How AI is shaping home security – and what you need to know

The latest security technology promises earlier warnings and faster responses, but which features add real protection and which may not be worth paying for?

AI is shifting home surveillance from recording crimes after they happen to detecting suspicious behaviour early enough to help prevent or interrupt them.

Traditional CCTV has often been forensic – providing evidence after an incident has happened. “Criminals know this, which is why cameras alone do not stop break-ins,” says Ian Jansen van Rensburg, the founder of GhostHome. “AI changes the camera from a recorder into a sentry.”

Instead of reviewing footage the next morning, AI analytics detect a person entering a property, loitering at a gate or crossing a boundary line the moment it happens, pushing an immediate alert to a control room or armed response.

“That shifts the intervention point from ‘after the crime’ to ‘during the reconnaissance’,” explains Jansen van Rensburg. “Prevention comes from response time, and AI is what makes real-time response affordable.”

He says the impact of this shift is already evident in real-world data. According to Jansen van Rensburg, internal incident data from GhostHome’s monitored areas show year-on-year crime declines of between 35% and 80%, depending on the level of coverage.

However, these operational successes do not automatically translate into lower home insurance premiums. Marius Kemp, the head of personal underwriting at Santam, notes that AI technology is currently viewed as a valuable risk management tool rather than a guaranteed premium reducer. “Smart alarms, AI-powered cameras and leak detection systems can help prevent losses or limit damage by providing early warning of theft or intrusions,” he explains.

Kyriacos Floudiotis, the growth manager at FNB short-term insurance, agrees that while smart security systems manage risk, any impact on premiums depends heavily on the individual insurer and property profile. Beyond deterrence, he notes that AI technology also provides valuable digital evidence when claims are submitted.

Managing value, claims and maintenance

Before investing in new security tech, homeowners should ensure any upgrades are disclosed to their insurer, advises Kemp. He explains that these devices can significantly increase both the value of household contents and the cost of replacing fixtures, meaning sums insured must be updated accordingly.

According to Floudiotis, using AI in home security offers several key advantages:

  • Earlier detection of break-ins and suspicious activity
  • Faster incident reporting and response times
  • Verifiable video and digital records to support insurance claims

However, he warns that even the most advanced security systems must be properly installed, regularly tested and correctly maintained to remain effective.

Jansen van Rensburg warns that criminals are also targeting the infrastructure itself – cutting power and connections – so serious systems now build in backup connectivity and power so the cameras stay up when the power is out.

Not all smart security features are worth the cost

But which expensive extras are worth their cost, and which add little value?

Jansen van Rensburg says people should prioritise, in this order:

  • Real AI that can identify people and vehicles (not basic ‘motion detection’ that sends alerts when a cat walks past or headlights shine on the camera)
  • A direct connection to an armed response service, because an alert is useless if nobody responds
  • Using providers who know how to properly place cameras to cover entry routes and the property boundary, not only the front door
  • Backup power and internet, because criminals often take advantage during power outages when cheaper systems stop working.

He says homeowners should not assume that buying 4K cameras (which offer sharper images) for every corner of the property is the best investment. “A well-positioned full-HD camera with good AI features can be more useful than a poorly placed 4K camera,” he says.

Jansen van Rensburg also advises against costly cloud subscriptions for every camera, as some of these services may offer limited additional value compared with systems that process footage locally.

“The camera itself is the cheapest part of a security system. The real value comes from what happens after the camera detects a threat.”

Why human oversight still matters

The security industry has relied on AI for years, according to Steven Voortman of Verifier. While modern discussions often focus on generative tools, he says AI monitoring systems primarily serve to filter high volumes of camera alerts that human operators staring at screens could never realistically manage alone.

“We use black-screen monitoring. We don’t watch your camera feed at all until an alarm, a panic signal or an alert from an AI-integrated camera system gives us a reason to. Your privacy stays intact, and our attention lands exactly where it is needed,” says Voortman.

He explains that what AI really gives you is likelihood. “Through heat maps, virtual boundaries, video analytics, and licence-plate recognition, it alerts to the events most likely to matter. But critically, every alert still passes through human verification before escalation. The technology narrows the field; a person makes the call.”

Prioritise basics before high-tech upgrades

When allocating a security budget, experts warn against a one-size-fits-all approach. Physical barriers must always come first. If a home lacks sturdy doors, burglar bars or proper fencing, high-tech additions should wait.

According to Voortman, security tech works best when it addresses your home’s weak points. A home bordering a dense greenbelt may require perimeter thermal monitoring, while another property might simply need a gate camera or routine maintenance on existing, dusty hardware.

What’s next for AI security?

Looking ahead, Jansen van Rensburg expects estate-grade AI monitoring to become far more accessible for standard suburban properties as costs fall. The technology is also moving toward pattern-of-life learning – allowing systems to understand normal household routines and flag unusual events, like a gate opening at an unusual hour or an unfamiliar vehicle idling outside, before an actual perimeter breach occurs.

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Cathy Grosvenor

Skilled writer, sub-editor, proofreader and PR practitioner. Winner of multiple Caxton, Sanlam and MDDA community press awards. Served as judge for both the Sanlam and Caxton community press awards. Over 30 years of experience; 15 of which were spent as the editor of an award-winning community newspaper.
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