AI-Powered Agents vs. Traditional Automation: A Comparative Analysis for Security Applications

It seems ironic: Security systems are built on routine, mundane tasks repeated over and over, but the threats themselves are anything but predictable.

While the security threats fall into standard categories (such as assault or shoplifting), no two incidents are exactly alike. Each person—made unique by their personality, background, and goals—involved in a situation can affect the outcome—with potentially deadly consequences. 

Much like security itself, automated security solutions range from rigidly routine to intensely dynamic. Read on to learn more about the capabilities and limitations of traditional automation solutions compared to AI-powered agents.

Traditional Automation and AI-Powered Agents: A Basic Overview

Door-triggered alarms, motion-activated video recording, sensor-based sirens—automation has been around for quite some time in physical security. Traditional automation works in a straightforward “if, then” sequence: If this security badge registers at this access control point, then the door will open. If the camera detects motion in this specific area, then the alarm will sound. Traditional automation is static and well suited for repetitive tasks without deviation.

AI-powered agents achieve their goals by using complex reasoning to understand situations and decide on the best course of action. AI-powered agents use a combination of natural language processing and machine learning to allow direct interaction with and growth from real-world situations. 

There are several levels of AI-integrated tools available, and not all of them are created equally. Some are more reactive, directly responding to requests by security personnel; others, such as agentic AI, are proactive, actually able to set actions into motion before situations escalate. Agentic AI is well suited for complex tasks as it has the ability to adapt as needed.

It can help to think of traditional automation and AI-powered agents in terms of this common analogy: Traditional automation is like a train on tracks, while AI-powered agents are cars on the road. Both can get you to destinations, but one has flexibility and the other does not. To make changes to traditional automation, you essentially have to build an entirely new train track. AI-powered tools, on the other hand, can adapt easily to obstacles in the road and take alternate routes without pause.

Trains have certainly been around longer, but, thanks to their versatility, cars are the predominant mode of transportation today. Both have their uses, but it’s important to determine where each is most effective to achieve optimal performance in every area.

Flexibility and Adaptation

Traditional automation can take some time to get up and running unless it is already a programmed part of an established system. Those implementing the automation have to consider every piece of the automation from beginning to end and any deviations that need to be accounted for. 

If the traditional automation system encounters something unaccounted for, it may stall, freeze, or fail to react at all. In other words, it has no room for flexibility or adaptation. As industries change and evolve, pieces of the traditional automation system may need to be completely reconfigured to keep up.

AI agents are more complex to set up initially (though they can also come as part of an established system, allowing you to skip the massive undertaking of programming your own agentic AI), but they continuously learn and grow with time. The cycle of analyzing data, learning from new information, and adapting actions accordingly allows AI agents to improve with every interaction.

As industries evolve, AI naturally evolves right along with it, making it perfectly tailored to fast-paced environments and dynamic situations. 

Human Involvement

Traditional automation has served the security industry well as a tool. Depending on how it is set up, the automated tool can alert human personal when there’s movement or when sensors have been triggered, but it can’t contextualize the information to create custom reports or enhance situational awareness. 

AI agents act more like low level employees (albeit, employees with superhuman data processing skills and attention spans) than just another tool. Agentic AI can take the first steps toward mitigating or containing situations, such as with targeted spotlights, locked doors, or customized audio messages, but it may need to still pass the baton to its human counterparts. Unlike the generic alerts triggered by traditional automation, AI-powered alerts could provide custom reports, giving human personnel increased situational awareness and better decision-making capabilities.

Even though it is able to filter through alerts and complete many tasks autonomously, AI agents (much like an employee) still require human supervisors to check in regularly to ensure it stays on the right track.

False Alarms

Traditional automation’s lack of discernment and ability to contextualize means it could flag an unexpected late-night employee with the same level of urgency as an armed intruder. False alarms are common with traditional automation, leading to potentially dangerous alert fatigue (where employees don’t check alerts urgently as they believe it is likely another false alarm).

AI agents excel at pattern recognition and contextualization, meaning it can significantly cut down on false alarms. This not only frees up security personnel to focus on more important issues than verifying every false alarm, but also reduces the likelihood of alert fatigue overall.

Immediate Reactions

Traditional automation can trigger lights, sirens, and even standardized loudspeaker messages instantly. Unfortunately, the lack of customization can be a tip-off that there will be a delay in actual personnel response. Traditional automation can also immediately send alerts to security personnel, but it can take some time for a human to actually verify what is going on and determine the best course of action from there. 

Paired with the right tools, Agentic AI can increase response times exponentially. Targeted spotlights and customized audio messages make it appear as though humans are actively watching every move wrongdoers make. In addition, filtered alerts and customized reports make response times from actual humans faster and more effective.

Evidence Collection

Traditional automation can trigger surveillance camera recording and can flag and store footage with potentially suspicious activity. These are useful features, but the capabilities don’t go much past that for evidence collection. It falls on human security personnel to organize, compile, and find relevant digital evidence after a crime—a process that takes valuable working hours and slows investigations. 

AI-powered agents, on the other hand, fast-track evidence collection by aggregating and flagging relevant evidence, making the investigative process significantly faster and easier. AI-powered search features can also make pulling up all related footage as easy as typing a keyword in a search bar. 

This speed isn’t just convenient; streamlining the investigative process could have major impacts on catching criminals and recovering stolen goods.

Incorporating AI into Your Security Setup

Agentic AI and other AI-based tools are the future of effective security—a future that’s fast approaching.

LiveView Technologies® is enhancing its mobile security units by offering AI-powered tools to help you protect your business in the most efficient, effective way possible. For more information, contact LVT for a demonstration today.