AI in Security and Surveillance
ADI experts share insights about this growing trend
Artificial intelligence has moved beyond a futuristic concept into a transformative force in the physical security sector, particularly in video security.
Artificial intelligence (AI) has become a game-changer in the physical security sector, driving advancements in AI security systems and transforming traditional approaches to video surveillance. From improving efficiency to reducing false alarms, the integration of AI in security and surveillance is reshaping the industry.
The evolution of video security from passive monitoring to active, intelligent systems is largely driven by artificial intelligence (AI). These AI security systems can quickly and accurately process and analyze vast amounts of live or recorded video data, enabling security operators to identify critical events without manually reviewing hours of footage.
“Features that were once considered high-end options in cameras are now becoming standard,” says Nathan Vaughn, commercial video and access control specialist at ADI. “Most cameras today will have some advanced analytics that goes beyond simple motion, including person and vehicle detection, and being able to classify objects.”
Thanks to AI video surveillance systems being able to employ deep learning and neural networks, basic analytics tasks like motion detection and object tracking have become commonplace. These systems can now provide advanced capabilities, such as detecting fine attributes of objects, tracking individuals or vehicles across multiple cameras and detecting and flagging anomalies in real time. These features make AI CCTV systems a vital component of modern security infrastructure, allowing operators to focus on genuine threats rather than routine activity.
“This technology has become very easy to use; it doesn't take a skilled professional to use the search functions,” says Vaughn. “Users can search for who was wearing a red shirt in a certain location on Saturday, or find out if someone moved through a scene with a backpack. You can search for vehicles based on size, type, color and specific license plate information. The software brings it all together, and you can create a timeline of an event in a matter of minutes — not hours or days.”
The advent of AI and security technology has revolutionized video analytics, transforming what was once a basic tool into a sophisticated security solution. Although traditional systems could detect motion, they often triggered false alarms from swaying trees, wandering animals or changes in lighting. Today's AI-powered analytics can distinguish between routine activity and genuine security concerns.
Modern AI security systems are even being trained to understand context and complexity within scenes. They can analyze group dynamics, identify hostile interactions and interpret human behavior patterns through pose estimation technology. This advanced scene comprehension allows security teams to focus on actual threats while reducing costly false alarms and unnecessary responses.
"Today's mid-tier systems can track multiple vehicles or people across an entire facility, measuring their speed and direction,” Vaughn says. “In commercial settings, we're seeing powerful safety features like the ability to detect weapons, identify gunshots and analyze various types of sounds that might indicate a threat."
Edge-based processing further enhances these systems by conducting analysis directly on security devices — which is a game-changer for system responsiveness. By processing data at the source rather than sending everything to central servers or the cloud, edge computing delivers real-time analysis with minimal delay. This immediate processing proves crucial for time-sensitive applications like intrusion detection or emergency response, where every second counts.
Edge processing also offers practical advantages for smaller installations. Users can deploy targeted analytics for specific needs like people counting or perimeter monitoring without investing in expensive on-premises servers. This makes advanced AI capabilities more accessible and cost-effective for organizations of any size.
AI surveillance systems have practical applications across various industries, including in commercial settings, healthcare facilities and retail environments. By integrating video, audio, IoT sensors and access control, AI in security and surveillance provides a comprehensive understanding of potential threats, enabling proactive prevention and efficient response. For example, a modern AI surveillance system might simultaneously analyze unusual movement patterns, detect specific sound signatures and track access control anomalies to identify potential security breaches before they occur.
This multimodal approach to security is particularly valuable in complex commercial environments. In healthcare facilities, systems can monitor everything from patient safety to restricted area access. By integrating with existing building systems such as lighting, alarms and intercoms, AI-powered security solutions can create a coordinated response to potential threats.
In retail environments, AI-powered systems are helping prevent theft while also providing valuable business intelligence. Advanced analytics can identify suspicious behavior patterns, track customer flow and even integrate with point-of-sale systems to detect potential fraud. These same systems can provide insights into customer behavior and store operations, making them valuable tools for both security and business optimization.
The evolution of AI in security extends to residential applications as well.
"Even in home automation, AI is becoming more prevalent. Products like Google Nest can determine whether a package has been left, identify visitors and manage home security more intelligently."
- Brian Creech, intrusion and commercial fire systems specialist at ADI
The residential smart camera market has grown rapidly as manufacturers integrate more sophisticated AI capabilities into consumer-friendly devices. These systems offer many features previously available only in commercial systems, but now packaged for home use. Popular applications include automated responses to detected events, customizable alert zones and integration with smart home devices for automated lighting and access control.
“On the residential side, we're seeing AI features built into video doorbells and exterior cameras that can reject false alarms from things like postal carriers or package deliveries,” Creech adds. “Some systems even include facial recognition capabilities that can identify family members and regular visitors.”
Despite the advantages of AI in security and surveillance, many integrators face hurdles in adopting these technologies. Key blockers for many integrators include the complexity and perceived high cost of AI solutions. The rapid pace of technological advancement can make it difficult for integrators to stay current with the latest capabilities and best practices.
“Things can move very slowly when it comes to new technology adoption,” Creech says. “A lot of installers and integrators are comfortable where they're at. And getting them to move can be tough at times.”
Many integrators struggle with the transition from traditional security systems to AI-enhanced solutions, facing not only technical challenges but also education gaps due to changes in how systems are designed, sold and maintained. The shift often requires new skill sets and different approaches to project planning and implementation.
“Everything's a bid project,” Vaughn adds. “If you come in with a higher-end system, a lot of companies won't get that job. They don't know how to sell the benefits or explain why this system is more valuable and how it could save money in the long run.”
Another challenge is demonstrating the return on investment of AI-driven systems. Many end users may not initially see the need for AI-enhanced features, especially if they're used to more traditional video security setups. Demonstrating the value of AI in security and surveillance to hesitant clients can be challenging. This hesitation is particularly common among smaller organizations and residential customers who may be more price sensitive.
Integration with existing systems poses another challenge. Many organizations have substantial investments in legacy security infrastructure, and integrators must find ways to incorporate AI capabilities without requiring complete system overhauls. This often requires creative solutions and careful planning to ensure smooth integration while maximizing the value of existing investments. The use of smart cameras and smart edge devices, along with pay-as-you-go cloud-based solutions, is alleviating many of these scalability concerns.
One key to overcoming adoption challenges lies in education—both for integrators and end users. Industry events and manufacturer training sessions play a crucial role in keeping integrators informed about the latest AI capabilities and applications, including AI video surveillance systems.
“A good place to learn about new technologies is at an expo,” Vaughn says. “We'll have a lot of end users come back from the expos and ask questions about new products and technologies. They have a chance to see new products, talk to the representatives and see the tech in action.”
Successful integrators are taking a proactive approach to education, participating in manufacturer training programs and industry certifications.
They're also developing internal expertise in AI technologies and building relationships with vendors who can provide ongoing support and guidance. This investment in knowledge and skills is becoming increasingly critical for remaining competitive in the evolving security landscape.
“The exposure of technology and the education of the end user is really the benefit,” says AJ Shaw, systems group supervisor at ADI. “Once the end user wants it, then the installers will need to know about it. And that's where it really starts. A lot of our vendors and manufacturer representatives will go out to the end users and help educate their customers. And while our expos are geared more toward our customers than the end users, it doesn't hurt to have a customer bring in their end users to talk to a vendor. It can be very valuable.”
The future of AI in security isn't about replacing human operators — it's about empowering them with better tools and insights. While AI handles the massive task of continuous monitoring and initial analysis, human operators remain at the center of the decision-making process. This “human-in-the-loop” approach ensures that AI serves as a powerful tool for enhancement rather than replacement of human judgment.
The technology is rapidly advancing toward more sophisticated scene understanding capabilities. Rather than simply identifying objects, next-generation AI will better comprehend complex interactions and behavioral patterns within scenes. This advancement will enable AI security systems to better predict potential issues before they escalate into serious problems.
The key to successful AI implementation lies not in selling technology but in providing solutions to real problems.
As these systems become more sophisticated and accessible, integrators who can effectively communicate their value will be better positioned to serve their clients' evolving security needs. Success in this rapidly evolving landscape will depend on staying informed about new capabilities while maintaining a steady focus on practical, client-focused solutions.
“My advice to integrators is to ask more probing questions to your customers,” Vaughn says. “Ask why they called you, if they're having any issues, break-ins or theft. Walk around the site, get a design or plan together based on that information. If you have a real conversation with a customer and understand their needs, you're not selling anymore; you're providing useful tools to help them solve problems and create a secure environment. And, in these situations, AI-driven solutions can be very effective.”
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