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4 challenges limiting AI video surveillance adoption in 2022

4 challenges limiting AI video surveillance adoption in 2022
As with anything new, AI video surveillance also faces several challenges that limit its adoption and growth.
Video surveillance has been entrenched in the realm of security for many decades, but the idea that video has value beyond security is fast gaining traction. New cameras with major technological advances in software and hardware are just beginning to hit the market from a variety of different manufacturers.

As with anything new, AI video surveillance also faces several challenges that limit its adoption and growth. Despite some obvious advantages that can increase return on investments multi-fold, several customers remain hesitant.

In general, additional education and awareness are needed at nearly all levels of the market. But knowledge gap is not the only issue. This article explores some of the major challenges that the AI-enabled video surveillance industry faces.

Organizational structure

Video is still entrenched in the security realm of most organizations, making surveillance positions report into security operations management or other administrative functions. Modern cameras provide much more than security, so much so that many leading organizations consider it a tool for business intelligence.

“While this is gradually changing as more disciplines within organizations begin to see the value of a camera as a powerful sensor, cameras are still mostly regarded as a tool for security and surveillance and are not yet included in other top-level, data-driven digitization efforts within a company,” explained Fabio Marti, VP of Marketing at Azena.

Lack of awareness across the value chain

The field of intelligent cameras and AI-enabled analytics is still very new. The market is becoming educated on the potential of these powerful edge sensors that can process sophisticated analytics.

“Customers need to see what is really possible with these cameras and how others have gained value from it,” Marti added. “Additionally, both systems integrators and end-user organizations have a current lack of comprehensive data science expertise amongst their staff to help drive initiatives such as leveraging a camera system’s potential for generating valuable data or driving operational efficiency.”

Lack of familiarity

According to Sam Joseph, Founder & CEO of Hakimo, the biggest challenge is that end-users have not become used to AI algorithms, and hence, in some cases, they are hesitant about whether the algorithms will actually work in practice.

“This can be overcome as more and more end-users adopt AI solutions and become confident in those algorithms over time,” Joseph said. “Because once someone sees AI algorithms in action, it will be obvious to them how the AI is clearly way better than humans in those tasks.”

Hassles of fine-tuning analytics

AI video surveillance cameras are as good as the training that goes into their intelligence. Dan Berg, Integrations Product Manager at Salient Systems, pointed out that a major challenge limiting the adoption of AI in video surveillance is the time and cost required to configure and fine-tune the analytics.

“To be successful, the integration organization needs to identify the right customer – one that understands the need for AI in their operations and is engaged with the technology on a daily basis,” Berg said. “Deploying AI analytics successfully requires the integrator and end user to have clearly defined goals and success metrics, as well as patience.”


The use of AI in video surveillance is here to stay. In the coming years, we are sure to witness more technological advancements that make security cameras smarter.

But their adoption may not be as fast as the industry would like to see. As it is, the security industry is slow to change, taking a long time to embrace new technologies. You can’t blame the customers either because the security of security devices is an equally important concern now.
More awareness of the benefits is necessary for AI-enabled surveillance systems to see more market penetration. This is something in which solution providers, as well as integrators, can play an equally important role in.
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