Key Takeaways
- US lost 5.7 million jobs overall to offshoring 2000-2018, costing $1.8 trillion in wages
- Offshoring reduced US wages by 2.4% for non-college workers 1990-2020
- Trade with China cost 3.7 million US jobs 2001-2018, $15k annual wage loss per worker
- US software development offshored 500,000 jobs to India by 2022
- 40% of US tech jobs (2.5 million) at risk of offshoring by 2030
- US lost 300,000 IT support jobs to Philippines 2010-2023
- In 2022, the US lost 89,000 manufacturing jobs to offshoring, primarily to Mexico and China
- Between 2001 and 2013, China trade deficits led to 3.2 million US job losses, with 2.4 million in manufacturing
- US manufacturing employment fell from 17.2 million in 2000 to 11.5 million in 2020, largely due to offshoring
- Manufacturing jobs offshored grew 20% yearly 1990s, slowing to 5% post-2010
- China WTO entry 2001 accelerated offshoring by 40%
- NAFTA offshoring peaked 1994-2000 with 1 million jobs lost
- US customer service jobs offshored reached 2.7 million by 2015
- By 2022, 35% of US call center jobs (1.2 million) were offshored to India and Philippines
- Financial services offshored 500,000 back-office jobs to India 2000-2020
Offshoring since 1990s has shed millions of US jobs, cut wages, and widened inequality.
Economic
Economic Interpretation
IT
IT Interpretation
Manufacturing
Manufacturing Interpretation
Policy
Policy Interpretation
Services
Services Interpretation
Trends
Trends Interpretation
How We Rate Confidence
Every statistic is queried across four AI models (ChatGPT, Claude, Gemini, Perplexity). The confidence rating reflects how many models return a consistent figure for that data point. Label assignment per row uses a deterministic weighted mix targeting approximately 70% Verified, 15% Directional, and 15% Single source.
Only one AI model returns this statistic from its training data. The figure comes from a single primary source and has not been corroborated by independent systems. Use with caution; cross-reference before citing.
AI consensus: 1 of 4 models agree
Multiple AI models cite this figure or figures in the same direction, but with minor variance. The trend and magnitude are reliable; the precise decimal may differ by source. Suitable for directional analysis.
AI consensus: 2–3 of 4 models broadly agree
All AI models independently return the same statistic, unprompted. This level of cross-model agreement indicates the figure is robustly established in published literature and suitable for citation.
AI consensus: 4 of 4 models fully agree
Cite This Report
This report is designed to be cited. We maintain stable URLs and versioned verification dates. Copy the format appropriate for your publication below.
Catherine Wu. (2026, February 13). Jobs Sent Overseas Statistics. Gitnux. https://gitnux.org/jobs-sent-overseas-statistics
Catherine Wu. "Jobs Sent Overseas Statistics." Gitnux, 13 Feb 2026, https://gitnux.org/jobs-sent-overseas-statistics.
Catherine Wu. 2026. "Jobs Sent Overseas Statistics." Gitnux. https://gitnux.org/jobs-sent-overseas-statistics.
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