Investors and policymakers are recalibrating expectations about China's role in the global AI race as Beijing pursues an "AI+" industrial strategy and market participants look beyond Nvidia for growth. Bernstein analysts, in a recent note, argued that "the latest news flow around China banning purchases of Nvidia chips is unhelpful on the margin for AI development progress, at least domestically," and their first-ever Asia thematic focus list recommended only a handful of mainland companies—largely in what they labelled "AI & Tech Diffusion."

The strategic backdrop is plain. In late August, Chinese regulators released details of an "AI+" plan to accelerate deployment of artificial intelligence across manufacturing, healthcare, logistics and public services. At the same time, Western export controls and commercial constraints have curtailed unfettered access to the most advanced Nvidia GPUs, nudging domestic developers to pursue efficiency gains and bespoke hardware. "China is developing cutting edge AI capabilities with significantly less hardware, redefining expectations of computing power requirements," Morgan Stanley wrote, noting its stock screen prioritized valuation, earnings momentum and thematic exposure.

That combination—policy push plus hardware constraints—has concrete market implications. Cloud operators and software firms skilled at model optimization stand to capture a disproportionate share of value if Chinese firms can deliver comparable outcomes with fewer or different chips. Companies with strengths in large language models and AI services, such as Baidu's AI Cloud and Alibaba's cloud arm, are being watched by analysts for potential upside tied to enterprise adoption and government procurement. On the silicon side, domestic chip designers including Cambricon and Horizon Robotics have gained attention for developing processors optimized for inference and edge use-cases that require lower power and lower-cost deployments than datacenter GPUs.

Equity analysts emphasize that investors must distinguish between technical capability and commercial traction. Bernstein's cautious roster reflects concerns over profitability, intellectual property constraints and the time needed for local ecosystems to scale. Morgan Stanley's screening approach, which balances thematic exposure with traditional metrics like price-to-earnings and earnings revisions, underscores the need to marry hype with hard financials in a market still digesting policy shifts and regulatory risk.

Financial flows already signal the transition. Venture and private-equity capital in Chinese AI startups has increasingly favored software, model-development tools and application-layer products that promise faster monetization than cutting-edge chip fabrication. Public-market volatility has been pronounced: domestic chip-equipment suppliers and edge-AI names have experienced sharp intraday swings on any news about U.S.-China technology tensions.

Looking ahead, China’s focus on algorithmic efficiency, model compression and industry-specific applications could reshape global demand for high-end GPUs while creating new pockets of profit domestically. For investors, the key trade-offs are clear: shorter-term risks from regulatory uncertainty and supply-chain bottlenecks versus longer-term opportunities as the country leverages policy, capital and a huge data base to diffuse AI across its economy. As Bernstein and Morgan Stanley suggest, the winners may not be near-perfect substitutes for Nvidia, but a different constellation of cloud, software and specialized silicon that fits China's distinct policy and market environment.