Most AI in CCTV solves problems that weren’t there. That sounds sharp, but it is true. AI can add enormous value to video security. Only it is not automatic and certainly not everywhere.

What people expect from AI in CCTV

The expectations are understandable:

• Less manual monitoring
• Faster detection of incidents
• Better decision-making based on data

The image that often arises is that AI automatically makes an existing CCTV environment smarter. As if you turn on a function and you’re done. That’s not how it works.

Where AI is already delivering value today

AI works well in environments where patterns are recognisable and the context is stable. Consider:

• object or area detection in defined zones;
• counting and simple behavioural analysis;
• operator support with large amounts of camera images.

In these kinds of scenarios, AI reduces the workload. Not by replacing people, but by providing focus.

Case study

In a logistics environment, AI was deployed to detect anomalous behaviour. The technology worked, but the reports kept coming. The cause was not with the AI. The environment was constantly changing and the cameras were never positioned with analysis in mind.

AI did exactly what it was supposed to do, but the problem was in the principles.

Where things often go wrong with AI in CCTV

AI is regularly added without the prerequisites being right. Then disappointment ensues. Common causes are:

• insufficient or inconsistent input data;
• highly variable lighting and environmental factors;
• unclear expectations about accuracy;
• no management or training of models.

AI is not a separate component. It depends on camera setup, light, environment and usage. Without a good foundation, AI increases complexity rather than value.

The role of the VMS and customisation

A video management platform like Milestone XProtect makes it possible to integrate AI in a controlled way. Not as a gimmick, but as part of the whole. In some situations, standard functionality is sufficient. In other cases, you need to customise the solution, for example by using custom plugins.

The key question here is not ‘What can AI do?’, but ‘What actually adds something to the operation here?’. That distinction determines whether AI becomes a tool or a source of frustration.

Where can you start yourself?

When considering AI within your CCTV environment, don’t start with the technology. Start by asking the following questions:

• What decision do you want to be able to make faster or better?
• What signals are you missing today?
• Is the environment stable enough to recognise patterns?

If these questions cannot be answered sharply, AI is probably not the right move yet.

AI in CCTV: hype versus reality

The market is evolving rapidly: new models, new terms, new promises. This is not necessarily a bad thing, but it calls for sobriety. AI in CCTV is not a final solution. It is a tool that only works within clear frameworks. Those who accept that will get value out of it. Those who expect everything will be disappointed.

Conclusion

AI has a place in modern CCTV environments. But only if it is deployed with realistic expectations and a solid foundation. Not as a promise, but as a conscious choice.

Are you considering applying AI within your CCTV environment, but in doubt about its feasibility or added value? Then it is wise to look at the whole picture first. At DZ Technologies, we help organisations distinguish between what works and what is mostly promise. Quietly, substantively and without sales talk.

Feel free to contact us to discuss your situation.

FAQ