across tech, media and telecom, it underlines that the bottleneck is shifting from core model capability to infrastructure build‑out, distribution channels and product integration—from cloud GPUs to AI‑augmented consumer devices. That perspective is particularly important coming from Greater China, where firms like Baidu, Alibaba, Tencent and Moonshot AI are racing to catch and surpass Western models while threading a complex regulatory environment.([naipnews.naipo.com](https://naipnews.naipo.com/zh-hans/37592/?utm_source=openai))

For the AGI race, scaled deployment feeds back into model development in two ways. First, it provides massive real‑world usage data that can be mined (where lawful) to improve alignment, robustness and reasoning. Second, it sharpens commercial incentives: platforms that succeed in embedding AI into everyday experiences—from short‑video feeds to smart glasses and service robots—will have more cash flow to fund next‑generation training runs. The piece also hints at a brewing edge‑AI contest, with Chinese and Taiwanese hardware ecosystems looking to push more intelligence into devices. If that plays out, we’ll see a diversification away from a handful of hyperscale training centers toward a more complex landscape of edge‑aware architectures.