Over the last year, enterprise security operations centers (SOCs) have seen a surge in alerts linked to artificial intelligence (AI) tools and agents. These alerts stem not from attacks on AI, but from regular use within organizations. Developers and staff frequently use AI tools, triggering alerts that enter the SOC stream.
Despite accounting for only 0.43% of all SOC alerts, AI-related notifications are increasing rapidly, having grown by 685% between February and June 2026. Although AI alerts currently represent a small fraction of the total, their rapid growth indicates a significant trend.
Understanding AI-Triggered Alerts
AI-related alerts are characterized by their composition rather than volume. They are sorted into three categories: real attacks, risks, and noise. A staggering 94.1% of these alerts are noise, 5.8% represent genuine risks, and only 0.02% are real attacks.
The noise primarily results from normal AI tool usage that appears suspicious to detection engines. In contrast, real attacks often exploit AI brand names in phishing schemes, leveraging the familiarity and trust employees have with these brands.
Impact of AI Adoption on Alert Volume
AI tools contribute to a growing number of alerts, with around 73,000 AI-related alerts among 16.9 million total SOC alerts. This growth is continuous, with each month surpassing the previous in alert count. The rapid increase suggests the current percentage of AI alerts is merely a baseline, with much higher volumes expected soon.
Most AI-generated alerts are noise, triggered by outdated detection systems misidentifying legitimate activities. For example, coding agents performing routine tasks often trigger alerts due to pre-existing detection rules not adapted for AI use.
Strategies for Managing AI-Related Alerts
To manage the influx of AI-related noise, SOCs need to tune legacy detection systems to differentiate between genuine threats and normal AI behavior. This involves updating detection engines to recognize standard AI activities and minimize false positives.
Furthermore, security teams should establish clear policies on data sharing with AI platforms and proactively monitor risky activities, such as permission-bypass flags and unauthorized data access.
Running AI tools in isolated environments can help segregate their actions from user activities, reducing the risk of unauthorized access to sensitive information.
Conclusion: Preparing for the Future
The integration of AI into enterprise environments has not led to an increase in AI-enabled breaches, but it has significantly raised the volume of alerts. While most are false positives, they can obscure genuine risks, making it crucial for SOCs to adapt detection strategies.
By distinguishing normal AI activity from potential threats, SOCs can better handle the growing alert volume without being overwhelmed. This approach will ensure effective security management as AI adoption continues to rise.
Intezer offers an autonomous AI SOC platform designed to address this challenge by providing comprehensive alert analysis without overwhelming analysts. Visit intezer.com to learn more about how their platform can support your SOC.
