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From hype to practical value

Quintin Roberts

Artificial intelligence is drawing more attention across the physical security industry. In the 2026 Genetec State of Physical Security report, based on input from more than 7300 security professionals worldwide, AI ranked alongside access control and video surveillance as a key priority for the year ahead.

That interest is understandable, as security teams are dealing with growing volumes of video, alarms, sensor data, and incident information. They are looking for practical ways to reduce manual work and speed up investigations.

For physical security leaders, the challenge is separating real value from market noise. Interest in AI is growing, but so are questions about how it should be applied. The same research found that 70% of end user respondents are concerned about how AI systems are designed and implemented. That is why the focus needs to be on where AI can deliver meaningful value today, and how to adopt it in a way that is responsible and aligned with operational needs.

A practical way to think about AI

As security operations become more data-rich and complex, the value of AI depends on how well it supports the people using it. In physical security, AI is most useful when it helps teams work more efficiently and make better decisions. On its own, AI is a set of development technologies and techniques used to build systems that can learn from data, recognise patterns, and support decision-making. What matters is how those technologies and techniques are applied in the physical security context to provide real operational benefits.

The practical value of AI is made clear through the lens of intelligent automation. The underlying techniques are AI-based, but when combined with physical security rules, actions, sensor data, and intuitive user experiences, they enable intelligent automation capabilities that are practical for day-to-day operations. These include reducing cognitive load, surfacing relevant information faster, and helping teams make informed decisions with greater confidence.

Some of the clearest benefits are in automating daily security operations. During live monitoring, intelligent automation can help reduce nuisance events and surface alarms that need attention. In investigations, it can help teams search large volumes of video and metadata more efficiently, reducing the time it takes to locate relevant evidence. It can also help connect information across systems and sites, giving operators and investigators more context when they need to understand what happened.

Why connected systems matter

Because the value of AI-based solutions depends heavily on context, a system can only support good decisions if it has access to the right information and can present it in a way that makes sense to the user. When video, access control, sensors, communications, and other data sources work together, operators get a clearer picture of events as they unfold. Investigators can move more quickly from one clue to the next. Teams can work across multiple sites and systems without losing time to disconnected workflows.

Open architecture also matters. Organisations need the flexibility to work with different sensors, devices, and analytics, while maintaining a coherent experience for operators. A connected environment creates a stronger foundation for intelligent automation than a closed system built around isolated data sets.

Responsible AI needs to be built in

For AI to be used, it needs to be trusted. Physical security systems often handle sensitive information, so privacy, transparency, and accountability must be built into the design from the start. Organisations need confidence that this technology is used in ways that respect data governance requirements, minimise bias, and support safe, explainable outcomes.

As AI technology becomes more capable, one point remains constant: these tools should support people, not replace them. Security operators and investigators bring judgment, context, and experience that technology cannot replicate. AI can help physical security systems process more information and intelligent automation can help operators work more efficiently. Using technology can help with suggesting, surfacing, and prioritising, but final decisions still belong with people.

Evaluating AI-based solutions

When evaluating AI-based systems or features, organisations need to ask practical questions. Does the technology solve a real operational problem? Does it fit into existing workflows? Does it reduce noise and respect privacy and governance requirements?

Those are the questions that matter most. In the end, the value of AI in physical security should be measured the same way as any other technology: by whether it helps people respond faster, investigate more effectively, and make better decisions with confidence. Delivering practical value in the field is what matters.

The report is available at tinyurl.com/yc89t2kt.

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