Artificial intelligence (AI) holds significant promise for increasing productivity in all business functions, and cybersecurity is no exception. Arguably no area of the security workforce is more poised to benefit from AI than the security operations center (SOC). Today’s SOC teams manage continuous attacks while navigating a complex and disparate tool environment, large volumes of data, and a shortage of security experts. Within this scenario, the AI generation assistant (GenAI), purpose-built as a security platform, presents an important opportunity to allow security teams to work at the speed needed to turn the tables on would-be attackers.
But AI is only as good as the data it works on. Fortunately, the modernization of SOC functions is already underway, bringing unprecedented visibility into security-related events across the enterprise. The emerging combination of this visibility paired with an AI-enabled assistant in SOC has security leaders taking notice.
XDR and AI combine to drive unprecedented visibility and high-speed response
The increasing adoption of extended detection and response (XDR) platforms is at the core of the SOC modernization effort. XDR solutions integrate security telemetry across security domains, including identity, endpoints, software-as-a-service (SaaS) applications, email, and cloud workloads to provide detection and response capabilities on a unified platform.
XDR platforms can use AI to correlate cross-domain security signals that consider all attacks and identify threats with a high degree of confidence. This is in stark contrast to traditional automated detection and containment solutions that often rely on a single identification of a compromise. The increased reliability that AI brings to the table greatly improves the signal-to-noise ratio and results in fewer false positives for manual investigation and configuration.
Significantly, the more data available for AI to analyze, the more effective it will be. Therefore, it is important to consider how to best access the wider scope of XDR coverage to fully unlock the capabilities of AI.
The GenAI assistant is purpose-built for SOC conversion
The use of GenAI in SOC has the potential to revolutionize security analysts. They can use GenAI to summarize an incident, assess its impact, provide actionable recommendations for rapid investigation and remediation, and create a post-response task report. Guided assistance can also help unlock new skills that allow analysts at all levels to complete complex tasks like threat hunting, malware reverse engineering, and more. With AI-driven threat intelligence, analysts can ask in natural language about emerging threats and their organization’s exposures and get contextual insights to help them respond.
In randomized controlled trials of its Security Copilot, Microsoft found that security professionals were an average of 22% faster on all tasks when using Copilot. In addition, it found that 97% of participants wanted to use Copilot the next time they completed the same task.
The opportunity is endless, but execution must be based on the principle that AI will not replace human talent in SOC—it will augment it. This requires a thoughtful, user-friendly approach to integrating GenAI into existing workflows, as well as ensuring high levels of accuracy and transparency. SOC teams must have complete control when investigating, repairing, and bringing assets back online.
Taking AI forward in SOC
In this rapidly evolving environment, a thoughtful, forward-thinking implementation strategy can help innovative security organizations confidently leverage today’s AI capabilities and lay the foundation for a seamless adoption of tomorrow’s innovations.
An effective AI strategy will appropriately identify and address high-risk areas, cybersecurity maturity, existing infrastructure and tools, and budget constraints among other factors. While the implementation should be phased to minimize operational disruption, organizations should also consider how to ensure the broad scope of XDR to optimize their AI investments.
In addition, the most successful organizations will take a human-first approach to the implementation of AI that focuses on the needs of analysts. The impact of AI on the SOC should also be tracked and measured to help refine use cases and maintain a good user experience. For example, organizations can compare team metrics six months before implementing GenAI against metrics from the first six months of full team implementation. Top metrics to consider would be: mean time to response (MTTR); events that run on the day; and average incident resolution time.
AI is already changing the way knowledge workers around the world deal with to-do lists. It’s no surprise to see cybersecurity professionals take notice, especially those in SOCs where importing, analyzing, and reporting information is a big part of the daily workflow. But the rapid pace of AI development and adoption can make it difficult to see what’s just marketing in what could provide a tangible improvement to your online security. This challenge likely won’t go away anytime soon, but rest assured that basing your AI strategy on a deep understanding of your security team’s needs is a good place to start.
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