How AI Is Fueling the SOC of the Future

The traditional Security Operations Center (SOC) is undergoing a major shift, primarily driven by AI integration. Nearly 90% of organizations now utilize AI technologies, with significant application in threat detection, response, and incident recovery. However, only 27% have fully automated threat detection, indicating a gap in realizing AI’s full potential. To keep pace, security leaders must strategically harness AI to build the SOC of the future.

How AI augments SOC teams and integrates workloads

AI can help security analysts redefine their roles and empower them to focus on higher-value, strategic initiatives. Defenders can shift from a constant reactive mode to work that reduces risk and elevates the value of security operations in the business.

We have often talked about products in the SOC, such as Security Information and Event Management (SIEM), Security Orchestration and Automated Response (SOAR), and User and Entity Behavior Analytics (UEBA) are core components of SOC operations. These are sometimes poorly stitched together in workflows, resulting in a Frankenstein of interoperability difficulties, and unnecessary mental load for analysts. However, modern conversations now focus on capabilities rather than products, especially as AI is helping to reduce the switching fatigue by acting as a connecting tissue.

AI doesn’t stop at connecting existing tools together; it’s also a major productivity enhancer. It can co-author playbooks with an analyst, saving them the basic grunt work of creating yet another automated response from scratch. AI can also summarize an incident, drawing out the most relevant information from what’s presented and giving the analyst an early briefing head start.

When SOC teams leverage AI agents in their workflows, they benefit from even faster containment, scaled response, additional capability, and reduced manual toil. For example, AI agents that can auto-triage and remove false positives give analysts a head start when working through a ticket queue. But it’s not just about efficiency or productivity; AI can bring new capabilities into the SOC that were previously outsourced tools. For example, reverse engineering, where AI can figure out how a particular malware works to give security teams an understanding of what might have happened in an attack. These tools can also perform more in-depth analysis than automation during an investigation, ensuring much of that preparatory work is completed before the analyst reviews an incident.

Tapping into these AI tools will become vital for SOCs as threat actors are leveraging AI, and the pace of the cat-and-mouse game speeds up.

The Benefits of an AI-Powered SOC

When SOC teams spend all their time responding to alerts or addressing incidents, they have no time to contribute to strategic programs that drive efficiencies in the SOC. This is detrimental to the business, as digital system resilience directly impacts profitability.

AI unlocks a step-change in freeing up time, just as automation did before. This enables SOC teams to focus on strategic, proactive initiatives that drive business growth, reducing incident volume and creating more capacity for further investment.

In addition to freeing up time for SOC teams, AI will enhance the quality of response and help teams to respond faster. As attackers increasingly use AI to accelerate and scale their attacks, it is essential that modern SOCs adopt similar capabilities.

Developing an AI-Powered SOC

To establish an AI-powered SOC, cybersecurity leaders must first analyze the current SOC practices to identify tasks that require the most manual effort and then accelerate those tasks with AI. Common starting places include:

Authoring and managing detections: Many SOCs already leverage vendor-written detections and fine-tune them to meet their specific needs. AI can further enhance this process by co-creating and authoring new detections. Beyond just creating and authoring new detections, AI can also relieve analysts from the burden of managing the detection lifecycle. When a detection stops triggering or becomes too noisy, AI can identify the issue and suggest refinements to improve detection fidelity. For example, just as Netflix suggests films, AI can power a detection recommendation engine that determines which detections offer the best coverage, based on your data and the threats you face.

Interpret findings: AI can give analysts a head start by summarizing and highlighting key information from alerts. In addition to automatic enrichment, which saves time and prevents repetitive, draining tasks, AI can identify important details and suggest likely next steps This allows analysts to retain control, while saving valuable minutes on each investigation.

Run investigations: For a SOC, collaborative investigation of potential threats is not merely a function, it is the core mission. Effective investigations rely on having quality data to apply the right analytics and make informed decisions. While this may sound basic, achieving such a workflow across all business areas is surprisingly challenging. AI can enhance the SOC’s investigative capabilities by autonomously handling parts of an investigation, such as analyzing malware samples, or accelerate existing methods, like efficiently searching for similar malicious patterns in other assets. Offloading these tasks from overburdened analysts increases team capacity and allows them to focus on complex analysis, investigation, and remediation.

Draft investigation reports: Investigation reports are often tedious and time-consuming, but they are essential for corporate knowledge, historical records, and compliance. When high-quality, these reports can even serve as a valuable data source for AI, revealing common patterns and remediation trends within the SOC. However, writing them is typically lengthy, laborious and dull. This is where AI can shine: it can quickly gather information and create comprehensive reports. Is it glamorous? Maybe not. But it saves 15-20 minutes per investigation; time that quickly adds up.

Authoring playbooks: Playbooks automate security workflows, allowing security analysts to spend more time investigating threats. They deliver significant benefits in terms of time savings, response quality, and consistency. Additionally, playbooks serve as a clear documentation of the correct responses for specific scenarios, a valuable advantage for compliance teams! However, creating effective playbooks takes time and refinement to ensure they activate appropriately in relevant situations. Analysts often face such time pressures that it’s hard to develop these resources from scratch. Again, AI can help accelerate this process by generating and co-authoring playbooks, enabling analysts to avoid starting from a blank page.

Establishing the Future-Ready SOC

Leveraging AI will give your SOC a significant advantage, freeing up valuable time to develop a security strategy and remain prepared for whatever lies ahead. As complexity increases, including AI-driven attacks, targeted insider threats, and evolving cybersecurity regulations, staying ahead is more challenging than ever. However, the future SOC is not just about being battle-ready; it’s building resilience that endures, enabling organizational agility, and strengthening your business’s bottom line and reputation.