The Impact of AI and Remote Monitoring on Security Industry Risk Exposure

By Crystal Jacobs, Program Lead at Security America 

As artificial intelligence (AI) and remote monitoring technologies continue to become an alternate solution in the security industry, insurers are reevaluating how these innovations alter the risk landscape. While these technologies offer enhanced protection, efficiency, and operational insight, they also introduce new exposures and shift traditional liability models. Understanding and ensuring this evolving risk environment is now a priority for us as underwriters. 

From Human Error to Potential Systemic Failure 

Security has always been largely human-centric: physical security guards, manual monitoring, and reactive procedures dominating the landscape. Liability often stems from negligence, inadequate staffing, or delayed response to incidents. However, AI and remote monitoring may reduce some of these human error-related exposures while simultaneously introducing complex systemic risks. 

For example, an AI-powered surveillance system might fail to identify a threat due to algorithmic limitations or data misinterpretation. In such cases, liability questions become less about individual oversight and more about the design, training, and performance of the technology itself. Insurers must assess not only the operational use of AI but also the robustness of its development and deployment. 

In addition, centralized, cloud-based security operations—while efficient—depend heavily on network integrity and data security. A cyberattack on a remote monitoring provider could result in widespread exposure across multiple insured clients, amplifying the potential severity of a claim. 

Potential Overreliance on Technology Without Proven Loss History 

From an insurance underwriting perspective, one of the key concerns with AI-based remote monitoring systems is the overreliance on relatively new and unproven technology without a robust loss history to support its effectiveness. While these systems promise enhanced threat detection and faster response times, the lack of long-term actuarial data makes it difficult to quantify their actual impact on reducing claim frequency or severity. This uncertainty introduces risk for us, as there’s limited evidence to determine whether AI monitoring consistently leads to better outcomes compared to traditional security measures.  

Another potential underwriting concern with AI-based remote monitoring systems is their inconsistent performance across different environments. While these systems may function effectively in controlled or low-complexity settings, their reliability can diminish in more dynamic or high-risk environments, such as industrial facilities, retail spaces with high foot traffic, or mixed-use properties. Factors like lighting conditions, layout complexity, environmental noise, or network connectivity can all impact the accuracy and responsiveness of AI-driven systems. This variability makes it challenging for us to assess risk uniformly, as the same technology may produce very different results depending on the operational context. While the same can be faced with human-centric models, without solid historical data, it’s hard to say if AI-based models will be better or worse. 

Liability Uncertainty in AI Decision-Making 

AI’s ability to make decisions without direct human oversight complicates liability attribution. If an AI system fails to detect a breach or erroneously triggers a response that causes harm (such as a false alarm leading to unnecessary emergency response), determining who is legally responsible can be challenging.  Sure, contracts can assist in guiding this, but it would stand to reason that shared accountability between system developers, service providers, and end-users exists in a unique way.  This also complicates potential subrogation efforts which could increase claims costs. 

Moreover, the evolving nature of AI technologies introduces uncertainty in how existing legal frameworks apply, particularly when systems learn and adapt over time in ways not explicitly programmed by their creators. This dynamic behavior can blur the line between foreseeable risk and emergent behavior, further complicating the assignment of blame. Regulatory bodies may need to develop guidelines or models of risk assessment that account for the autonomous and sometimes opaque decision-making processes of AI.  

Lack of Industry Standards and Certification 

The lack of industry standards and a clear, universally accepted definition of “artificial intelligence” in the context of security monitoring creates a substantial challenge for us. At present, there is no consistent framework to certify or evaluate AI-based remote monitoring systems, leaving insurers to assess technologies that can vary significantly in capability, quality, and reliability. Compounding this issue is the broad and often vague use of the term “AI”—ranging from basic motion detection with simple rule-based automation to advanced machine learning models capable of real-time behavior analysis.

This ambiguity makes it difficult to determine whether a system truly offers enhanced security or is merely marketed as AI-driven without delivering measurable risk reduction. Without standardized definitions, performance metrics, or compliance certifications, we are left without a reliable basis to compare systems or validate their effectiveness. As AI becomes more integrated into security infrastructure, the need for industry-wide standards and clear definitions will be critical to ensuring consistent risk assessment and responsible implementation.  

While the development and implementation of AI systems hold promising potential for the future of security monitoring—offering increased efficiency, scalability, and automation—there remain significant unknowns that can only be addressed with time and experience. The true impact of these technologies on loss prevention, claim outcomes, and long-term risk exposure is still unfolding, and much depends on how consistently these systems perform in diverse environments and how well they are maintained and integrated. As the technology matures and its capabilities are better understood, we will be better positioned to evaluate its true risk-reducing value.   

But that’s what we, Security America, are here for.  As the leading program for the security alarm and life safety industry, our task is more than just selling you insurance.  Our task is to be right alongside the industry as new technologies, new standards and, thereby, new exposures present themselves.  As the industry evolves, we should too.  We are excited to navigate new technologies with you.  As you change, we adapt to ensure we are meeting your insurance needs.  Call Crystal Jacobs & the team at 866-315-3838 for more information on the Security America Insurance programs.  Be sure to reach out to the ESA Membership Team at membership@esaweb.org for other membership benefits!  Don’t forget – being an ESA member can also save you some SIGNIFICANT dollars on your insurance.  If you are a member, your premium savings typically COMPLETELY COVERS the cost of your membership.