Using AI Gun Detection Technology to Enhance Workplace Safety

The impact of gun violence in the U.S. has set an alarming trend, with roughly 350-400 gun-related workplace homicides occurring annually. The Bureau of Labor Statistics reported 379 firearm-related fatal occupational injuries in 2024 alone. As a result, new technology to prevent these incidents is in high demand, and firearm detection systems are staking their claim as one of the most effective ways to detect perpetrators earlier for faster law enforcement response.

“AI-powered weapon detection technology can be valuable for environments such as schools, hospitals, retail, and public entities where campuses and premises are easily accessible and open to the public,” said Ariel Jenkins, Assistant Vice President – Risk Control at Safety National. “By enabling faster identification of potential threats, these systems can help organizations take action sooner and strengthen their overall approach to workplace safety and security.”

Understanding how AI gun detection systems operate can help organizations evaluate whether this technology may play a role in strengthening their workplace security strategies.

How AI Gun Detection Systems Work

AI gun detection technology uses computer vision and cameras connected to a vendor-operated operations center, enabling them to detect when weapons are brandished on the premises. This requires multiple operating cameras installed at all external points of entry and internally throughout the building. Often, these vendors can use cameras already installed around a building, helping to reduce the need for new hardware installation. Their technology can usually detect a weapon being held out in the open in a matter of seconds.

Optimizing Technology with Human Verification

Some vendors incorporate human analysts to ensure that when a weapon is detected, it is verified, minimizing false alarms. This approach, along with sound human judgment, can help validate dispatching security or law enforcement once the threat of a weapon is detected. Analysts can also quickly pinpoint the location of the weapon.

Risk Tradeoffs to Consider

While false positives can occur, such as when a camera and a human analyst cannot distinguish an object from a weapon, important tradeoffs must be considered. One risk is that law enforcement might use deadly force against a subject who is not actually armed. On the other hand, if the detection sensitivity is set too low, there is a chance that real threats could go undetected.

Additionally, for weapon detection technologies that utilize camera-based computer vision, weapons usually need to be visible or displayed for the AI to recognize them. For instance, a concealed weapon inside a bag or holster could be detected, but law enforcement will not be dispatched in open carry states unless it is brandished in a manner deemed threatening. Often, this technology is reserved for security checkpoints. Despite being relatively new, gun detection systems have made significant strides in reducing the risk of violence and can play a crucial role in an organization’s risk mitigation strategy.

While concerns about privacy and data use warrant careful consideration, it is important to understand that AI gun-detection technology is intended to be a targeted, event-driven safety tool rather than a broad surveillance system. These solutions analyze existing camera feeds to identify weapons that are visibly brandished, without using facial recognition or tracking individuals, and often incorporate human verification to reduce false alarms. Their potential value lies in enabling faster response to credible threats in environments where seconds matter.

At the same time, decisions around adoption often reflect varying levels of risk tolerance, governance expectations, and public perception. Moving forward, a balanced approach grounded in clear policies, transparency, and stakeholder engagement can help organizations evaluate how and whether these tools fit within a broader safety and security strategy.

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