Key Takeaways
- U.S. construction industry employed 8.1 million workers as of May 2024.
- Global AEC workforce shortage projected to reach 2.3 million workers by 2030.
- Women represent only 11% of the U.S. construction workforce in 2023.
- The global Architecture, Engineering, and Construction (AEC) market size was valued at USD 9.67 trillion in 2022 and is projected to reach USD 14.42 trillion by 2030, growing at a CAGR of 5.1%.
- U.S. construction spending reached $1.79 trillion in 2023, marking a 7.5% increase from 2022.
- The Asia-Pacific region accounted for 45% of the global construction market share in 2023.
- Construction fatalities in U.S. dropped 5.8% to 1,056 in 2022.
- Global construction productivity grew only 1% annually vs. 2.8% in total economy 2010-2023.
- 91% of large U.S. projects completed on time with lean methods in 2023.
- LEED certified buildings number exceeded 100,000 globally in 2023.
- Construction industry responsible for 39% of global carbon emissions in 2023.
- 25% of new U.S. buildings achieved net-zero energy by 2023 standards.
- 75% of BIM adoption in U.S. AEC firms in 2023.
- 42% of global construction projects use AI and automation tools as of 2024.
- Cloud-based construction management software market grew 18% to $12 billion in 2023.
U.S. labor shortages and aging workforces are driving AEC toward productivity tools, with market growth accelerating worldwide.
Employment & Labor
Employment & Labor Interpretation
Market Size & Growth
Market Size & Growth Interpretation
Safety & Productivity
Safety & Productivity Interpretation
Sustainability
Sustainability Interpretation
Technology Adoption
Technology Adoption 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.
Henrik Dahl. (2026, February 27). Aec Industry Statistics. Gitnux. https://gitnux.org/aec-industry-statistics
Henrik Dahl. "Aec Industry Statistics." Gitnux, 27 Feb 2026, https://gitnux.org/aec-industry-statistics.
Henrik Dahl. 2026. "Aec Industry Statistics." Gitnux. https://gitnux.org/aec-industry-statistics.
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