Security camera companies are embracing AI to give customers detailed descriptions of surveillance footage that are often spot on but can also be wildly wrong (Scott Calvert/Wall Street Journal)

Security camera manufacturers are rapidly deploying AI-powered video analysis to provide detailed surveillance insights, but the technology exhibits significant accuracy gaps that can generate costly false alarms and misallocated response resources. For IT leaders responsible for physical security infrastructure, this creates a critical governance challenge: implementing AI-enhanced surveillance requires careful validation protocols, clear liability frameworks, and hybrid human-in-the-loop verification processes to mitigate false positives that could trigger unnecessary emergency responses or damage organizational reputation. Organizations must balance the operational efficiency gains of automated threat detection against the business risks of unreliable AI outputs before widespread deployment.