Key Takeaways
- Retail surveillance ROI expected at 7:1 by 2030 studies.
- Surveillance industry employed 1.2 million people globally in 2023.
- U.S. surveillance market contributed USD 120 billion to GDP in 2023.
- U.S. commercial sector accounted for 42% of video surveillance installations in 2023.
- Retail industry represented 28% of global surveillance camera demand in 2023.
- Transportation & logistics end-use segment grew 19% in camera deployments in 2023.
- The global surveillance market is projected to grow from USD 68 billion in 2024 to USD 145 billion by 2030 at 13.4% CAGR.
- IP cameras expected to hold 52% revenue share by 2030 due to AI integration.
- Asia Pacific forecasted to grow at 17.2% CAGR, largest region by 2030.
- In the U.S., 85 million surveillance cameras were installed by end of 2023, averaging 250 cameras per 1,000 people.
- China had over 626 million surveillance cameras in operation in 2023, the highest globally.
- The average number of cameras per retail store in the U.S. increased to 45 in 2023 from 32 in 2019.
- The global video surveillance market size was valued at USD 62.75 billion in 2023 and is projected to reach USD 164.38 billion by 2030, growing at a CAGR of 15.2% from 2024 to 2030.
- In 2023, the IP camera segment dominated the video surveillance market with a revenue share of over 45%, driven by advancements in network infrastructure.
- The video surveillance storage market was valued at USD 11.2 billion in 2022 and is expected to grow to USD 25.6 billion by 2027 at a CAGR of 17.9%.
Surveillance cameras drive major economic impact, with retail theft savings and a 7 to 1 ROI expected by 2030.
Economic Impact
Economic Impact Interpretation
End-User Statistics
End-User Statistics Interpretation
Forecasts
Forecasts Interpretation
Installation Statistics
Installation Statistics Interpretation
Market Growth
Market Growth Interpretation
Technology Trends
Technology 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.
Isabelle Moreau. (2026, February 13). Surveillance Cameras Security Industry Statistics. Gitnux. https://gitnux.org/surveillance-cameras-security-industry-statistics
Isabelle Moreau. "Surveillance Cameras Security Industry Statistics." Gitnux, 13 Feb 2026, https://gitnux.org/surveillance-cameras-security-industry-statistics.
Isabelle Moreau. 2026. "Surveillance Cameras Security Industry Statistics." Gitnux. https://gitnux.org/surveillance-cameras-security-industry-statistics.
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