Traditional video surveillance tends to be reactive. Companies install cameras and hope they won’t need to use them. If a problem happens, security teams review hours of footage to piece together what went wrong. But this approach is struggling to keep up. The reason isn’t fewer cameras — it’s too many. Today’s environments, like campuses, hospitals, retail stores, and city centers, are packed with cameras covering multiple sites. However, human attention is limited, making it impossible to monitor everything in real time.

The Limitations of the Old Surveillance Model

For years, the video wall era created three big issues. First, operators burn out from staring at screens all day. Second, manual triage can’t handle the volume of footage and alerts. Lastly, systems often cry wolf, generating false alarms so frequently that security teams stop paying attention. This combination reduces the effectiveness of traditional surveillance, leaving organizations vulnerable to issues that slip through the cracks.

Edan Sorski, Head of Cloud at Lumana, explains that the future of video security is about moving beyond simple detection. Instead of just recording and reviewing footage after the fact, systems will monitor, verify, and even trigger actions automatically. This shift will allow humans to focus on oversight and handling exceptions, rather than constantly watching screens.

The Need for Smarter Surveillance in Business

Retail is a prime example of why traditional surveillance is no longer enough. Losses from theft hit $112.1 billion in 2022, putting huge pressure on loss prevention teams. Detecting theft isn’t enough anymore. Teams need to verify what’s happening and respond quickly, ideally before losses occur. Waiting hours or days for someone to review footage isn’t effective in stopping theft in progress.

Systems that only record footage for later investigation fall short. More cameras mean more alerts, more false alarms, and more work for security staff trying to make sense of it all. The old model of people staring at video walls simply can’t scale with the volume of data. As a result, the market is shifting towards smarter solutions that can handle this complexity.

The Rise of Agentic AI for Video Security

Market growth reflects this change. The U.S. video surveillance industry is projected to reach $37 billion by 2030. Companies want systems that do more than just detect incidents after they happen. They want platforms that integrate well with existing software, reduce false alarms, and automate responses.

Traditional basic analytics—like motion detection and classification—are no longer enough. These systems often struggle with changing light, weather, or cluttered scenes, leading to false alerts and missed threats. The next generation of AI-powered surveillance aims to overcome these challenges by creating agentic workflows. These systems can monitor continuously, verify suspicious activity, and trigger appropriate responses automatically, freeing humans from constant watch duty.

This new approach is about proactive security. Instead of reacting after a problem occurs, organizations can prevent or mitigate issues in real time. It’s a smarter way to secure assets, improve efficiency, and reduce workload for security teams. As AI-driven systems become more advanced and integrated, the future of video surveillance looks less like watching and more like acting.

Inspired by

• https://justainews.com/applications/face-and-image-recognition/lumana-vision-for-agentic-ai-and-videosurveillance/

Sources

• lumana.ai