Adding AI and Automation Capabilities to Legacy Systems
These capabilities aren’t futuristic; they can be added to existing security systems, a key value of Soloinsight, a leader in security automation and access control solutions. Ambient AI and Camio are two companies whose customers already have AI capabilities like those described in this article.
James Connor, Ambient’s Head of Corporate Engagements, noted, “The job of a security officer is to ‘observe and report.’ LLMs and LMMs make this job faster and more effective by linking sensor data, including video, in real-time, enabling officers to act quickly rather than retrospectively.”
Carter Maslan, CEO of Camio, emphasized, “For the first time, we can address risks with the equivalent of 1,000 experts fully trained in our policies from day one. The shift from simple classifier analytics to LMMs capable of understanding video, images, and data, as well as security policies and procedures, allows us to tackle risks that previously required a human to prioritize and resolve. These AI capabilities emerged only six months ago, driven by billions in investments outside the physical security industry. With them comes a mandate to harness these rapid AI advances for security and additional business operations capabilities.”
As one Camio customer said, “Every camera has its own post orders!”
Connor often states, “Modern innovations should not just bring forth newer capabilities but also harmonize with existing legacy systems, prioritizing scalability and upholding standards for security and privacy.” President of Soloinsight, Farhan Masood adds, “The essence of modern security lies in their adaptability. Legacy systems reach their potential when integrated with advanced automation and identity management solutions.”
Developing AI-Enabled Security Operations Capabilities
Facility security practitioners can now reassess their needs by evaluating past and potential risks through an AI-enabled perspective. For instance, consider, “If I could post a security officer 24/7 at every key vantage point, what should they monitor, and what data would help inform their actions?” This approach involves evaluating camera coverage and determining which systems contain relevant information.
In serious incidents, like potential workplace violence, AI can assist by identifying individuals with restraining orders who should be barred from entry, enhancing at-risk employee protection. Routine nuisances, such as unauthorized parking in reserved spots, can also be prioritized by risk and frequency. With AI, such scenarios can be automatically evaluated against the relevant policies and procedures, allowing faster, data-informed, appropriate responses.
For example, a VIP visitor arriving late for a high-level executive meeting could be allowed to park in the reserved space for the duration of the meeting, instead of broadcasting the parking violation over the public address system, which would interrupt the meeting and embarrass the VIP as well as the meeting host. This is an example of security using AI to intelligently apply policies and procedures harmoniously to the business, which requires a more comprehensive evaluation of security operations and situation response that has been needed in the earlier security technology era.
Data-Driven Security and Business Operations
As businesses become more data-reliant, AI-enhanced security systems provide data insights beyond security, boosting efficiency across functions like staffing, retail responsiveness, marketing campaign evaluation, and manufacturing area safety compliance monitoring.
By comparing current physical security capabilities with new AI potentials, security can create a risk-prioritized, cost-effective strategy that maximizes existing personnel resources and adds value across business operations.
What once was impossible is now within easy reach with AI.
