US technology employers announced 18,720 job cuts in March 2026, up 24% on the same month a year earlier, bringing total tech sector layoffs to more than 52,000 in the first quarter alone. Oracle, which disclosed thousands of cuts last week, is the latest in a line that includes Block, Atlassian, and others that have cited AI-driven efficiency as an explicit reason for reducing headcount. Across the Pacific, a different picture is emerging. New reporting from CNBC finds that Chinese technology companies are, for now, largely holding or growing their workforces, even as they invest heavily in AI development.
The contrast is not straightforward, and neither side of it is entirely what it appears. In China, major companies are pursuing different strategies. Alibaba's headcount has dropped more than 30% over the past two years, a reduction the company attributes to business restructuring around AI. Tencent, by contrast, disclosed a modest increase in total employees last year. Huawei's research and development workforce grew slightly, reaching 114,000 as of December. The picture is mixed, but the explicit attribution of mass cuts to AI efficiency, the pattern now common in US earnings announcements, is less visible among Chinese companies.
Several structural factors help explain the gap. Chinese enterprises are, on average, less digitised than their US counterparts. Enterprise software adoption, which is the layer on which many AI productivity tools sit, is thinner in China. The efficiency gains that US companies are extracting by deploying AI on top of existing digital infrastructure are not yet available at the same scale in China because that infrastructure is not yet in place. This is, in effect, a lag: the displacement that US tech workers are experiencing now may arrive in China later, as digitisation advances.
There is also a policy dimension. China maintains an explicit national employment target, with an urban jobless rate goal of around 5.5%. That creates a political context in which companies have incentives not to announce large AI-driven layoffs, and in which the framing of job cuts matters. Whether Chinese companies are genuinely hiring more because of different economic conditions, or whether the same pressures are present but less visible, is a question the available data cannot fully answer.
The pay gap between the two labour markets adds another layer of complexity. Algorithm engineers in China earn an average of around 20,000 yuan per month, roughly $2,900 at current exchange rates. The same role in Silicon Valley commands multiples of that. When AI tools reduce the productivity advantage of expensive human labour, US companies face a stronger immediate incentive to cut than Chinese companies do. The marginal saving from replacing a $300,000 engineer with an AI system is simply larger than the saving from replacing a $35,000 one.
Bloomberg's tracking of US tech sector job cuts shows the trend accelerating. First quarter 2026 cuts are the highest since 2023, and the explicit AI attribution is becoming more common rather than less. The standard counter-argument, that AI creates new roles even as it eliminates others, is harder to find in these numbers than it was a year ago. The new roles that are growing are concentrated in infrastructure: data centre construction, electrical systems, facilities management. They are not the knowledge-work replacements that tech industry optimists have been promising.
The US-China jobs divergence is, in that sense, a preview rather than a settled contrast. The structural forces driving US cuts are not absent from China; they are delayed by digitisation lag and policy context. What is happening in American tech right now is likely a leading indicator of what arrives elsewhere as AI capability spreads and local infrastructure catches up.