INTERSEC DUBAI 2026 – AI-Powered Security Cameras: From Reactive Monitoring to Proactive Intelligence

Rudie Opperman: Regional Manager, Engineering & Training – MEA at Axis Communications

1. How is AI transforming the role of security cameras from passive monitoring tools into intelligent decision-making systems?

AI is fundamentally changing what security cameras are used for. Cameras are no longer just recording devices that capture footage for review after an incident. They are becoming intelligent sensors that can interpret what is happening in real time.

With AI built directly into the camera, systems can detect objects, recognise patterns and identify unusual behaviour as events unfold. This enables organisations to move from reactive monitoring to proactive decision-making, responding faster and more accurately without relying solely on manual observation or post-incident analysis.

Axis will demonstrate this shift in practice at Intersec Dubai 2026, showing how intelligence at the edge enables cameras to generate actionable insights directly at the source, supporting faster decisions, improved safety and stronger operational outcomes across complex environments.

• How can AI in security cameras enhance operational efficiency while reducing manual monitoring costs?

AI significantly reduces the reliance on continuous manual monitoring by filtering out routine activity and directing attention to events that genuinely require action.

Instead of operators watching multiple screens or reviewing large volumes of footage, analytics highlight exceptions such as unusual movement, safety risks or policy violations. This improves response times, reduces operator fatigue and allows teams to manage larger or more distributed environments without increasing staffing levels.

For organisations operating at scale, this approach delivers measurable efficiency gains while maintaining high levels of situational awareness and control.

• What are the key benefits of edge-based AI processing in security cameras?

Edge-based AI enables data to be processed directly within the camera rather than being sent to central servers or the cloud for analysis.

This allows insights to be generated immediately at the scene, supporting faster response and more reliable system behaviour. It also reduces bandwidth usage and storage requirements, lowering infrastructure demands and overall system complexity.

Processing data locally strengthens resilience and privacy, as systems rely less on constant connectivity and continue to function effectively even in constrained or demanding environments.

• What industries are seeing the greatest impact from AI-enabled surveillance today?

AI-enabled surveillance is delivering the greatest impact in environments where real-time awareness, safety and operational continuity are critical.

This includes sectors such as critical infrastructure, transport and logistics, industrial facilities, smart cities and large public venues. In these settings, AI helps organisations detect issues earlier, respond more effectively and maintain smooth operations in complex or high-risk conditions.

Increasingly, security cameras are also being used as sources of operational data, supporting compliance, planning and informed decision-making beyond traditional security use cases.

• How is Axis leveraging AI to deliver smarter, more reliable, and future-ready security camera solutions?

Axis embeds intelligence directly into its devices and designs systems around open, scalable platforms that can evolve over time.

By combining edge-based analytics, purpose-built processing technology and a strong ecosystem of partners, Axis enables customers to adapt their systems as operational needs change. This approach supports long-term reliability, cybersecurity and consistent performance across the system lifecycle.

Rather than forcing frequent hardware replacement, Axis focuses on architectures that allow intelligence and functionality to grow through software, ensuring systems remain relevant, secure and effective as technology and use cases continue to evolve.