Security Operations Centers (SOCs) are adopting artificial intelligence to combat overwhelming alert volumes, but many current tools fall short of their promise. A growing consensus among security professionals indicates that most AI-powered platforms primarily deliver faster alert triage—summarizing and prioritizing threats—without significantly reducing the manual workload for analysts.
While summarizing alerts with generative AI can shorten the initial time to acknowledge an incident, the core bottleneck remains. Security analysts are still required to manually perform the critical response actions, such as isolating an affected endpoint, blocking a malicious IP address on a firewall, or revoking compromised user credentials. According to a report from BleepingComputer, this focus on analysis over action means that the promised efficiency gains from AI are not fully materializing, leaving security teams burdened with the most time-consuming tasks.
The true value of AI in security operations lies in its ability to drive end-to-end automation. This approach involves integrating AI with orchestration platforms to not only identify and analyze a threat but also to execute a series of predefined response actions across multiple systems. For example, upon detecting a credible phishing attempt, an automated workflow could quarantine the email, block the sender, scan for other instances across the organization, and isolate any endpoints where a user may have clicked the malicious link.
By shifting the focus from simply providing faster insights to automating complete workflows, organizations can achieve a meaningful reduction in both analyst workload and incident response times. This allows human analysts to concentrate on more complex threat hunting and strategic initiatives, rather than executing repetitive, manual response tasks.
