How AI is Reinventing the Security Operations Center

The typical SOC team can be presented with thousands of security alerts every day. While most turn out to be false positives, each needs reviewing, and, nevertheless, creating a to-do list that is almost impossible to complete. Unsurprisingly, security professionals are often in the position of having to firefight. Picking which alerts to focus on and which ones to leave can mean missing a true positive. The idea of taking proactive stance that everyone in the industry aspires to can be an impossible ideal.

This all-too-common scenario isn’t just an operational nuisance; it can bring the very real risk of missing genuine threats while also contributing to a much broader issue: burnout. A recent industry study, for example, revealed that nearly three-quarters of SOC analysts experience some level of burnout, caused by issues such as understaffing and increased workloads. As a result, nearly two-thirds say they are likely to switch jobs in the next year. – a situation which is simply unsustainable over the long term.

Adding to the sense of pressure is the nature of today’s attacks, with threat actors using AI to create highly adaptive, fast-moving threats. The big problem here is that traditional security tools and manual processes simply don’t scale in this environment. Without the ability to understand and act on threats at machine speed, even well-resourced SOCs risk being outpaced, leaving critical systems exposed and teams constantly stuck in reactive mode.

The case for SOC automation

This puts some organizations into a perfect storm scenario, where their adversaries are ideally placed to exploit gaps in coverage before stretched security teams can respond. Thankfully, the situation is far from one-way traffic, with AI-driven platforms also having a transformational effect on how SOCs go about various key processes, from automating routine tasks to helping analysts identify and prioritise high-priority threats.

Take automated triage, for example, where AI can be used to process enormous volumes of alert data in near-real time. In this context, its role is to filter out the false positives that can drain SOC resources and, instead, escalate only the genuine threats for expert human review. Crucially, the best solutions can triage any alert, regardless of type, source or format to provide a level of responsiveness that manual processes can no longer match.

Instead of wading through a backlog, analysts are presented with a curated shortlist of credible threats, each with contextual insights and recommended next steps. Investigation times are cut from hours to minutes, and the team is no longer stuck in reactive mode. Released from the associated impact of alert fatigue, analysts can focus their efforts more effectively on potentially critical and emerging incidents.

AI also transforms response times. By automating investigative steps and generating dynamic remediation recommendations, analysts can quickly understand the scope of a threat and act immediately, often with a single click. In contrast to rigid, rule-based workflows, this introduces much-needed flexibility into SOC operations.

Elsewhere, AI is changing the economics of log management. With affordable, scalable and vendor-neutral solutions, SOCs can now store and query vast archives of security data efficiently, supporting long-term compliance and, when required, forensic investigations. In particular, integrated log management across multiple systems and sources makes it easier to unify this information and identify meaningful patterns or anomalies that might otherwise go unnoticed.

The benefits aren’t just technical, they’re human. By reducing the volume of repetitive tasks and improving working conditions, AI can help stem the tide of burnout and attrition seen across SOC teams. It also lays the foundation for a more strategic role, where analysts spend less time juggling immediate priorities and more time focused on improving security posture.

These represent a compelling set of capabilities, but even with automation in place, AI isn’t a silver bullet. While it excels at automating repetitive tasks and processing large volumes of data, there are still critical areas where human judgment remains essential. From assessing the context of a threat to making strategic decisions about incident response, experienced analysts play a vital role in ensuring that SOC operations remain accurate, ethical and aligned to business risk.

There are also important questions to consider around data quality, model transparency and the potential for bias, all of which require careful oversight to avoid unintended consequences. The point is, AI can enhance SOC performance, but it must be deployed with a clear understanding of its limitations.

Overall, however, the case for increasing the role of AI within contemporary SOCs has, for many across the industry, already been made. The question is, how quickly can organizations deliver on the undeniable benefits?

About the Author

Shahar Ben-Hador is the Co-Founder and CEO of Radiant Security, an AI-powered security platform designed to modernize Security Operations Centers (SOCs). Before founding Radiant Security in 2021, he held key leadership roles at Exabeam, where he served as CIO and later as VP of Product Management, helping to develop the company’s first SaaS product. His cybersecurity journey began at Imperva, where he progressed from IT Administrator to become the company’s first-ever Chief Information Security Officer (CISO).

Shahar Ben-Hador can be reached via [email protected] and at www.radiantsecurity.ai