AI In Video Surveillance Market Size - By Component (Hardware, Software, Services), Deployment (Cloud-based, On Premise), End Users (Commercial, Residential, Infrastructure, Defense and Military, Public Facility, Industrial), Use Cases & Forecast, 2024 -

AI In Video Surveillance Market Size - By Component (Hardware, Software, Services), Deployment (Cloud-based, On Premise), End Users (Commercial, Residential, Infrastructure, Defense and Military, Public Facility, Industrial), Use Cases & Forecast, 2024 - 2032

AI In Video Surveillance Market size is expected to expand at over 15.5% CAGR from 2024 to 2032, propelled by technological advancements and the increasing security concerns. Video surveillance systems offer unparalleled capabilities in threat detection, identification, and response for enhancing security measures across various sectors. The integration of AI algorithms enables real-time analysis of video streams, further allowing proactive threat mitigation and faster incident response times.

AI algorithms also render the automation of routine surveillance tasks, such as object recognition, behavior analysis, and anomaly detection for reducing the workload on human operators and enhancing operational efficiency. Additionally, the integration of AI with other emerging technologies like IoT and cloud computing offers improved capabilities of video surveillance systems, facilitating seamless data management, remote monitoring, and predictive analytics. For instance, in March 2024, Iveda®, the global solution for cloud-based AI, launched IvedaAI Cloud Subscription, its new service that efficiently makes cutting-edge AI video services accessible for use cases from users to professional level.

The AI In video surveillance industry is classified on the basis of component, deployment, use cases, end-user and region.

Based on component, the market value from the hardware segment is slated to witness significant growth during 2024-2032, favored by the advancements in hardware technologies, including high-performance processors, specialized chips, and edge computing devices. Real-time analysis of high-resolution video feeds helps improve the accuracy and speed of threat detection and recognition. Additionally, the growing demand for edge-based AI solutions, driven by the need for decentralized processing and reduced latency is pushing the adoption of AI-enabled hardware devices in video surveillance applications.

In terms of deployment, the AI In video surveillance market from the on premise segment is poised to depict over 14% CAGR during the forecast period. This is due to their ability to offer enhanced control and security over sensitive video data for addressing concerns regarding data privacy and compliance with regulatory requirements. Organizations, particularly in sectors, such as government, finance, and healthcare, prefer on-premise deployment to maintain data sovereignty and mitigate risks associated with cloud-based solutions. This deployment also provides faster response times by processing video data locally for enabling real-time threat detection and immediate action.

Europe AI In video surveillance industry size is anticipated to grow at a significant pace at over 14% CAGR from 2024-2032, attributed to the increasing adoption of smart city initiatives across several countries. The rollout of stringent regulatory frameworks is promoting the deployment of intelligent video analytics for public safety and security. Furthermore, the proliferation of IoT devices and the need for comprehensive security measures in critical infrastructure sectors, such as transportation, healthcare, and retail are fueling the regional industry growth.