AI Adoption in Security: Why It Matters and How to Get It Right

Across industries, artificial intelligence (AI) has transitioned from a futuristic concept to a practical, competitive necessity. The question is not if organizations should adopt artificial intelligence, but how they can do it thoughtfully. AI’s capabilities are accelerating rapidly, from streamlining logistics operations to triaging cybersecurity alerts. How do you know which processes best benefit your business, and why should security leaders invest in this technology?

First, the risk of not leveraging AI is too great. For example, recently, thieves executed a heist at the Louvre Museum, stealing priceless and historic jewels. A single surveillance camera was monitoring the exterior wall where the thieves broke in, and on that day it was tilted in the wrong direction. AI is an expert at pattern detection, and it could have easily flagged this tilted camera as an anomaly, allowing it to be fixed in a timely manner. An AI solution could have prevented the thieves’ entry, flagged movement during the heist and preserved the footage. But because no proactive measures were in place, the suspects were able to get inside undetected and law enforcement were left scrambling for the missing video evidence.

In the security industry, AI empowers organizations to take preventative action against looming security threats. However, adoption requires strategic planning, organizational buy-in and thoughtful integration. When considering a new AI solution, first answer the question, “What is our biggest challenge?”

Maybe a city’s transportation department is struggling with limited resources and delayed response times to traffic incidents. As a result, officials might decide to pilot an AI solution for automated detection of stalled vehicles or collisions. With this clear use case in mind, the city can measure impact without overcommitting resources. Also, to ensure success, security teams should collaborate with other departments, like IT, traffic engineers, dispatchers and legal teams, to assess practicality and policy alignment. This approach—problem-based, pilot-focused and converged—makes adoption more intentional and more likely to succeed.

While the promise of AI is enormous, there are risks to implementing any new technology. Bias in algorithm training data and overreliance on automation can cause critical errors in workflows and decision-making. That is why transparency, human-in-the-loop systems and strong governance must be baked into any AI initiative. AI adoption is more than a hurried business solution. It is a leadership decision that can transform an organization. Those who embrace AI intentionally, iteratively and ethically will be the ones who lead the security industry into the future.

The views and opinions expressed in guest posts and/or profiles are those of the authors or sources and do not necessarily reflect the official policy or position of the Security Industry Association.

This article originally appeared in All Things AI, a newsletter presented by the SIA AI Advisory Board.