The crowd analytics market is expanding as AI, computer vision, and IoT enable real-time crowd safety and behavior analysis, with the U.S. segment growing from USD 1.30 billion in 2025E to USD 6.76 billion by 2033 amid rising smart city and security deployments.
Austin, Jan. 12, 2026 (GLOBE NEWSWIRE) — The Crowd Analytics Market size is valued at USD 4.84 Billion in 2025E and is projected to reach USD 25.90 Billion by 2033, growing at a CAGR of 23.36% during the forecast period (2026-2033).
The growing use of artificial intelligence (AI), computer vision, and Internet of Things (IoT) technologies to provide crowd real-time monitoring and safety solutions is highlighted in the Crowd Analytics Market research. Deep learning-based behavioral and movement analytics will become more popular as a result of growing urbanization and the desire for smarter cities.
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The U.S. crowd analytics market size is valued at USD 1.30 Billion in 2025E and is projected to reach USD 6.76 Billion by 2033, growing at a CAGR of 22.98%.
The growing use of crowd analytics in security and smart city initiatives is propelling the market’s expansion. IoT devices and sophisticated AI-based video analytics are enhancing real-time crowd surveillance in public spaces and transit hubs.
Segmentation Analysis:
By Component
Software led the Crowd Analytics Market with a 46.80% share in 2025 owing to complex AI algorithms, real-time monitoring dashboards and predictive modeling techniques helping in decision making for public places and outlets. The services were the fastest-growing segment with a CAGR of 18.90% as demand for consulting, system integration and analytics-as-a-service models are increasingly sought after to support better interpretation and deployment of data across industries.
By Application
The safety & security dominated with a 34.50% share in 2025 as governments and corporations deploy analytics to control crow flow, deter congestion, and maintain a safe environment. The customer insights & engagement grew fastest at a CAGR of 20.20% relying on retail to evolve their service and layout strategies through behavior analysis in order to provide a superior shopping experience.
By End-User
The transportation led with a 28.60% share in 2025 as it uses data for optimizing passenger movements, securing airports, and traffic management. The smart cities recorded the fastest growth at a CAGR of 22.24% with population growth trends and governments’ investments on future-ready infrastructure programs mainly addressing sustainability elements and public real-time monitoring.
By Analytical Approach
The descriptive analytics held 37.10% share in 2025 as organizations continue to value more highly the interpretation of historical data for strategic and operational purposes. The real-time analytics was the fastest-growing segment at a CAGR of 24.41% due to IOT connected-devices and AI-inspired algorithms that enable instant situational awareness and instantaneous response in urban or commercial settings.
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Regional Insights:
In 2025, North America dominated the Crowd Analytics Market and accounted for 41.25% of revenue share, this leadership is due to the strong AI infrastructure and early adoption of crowd analytics within public safety as well as retail. U.S. tech giants lead the way with cloud-based solutions and integration into IoT.
Asia Pacific is expected to witness the fastest growth in the Crowd Analytics Market over 2026-2033, with a projected CAGR of 23.98% due to rapid adoption of AI based surveillance systems and smart infrastructure projects in urban countries.
Growing Integration of AI and IoT Enhances Real-Time Crowd Monitoring Capabilities Boost Market Growth Worldwide
The need for intelligent crowd analytics is growing as artificial intelligence and Internet of Things (IoT) solutions become more widely used. In smart cities, transit systems, and large gatherings, these capabilities enable real-time situational awareness, predictive tactical planning, and enhanced public safety. These systems are currently being used for emergency response and active crowd management in both the public and private sectors. Around 1.8 million AI-powered crowd monitoring devices were produced globally in 2025, enabling increased deployment across the globe.
Key Players:
- IBM Corporation
- Cisco Systems, Inc.
- NEC Corporation
- Nokia Corporation
- CrowdVision Ltd.
- AGT International
- Wavestore
- Walkbase
- Sightcorp
- Spigit
- Savannah Simulations, Inc.
- AllGoVision Technologies
- ReelyActive
- Crowd Dynamics International
- Hitachi Vantara LLC
- Splunk Inc.
- NEC Technologies
- Crowd Connected
- Smartvue Corporation
- CrowdANALYTIX
Recent Developments:
In August 2025, IBM (US) announced a strategic partnership with a leading telecommunications provider to improve its crowd analytics capabilities. This collaboration aims to integrate real-time data from mobile networks, allowing businesses to gain deeper insights into consumer behavior.
In September 2025, Cisco Systems, Inc. launched its new “Cisco Data Fabric” platform powered by Splunk Inc., targeting large-scale machine-data processing and crowd-analytics use-cases in smart venues and urban infrastructure.
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Exclusive Sections of the Report (The USPs):
- Detection Accuracy & Analytics Performance Metrics – helps you evaluate crowd density detection accuracy, real-time anomaly detection rates, and precision improvements enabled by AI and computer vision integration.
- Infrastructure Penetration & Connectivity Indicators – helps you assess surveillance camera density, IoT and sensor integration levels, and regional adoption of cloud-connected crowd analytics platforms.
- Government & Smart City Adoption Statistics – helps you track the scale of smart city initiatives and government-led projects implementing real-time crowd monitoring and management systems.
- Public Surveillance Deployment Growth Metrics – helps you understand growth rates of analytics-enabled public surveillance systems and their impact on large-scale crowd control strategies.
- Operational Cost Reduction & ROI Insights – helps you quantify cost savings from predictive crowd management, reductions in manual monitoring expenses, and return on investment across public and private deployments.
- AI-Driven Automation Impact Indicators – helps you assess the effectiveness of automated crowd analytics in improving response time, operational efficiency, and safety outcomes.
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