A Human-Led Approach to AI-Enabled Surveillance
This article builds on industry commentary originally published in InSecurity Magazine, drawing on the insights of Andrew Robbins, Director of Security, Risk and Resilience at OCS UK & Ireland. It reflects OCS’s experience at the frontline of security delivery, supporting complex and high-risk environments where decisions must be made quickly and responsibly.
AI-powered CCTV is changing how organisations approach surveillance. Intelligent video analytics, behavioural detection, and real-time alerts are expanding what systems can identify and prioritise. Experience shows that the strongest outcomes come from a human-led approach, where technology supports better decisions rather than replacing them.
Across the environments OCS supports, the focus is on enabling frontline colleagues. AI provides earlier insight and clearer information, helping teams act decisively and keep people and places safe.
From Passive Monitoring to Proactive Intervention
Traditional CCTV systems were largely reactive, recording incidents for review after the event. AI-enabled surveillance changes this dynamic. Advanced analytics can detect anomalies, recognise patterns, and flag unusual behaviour as it occurs. The value lies not in the alert itself, but in how it is assessed and acted upon.
In high-footfall locations such as stadium concourses, behavioural analytics can detect early indicators of risk, including loitering, pacing, or erratic movement. Trained officers review these prompts and decide whether intervention is needed, often preventing escalation.
The same principle applies across sectors. In retail, early identification of suspicious behaviour can reduce theft. In healthcare, recognising signs of distress enables support to be dispatched without delay. Surveillance becomes a preventative capability, strengthening situational awareness and shortening response times.
Reducing Noise and Improving Focus
One of the most persistent challenges in CCTV monitoring is volume. In large or complex estates, operators may be responsible for thousands of feeds and alerts.
AI helps by filtering out false positives and prioritising activity that genuinely requires attention. This reduces alert fatigue and allows security colleagues to focus on incidents that warrant immediate action.
For organisations operating across multiple locations, AI-enabled CCTV can also connect insights across sites. This supports faster escalation, more effective coordination with partners such as law enforcement, and better-informed deployment of resources. Over time, shared data can reveal repeat patterns or seasonal risks, helping teams plan coverage more effectively.
Building Trust Through Transparency
As surveillance capability increases, the responsibility that comes with it becomes more pronounced. Public trust depends on transparency, ethical governance, and robust data protection.
Clear signage, proportionate use, and robust controls help people understand that AI-enabled CCTV focuses on safety and prevention, not intrusive monitoring. Explaining why systems are in place and how data is protected is central to maintaining confidence.
Some organisations reinforce this approach by publishing privacy impact assessments or sharing summaries of data protection audits. These measures demonstrate accountability and provide reassurance that surveillance technology is deployed responsibly and for a clear purpose.
Augmented Security, Not Automated Security
The future of CCTV is not fully automated. It remains human-led, supported by technology. Developments such as multimodal analytics and integrated platforms will continue to evolve, but their effectiveness depends on how they are implemented and governed.
OCS places emphasis on training, capability, and culture. Security colleagues remain responsible for judgment and decision-making. AI supports them with earlier insight and better context, rather than operating independently.
This balance reduces the risk of over-reliance on technology and helps organisations remain adaptable in complex, fast-moving environments.
The Road Ahead: Opportunities and Challenges
AI-enabled CCTV will continue to advance. Predictive analytics may help anticipate incidents, while integration with access control and emergency systems could improve coordination during critical events.
These opportunities bring challenges. Increased connectivity heightens cybersecurity risk, requiring robust protection for systems and data. Bias within AI models also demands careful oversight, with regular auditing to ensure fair and accurate interpretation of behaviour.
Cost remains a consideration. While AI-enabled CCTV can deliver long-term value through prevention and efficiency, the initial investment can be significant. Phased implementation and clear performance measures help organisations adopt the capability responsibly and sustainably.
A Human-Centred Future
AI-enabled CCTV marks a significant evolution in security, but technology alone does not ensure safety. Outcomes depend on the people who interpret information, make decisions, and act.
By combining the speed and consistency of AI with professional judgement and experience, organisations can build surveillance systems that are proactive, transparent, and resilient.
For OCS, the position is clear. The future of surveillance is about empowering colleagues to act with confidence and clarity. When technology is applied responsibly and with purpose, CCTV moves beyond observation to become a practical partner in protecting people and the places they rely on.
