Goldman Sachs estimates 300M jobs could face AI disruption over the next decade, while new roles emerge in data centers and power infrastructure buildout

Goldman Sachs Research estimates that around 300 million full-time jobs globally are “exposed” to AI-driven automation over roughly the next decade, but expects the net impact on unemployment to be modest as new roles are created, especially in AI-related infrastructure such as data centers and power systems. The firm’s economists argue that AI will significantly reshape the task composition of many jobs rather than eliminate them outright, while simultaneously driving productivity gains and new categories of employment. In recent commentary and research updates, Goldman Sachs highlights that AI could automate tasks equivalent to about 25% of work hours in the US, with 6–7% of workers displaced over a ten‑year transition period in its baseline scenario. Even under that disruption, Goldman projects only about a 0.5–0.6 percentage point increase in the unemployment rate during the adjustment period, assuming workers are able to move into new roles over time. Occupations with higher substitution risk include programmers, accountants, legal and administrative assistants, and customer service roles, while professions that rely more on in‑person, complex, or judgment‑heavy work are seen as less exposed. A central point in Goldman’s newer framing is that the AI boom requires substantial physical infrastructure buildout, which itself is labor‑intensive. To support growing AI workloads, the US power system alone is estimated to need roughly 500,000 net new workers by 2030 to meet higher electricity demand. Construction, engineering, and skilled trades jobs tied to data centers and grid expansion have already grown, with Goldman citing strong increases in construction employment related to data centers since 2022. More broadly, the bank links AI to potential long‑run gains in productivity and GDP—earlier Goldman research estimated generative AI could lift global GDP by about 7% over a decade—while stressing that the near‑term labor market impact is likely to be uneven across sectors and generations, with younger tech and knowledge workers seeing earlier disruption.

✨ AI-generated background, compiled from web sources — not editorial content.

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