Key Takeaways
- In 2023, 262,682 tech workers were laid off across 1,190 companies globally
- In 2022, 165,151 tech employees faced layoffs from 1,066 companies
- In 2024 (as of October), 168,593 layoffs occurred in 542 tech companies
- Meta laid off 11,000 employees (21% of workforce) in November 2022
- Amazon cut 18,000 jobs in January 2023
- Google announced 12,000 layoffs (6% of staff) in January 2023
- Meta's 2022 layoffs represented 21% workforce cut
- Amazon's 2023 cuts equaled 6.5% of global staff (27,000 total across waves)
- Google reduced 6% of workforce in 2023 layoffs
- Q1 2022 tech layoffs totaled 13,728 from 61 companies
- Q2 2023 saw 77,000 tech layoffs across 268 firms
- Q4 2022 recorded 84,017 layoffs from 287 companies
- 62% of software engineers affected by 2023 layoffs
- Recruiting/HR roles comprised 15% of 2023 tech layoffs
- Fintech sector saw 22,000 layoffs (9% of total 2023)
Global tech layoffs surged to 262,682 workers in 2023, continuing at a similar pace into 2024.
Annual Totals
Annual Totals Interpretation
Company Layoffs
Company Layoffs Interpretation
Percentage Layoffs
Percentage Layoffs Interpretation
Quarterly Data
Quarterly Data Interpretation
Sector Breakdowns
Sector Breakdowns 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.
Priyanka Sharma. (2026, February 24). Tech Layoffs Statistics. Gitnux. https://gitnux.org/tech-layoffs-statistics
Priyanka Sharma. "Tech Layoffs Statistics." Gitnux, 24 Feb 2026, https://gitnux.org/tech-layoffs-statistics.
Priyanka Sharma. 2026. "Tech Layoffs Statistics." Gitnux. https://gitnux.org/tech-layoffs-statistics.
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