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AI: Jobs, Power & Money
1JUN

Nvidia adds 6,000 staff as rivals cut

3 min read
09:18UTC

Nvidia reported $81.6 billion in quarterly revenue on 20 May, up 85% year on year, and grew headcount 17% to 42,000 while its chip customers held flat or cut.

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EconomicDeveloping
Key takeaway

Nvidia alone grew revenue and headcount together; every firm building on its chips held flat or cut.

Nvidia reported $81.6 billion in quarterly revenue on 20 May, up 85% year on year, with data-centre sales up 92% 1. Headcount rose by 6,000 to 42,000, a 17% increase, and roughly 74% of those staff work in research and development. Chief executive Jensen Huang called it 'the largest infrastructure expansion in human history'.

Nvidia is the only major entity across the late-May beat growing revenue and staff together. The downstream firms building on its chips, Salesforce, Workday, Cloudflare and CrowdStrike, are flat or cutting. The labour value of the AI build-out flows up the stack to chip-design engineers, not out to the workforce adopting the tools.

Meta alone plans $125-145 billion in 2026 capital spending , most of it routed through suppliers like Nvidia. That is where the hiring lands. A reader watching headcount across the AI economy sees the same shape repeat: capital pours into infrastructure, the supplier that designs the silicon expands, and every firm one rung down counts the savings rather than the hires.

Deep Analysis

In plain English

Most big technology companies have been cutting jobs in 2026 as they adopt AI tools. The chipmaker Nvidia is the exception: it added 6,000 staff to reach 42,000, while its revenue grew 85% to $81.6 billion in a single quarter. Nvidia makes the specialised computer chips that power almost all AI systems. Companies building AI need to buy Nvidia chips, so as AI investment grows, Nvidia grows too. Almost three-quarters of Nvidia's staff work in research and development. The pattern is striking: the company that makes the tools disrupting other companies' workforces is the only one growing its own. However, analysts note this reflects a construction phase. Once companies finish building their AI systems, orders for Nvidia chips may plateau, and the hiring surge may not last.

Deep Analysis
Root Causes

Nvidia's unique position stems from three compounding factors. First, its CUDA software ecosystem, developed from 2006, created a switching cost that takes 18 to 36 months to overcome, locking AI training workloads to Nvidia hardware despite AMD and Intel entries. Second, H100 and B200 chip production is constrained by TSMC's CoWoS advanced packaging capacity, which limits supply and keeps margins above 70%, funding the headcount growth Jensen Huang describes.

Third, the 74% R&D share reflects Nvidia's transition from a graphics card company to a full-stack AI compute platform company: software, networking, and systems design all require engineers, not factory workers, producing a high headcount-per-revenue ratio distinct from traditional hardware firms.

What could happen next?
  • Consequence

    Nvidia's 74% R&D headcount share, sustained by near-monopoly GPU margins, concentrates AI-era employment gains in a narrow technical elite of roughly 31,000 chip and systems engineers globally.

  • Risk

    Custom silicon from Google, Amazon, and Microsoft represents a structural threat to Nvidia's revenue per employee ratio. If CUDA lock-in erodes, Nvidia's justification for its current headcount disappears quickly.

Sources:CNBC
Mentions:Nvidia →Meta →TSMC →Accenture →Cloudflare →Salesforce →Workday →CrowdStrike →Cisco →
First Reported In

Update #11 · Markets now reward the cut, punish the freeze

CNBC· 1 Jun 2026
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