Alert fatigue is one of the biggest challenges facing security personnel — and agentic AI could be just what is needed to overcome it.
Organizations use various devices to monitor environments, spanning access control, video surveillance and fire and intrusion detection. These tools provide powerful standalone features, however, they are based on reactionary processes that require humans to be alerted to every detected anomaly.
This has led to alert fatigue and a general failure to connect tools in a useful way that enables efficient security operations. Security personnel are trapped in a reactive loop, where they:
- Monitor disparate dashboards and alerts
- Attempt to address situations in real time
- Collect evidence afterward to assess an incident
Many mistakenly believe that disparate dashboards are the source of dysfunction, but it is the sheer volume of alerts. Personnel need a way to cut through the noise and use automation to combine insights across solutions to drive informed, timely action. They need to become more proactive than reactive, focusing on the highest-priority issues and letting automation handle the rest.
Thanks to agentic AI, the industry will soon achieve this reality—supercharging the value of every security investment and empowering teams to respond to incidents when they still matter.
Security integrators play a crucial role in guiding clients into this future, helping them start exploring agentic AI capabilities to address alert fatigue and significantly boost efficiency. The technology is still in its early stages, however, it is evolving rapidly and will soon become a security essential for optimal results.
To help you stay ahead, let’s explore what agentic AI is, its benefits to security teams, and how to integrate it into client ecosystems.
Agentic AI Explained
Agentic AI can act autonomously within a software ecosystem to enact a full process designed to achieve a specific outcome or goal. It leverages foundational technologies, including machine learning, large language models, visual language models, and generative AI, to behave like a human agent.
Agentic AI can process massive volumes of data in real time to identify threats and assess the appropriate response to each situation. To do so effectively, agentic systems need access to every security device, system, or sensor to collect data, analyze insights, and orchestrate security measures.
The technology is unique in its ability to constantly learn from its actions and optimize future actions based on details of each unique situation and the expressed goal.
Agentic AI vs. Traditional Computer Vision for Security
Traditional computer vision has been able to detect basic anomalies related to security and life safety. Agentic AI applies contextual awareness and intelligence to make decisions around threat assessment and incident response.
To illustrate the difference between traditional computer vision and agentic AI, consider these examples. In each of these scenarios, agentic AI works across multiple security devices in tandem to identify threats in real-time, activate the functions and features of each device, and ideally stop situations before they require human intervention.
Detecting Bad Actors
A video surveillance or intrusion detection system is installed to identify potential bad actors, such as someone exhibiting suspicious behavior or accessing restricted areas.
Computer vision would only be capable of detecting the presence of a human. It would have no context to determine if that human was a threat. It can only send an alert to a security operator, who must then assess the threat and determine the appropriate action.
Agentic AI would not only detect the presence of a human but would also analyze what that human was doing in context to calculate a threat assessment. Using that threat assessment, the agentic AI could decide if it could handle the situation using its generative AI deterrence or if it needs to involve a human immediately.
PPE Adherence
A video system is used to detect if personnel are properly wearing personal protective equipment (PPE) on a jobsite.
Computer vision would only identify one or two specific anomalies and provide a general alert that a PPE violation had been detected. A human would need to respond to a violation.
Agentic AI would be able to identify a wide variety of PPE concerns, specifying the type of violation and its location. It can use generative AI to issue a customized message in real-time to the individual(s) in violation, instructing them what they need to do to be in compliance.
Life Safety Threats
A video system is used at a hospital to provide security against life safety threats and bad actors who may enter the property.
Computer vision would only be capable of detecting that a human was present and would have no context to determine if that human was a bad actor, an employee, or a patient. It would not know if that human was a threat to themselves or others.
Agentic AI would not only detect the presence of a human but also analyze what they were wearing (street clothes, uniform, or hospital gown) and their actions to calculate a threat assessment. Using that threat assessment, the agentic AI could decide how to handle the situation (is this a patient or employee who needs help, or a bad actor who needs to be deterred?).
Questions to Discuss Agentic AI with Clients
Start engaging your clients in a conversation about agentic AI by asking questions like:
- Where does most of our security team’s time go? Can these tasks be automated or streamlined using AI?
- What types of incidents generate the most alerts? Can automation handle these types of incidents? (Think public nuisance vs an active shooter situation.)
- What effect can intelligent automated deterrence have on the overall workload of security personnel?
- What are the risks associated with using automated deterrence instead of real humans? Are there significant liabilities if automation is used in specific scenarios?
These questions can help you assess where to focus your efforts so agentic AI delivers immediate time and cost savings.
Agentic AI is a Security Force Multiplier
Agentic AI will redefine what teams can accomplish no matter their resources. Soon, companies of all sizes can ensure 24/7 coverage that maximizes the safety of employees, clients or customers, and the general public.
Integrators have not just an opportunity, but a competitive necessity to explore agentic AI use cases and keep up with its advancements. The technology will evolve rapidly and present significant efficiency gains to organizations that learn how to harness its potential.
Steve Lindsey is chief technology officer of LiveView Technologies (LVT).
