AI in Access Control: Enhancing Security with Intelligent Analytics
Artificial intelligence has now graduated from an academic ponderance to an inescapable juggernaut. Its potential for a business, regardless of industry, is enormous. We can see it make its mark in retail, banking, and healthcare. It also has a role to play in security, both digital and physical. It can enhance analytics capabilities, improve threat detection, and support predictive maintenance.
The Business Case for AI Integration
One study from McKinsey suggests AI could pump some US$150 billion, or 9% of combined GDP, into GCC economies. HID’s State of Physical Access Trend Report reveals more than a third (35%) of organizations worldwide will be testing or implementing some sort of AI capability in the next five years. In the course of our research, we heard from more than 1,200 enterprise decision-makers around the world and identified the use of AI as one of five main trends currently dominating the physical security segment.
The prevailing perception about AI is that it is here to stay and there is no going back, and so enterprises must adopt it to remain relevant. But none of that means AI has reached some sort of ceiling of maturity – certainly not in the GCC where AI skills gaps persist. What it does mean is that, as skills gaps are gradually filled, more use cases become viable.
The Evolution of AI in Physical Security
That is why we are seeing movement toward AI in physical access control. Thirty-eight per cent of respondents to HID’s survey said they were looking to incorporate AI into their access-control solutions, although the same percentage admitted they were unsure of the benefits. But it is also worth noting that less than a quarter (23%) said they had no plans to incorporate AI.
We found that many security professionals see AI’s strengths in analytics as low-hanging fruit, so rather than opting for an AI-centric security system, they are looking for ways to have AI-driven analytics enhance existing or future solutions. So, as mentioned previously, 35% of respondents said they would test or implement some form of AI in the next five years. Some 15% already use AI-enabled biometrics.
AI is a powerful partner in digitalization, from automation of the day-to-day grind of a knowledge worker to the enhancement of future-gazing for finance professionals. And engineers. In the physical world, things break. But the costs of repair are largely predicated on the ability to catch the problem early. If we keep enhancing that capability enough, we can replace minor components prior to equipment failure and save significant expenditure on replacements. This advanced condition-monitoring made possible by AI and machine learning gives rise to predictive maintenance. Remember that a point of failure in, say, a manufacturing capability is bad enough, but if we imagine the same in a physical access ecosystem, the consequences could be well beyond those of lost capacity or missed deadlines.
The same AI that monitors temperature, power, and rotation speeds looking for deviations from norms in physical equipment can do the same in a digital setting. Pattern matching is orders of magnitude more efficient with AI than with human observers. AI-driven physical security will come to dominate in a world where, with due diligence, AI can make everything better.
