Employers competing for the same thin pool of 518,000 qualified candidates against 1.6 million open positions are solving a scarcity problem. China is solving a national capability infrastructure problem. Those are different equations with different timelines.
China's pipeline is growing while the external market shrinks
- Stanford AI Index 2026: China's top AI model trails the US by 2.7% on performance benchmarks — achieved spending 23 times less. China produced 47% of the world's top-tier AI researchers in 2022 vs the US at 18%. AI talent migration from China to the US dropped 89% since 2017. The external market employers are competing in is shrinking while China's internal pipeline is growing.
- Gartner estimates the global AI skills shortage is already costing $5.5 trillion in lost productivity. BCG research: organisations that close their AI talent gap achieve 2.3x faster AI adoption and 67% higher AI ROI than those that do not.
Treat AI capability as a capital allocation, not a hiring queue
The question for your board is not whether you are tracking the AI talent market — it is whether you are tracking it as a hiring challenge or as a capital allocation decision. Those are not the same problem. D1 (Digital Economy) has always rewarded organisations that treat capability as capital. The organisations that close the AI capability gap fastest will be those that apply the same investment logic to their AI workforce (D5) as they apply to their technology build — a multi-year commitment with a defined capability architecture, not a hiring queue waiting to clear.
