Key Takeaways
- 55% of US temp workers are aged 25-34 in 2023.
- Women comprise 52% of the temporary workforce in Europe 2022.
- In India, 65% of temp staff have high school education or less 2023.
- The U.S. temporary help employment averaged 2.96 million workers in 2023.
- Globally, 28 million people were employed through temp agencies in 2022.
- In the EU, temporary agency workers numbered 3.8 million in 2022.
- Global temp staffing market expected to grow at 5.2% CAGR from 2024-2030.
- U.S. staffing industry projected to reach $215 billion by 2027.
- Europe temp market growth: 3.8% annually to 2028.
- Temporary staffing accounted for 25% of all new hires in manufacturing in the US in 2023.
- In healthcare, 15% of nursing staff in Europe were temps in 2022.
- IT sector in India relied on temps for 35% of hires in 2023.
- In 2023, the global temporary staffing market size was valued at USD 512.4 billion, projected to reach USD 752.1 billion by 2030 at a CAGR of 5.6%.
- The U.S. temporary staffing industry generated $189.2 billion in revenue in 2023, up 4.2% from 2022.
- Europe's temporary staffing market reached €208 billion in 2022, accounting for 1.5% of GDP across 18 countries.
Temporary staffing is booming globally, with major growth driven by millions of workers across industries and regions.
Demographic Insights
Demographic Insights Interpretation
Employment Numbers
Employment Numbers Interpretation
Growth Rates and Projections
Growth Rates and Projections Interpretation
Industry Penetration
Industry Penetration Interpretation
Market Size and Revenue
Market Size and Revenue 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.
Priya Chandrasekaran. (2026, February 13). Temporary Staffing Statistics. Gitnux. https://gitnux.org/temporary-staffing-statistics
Priya Chandrasekaran. "Temporary Staffing Statistics." Gitnux, 13 Feb 2026, https://gitnux.org/temporary-staffing-statistics.
Priya Chandrasekaran. 2026. "Temporary Staffing Statistics." Gitnux. https://gitnux.org/temporary-staffing-statistics.
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