Increasingly, AI agents have become a common and much-talked-about topic. Applications are seen in various industries, including security. This article discusses how AI agents can be applied in physical security and what some use cases are.
Increasingly, AI agents have become a common and much-talked-about topic. Applications are seen in various industries, including security. This article discusses how AI agents can be applied in physical security and what some use cases are.
AI agents have become a familiar term in physical security. AI agents are software components that do more than just event detection and object classification. They ingest data from various sensors such as cameras and access control devices, analyze the situation and recommend action plans.
AI agents vs. traditional AI
Compared to traditional AI, which is mostly rule-based, AI agents are more autonomous, context-aware and goal-driven.
“Traditional AI in security is typically narrow and reactive: a model detects motion, recognizes a person, or flags an object based on predefined rules. An AI agent, by contrast, operates at a higher cognitive layer,” said Koen de Jong, Founder and CEO of Visionplatform AI. “An AI agent can observe events, reason over multiple inputs, consult context from other systems, and decide what action to take next. It does not just answer the question ‘what happened?’ but also ‘does this matter?’ and ‘what should be done now?’”
For end users, this means fewer false alarms, faster decision-making, and less cognitive load on operators, de Jong said. “Instead of security teams constantly monitoring screens or reviewing alarms, AI agents act as digital colleagues that pre-analyze situations and support or automate responses according to policy,” he notes.
Xavier Miota, VP of Sales at Incoresoft, echoes those remarks. “Traditional AI basically comes from computer vision. In the past, we used to take computer vision or cameras, and we would look for a specific situation or a specific character or face or license plate, and we would record it. And then from there, we had to create a business logic to make sure that this information was useful,” he said. “AI agents go a little bit step further in that it actually takes the output to perform a task and to reach a goal.”
Various use cases
One of the biggest advantages of AI agents is that they shift security from a “watch and react” paradigm to an “understand, predict, and act” one. Use cases are wide and varied.
“Common use cases include assisted monitoring, where AI agents summarize ongoing activity and highlight only relevant anomalies. In incident response, agents can validate alarms, gather supporting evidence, and propose next actions such as escalation, reporting, or closure,” de Jong said. “Predictive and preventive scenarios are also emerging, such as identifying patterns that precede safety incidents or security breaches and prompting preventive action. The key shift is from event-driven security to intent- and context-driven security.”
Miota cites use cases in retail where operators can benefit hugely from AI agents.
“Let's say I have a store. Somebody steals something at my store last Friday. And then I have to go back to that video. And I have to look at hours and hours of recording. It's extremely time-consuming. With AI agents, I'm looking for a particular type of behavior, which will allow me to detect whether a person is thinking of stealing or not,” he said.
For example, if someone spends more than 10 minutes in a specific area, they're looking to do something bad. “A person who comes to buy spends less than 10 minutes. A person who comes to steal spends more than 15. So we can get early alarms on these type of behaviors. This may not be 100 percent right, but it can alert our personnel to verify and to validate that this person is actually buying or he's here to make trouble,” Miota said.
When applied to access control, AI agents can detect tailgating, credential misuse and other violations; cross-check face, badge, location and schedule; and adjust access levels dynamically. The end result is stronger security and reduced insider risk.
“Let’s say you and I work in the same office. You want to take your kid to school and you don't want the boss to know. So you're going to give me your RFID card. And when I go through, you are going to pass it through me, and it's going to say that you arrived at 8:30 when you actually arrived at 8:50. There's a lot of ways that you can cheat the system. With AI agents, you can do multiple tasks like facial recognition, like intrusion alerts, like detecting that a vehicle by its license plate entered the property at this right time, that the person entered not only the building but also his office at the right time by being able to match all the features in his face using facial recognition,” Miota said. “It’s very difficult to beat AI.”
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