AI-Powered SOCs, Explained

Contents

Security Operations Centers (SOCs) are the command center of an organization’s frontline cybersecurity defenses — responsible for monitoring threats, prioritizing alerts, and orchestrating remediation. However, today’s SOCs are facing an existential crisis: an overwhelming volume of increasingly complex and sophisticated threats combined with a shortage of skilled analysts. This perfect storm is pushing SOCs to their breaking point, burning out their teams and leaving their organizations vulnerable.

Legacy security solutions struggled to keep up with the evolving threat landscape, especially at scale. The rise of artificial intelligence (AI) has been hailed as a game-changer for SOCs, offering the potential for unprecedented efficiency gains.

But what does effective use of AI in the SOC look like? Below, we show top use cases for leveraging AI in the SOC and explore how AI is transforming security operations.

The technical foundations of an AI-powered SOC

Security automation has evolved way past SOAR — with Hyperautomation and AI integration forming the new cornerstones of modern SOC automation. Core components of AI used in SOC operations include:

  • Generative AI (GenAI) and Large Language Models (LLMs): These technologies can process vast amounts of security data to intelligently generate deeper threat insights, remediation recommendations, contextual case summaries, and new security workflows.
  • AI-driven Hyperautomation: By seamlessly integrating your security stack and instantly automating any security process using thousands of pre-built integration steps and AI-generated workflows, Hyperautomation offloads routine tasks, reduces analyst burnout, and accelerates threat response.
  • Natural Language Agents: AI SOC analysts can automate incident response by interpreting natural language instructions in security playbooks to execute tasks such as alert triage, containment, and remediation actions. Human analysts remain in charge of the processes and outcomes and can interface with AI agents using natural language for additional enrichment, investigation, and recommended next steps.

Top use cases for AI in the SOC

By analyzing vast amounts of data from across your security stack and executing intelligent automations, AI unlocks efficiency gains across SOC functionalities such as:

  • Incident investigation: Analyze massive volumes of alerts to identify patterns, suppress low-fidelity alerts, and automate triage and validation, accelerating the investigation process from start to resolution. 
  • Case management: Streamline the process of prioritizing, tracking, and managing security incidents by intelligently enriching and automating cases.
  • Workflow generation: Prompt AI with a natural language description of your use case to instantly build security automation workflows — no code required.
  • Case summarization: Analyze all relevant data points associated with a security alert to provide easy-to-digest, evidence-backed summaries of complex security cases, improving SOC analysts’ efficiency and collaboration.
  • Documentation: Automatically generate documentation for complex automated processes.
  • Executive reporting: Prompt the system to generate case info in the right tone and level of information for a specific persona, such as for a non-technical executive or board member. 
  • Team collaboration: Automatically alert Slack channels when a case is resolved.
  • Resource optimization: Use AI to assign cases to an available analyst based on workload and shift schedules. 
  • Data correlation: Combine and correlate data from all of the tools in your security stack, providing a holistic view of your security environment.
  • Threat response: Automate tasks like threat detection and containment for faster incident resolution.

How do AI-powered SOCs transform traditional security operations? 

Scaling SOC operations: AI can handle an influx of security events: triaging, investigating, and remediating the majority of Tier-1 and Tier-2 alerts. This frees up analyst bandwidth to focus on urgent incidents and strategic projects, enabling SOCs to efficiently scale their operations without increasing headcount (which is vital amidst today’s shortage of skilled cybersecurity talent).

Shifting to a proactive security posture: AI goes beyond just detecting and counteracting attacks by applying real-time intelligence to identify patterns and detect emerging threats. This allows SOCs to adopt a less reactive, more preemptive approach to address vulnerabilities before they can be exploited or breached. 

Reducing alert fatigue and analyst burnout: By autonomously triaging alerts and reducing false positives, AI reduces the number of irrelevant alerts that analysts must wade through. And, by automating tedious, repetitive tasks and auto-remediating most low-level alerts, AI helps senior analysts gain back the time and capacity to focus on more rewarding work like strategic projects. 

Speeding up MTTR: All of the efficiency gains from leveraging AI in the SOC translates to more alerts resolved, faster. 

Will AI replace humans in the SOC?

Adopting AI in the SOC is not about replacing human SOC analysts — it’s about augmenting and empowering them. With a looming 4 million+ cybersecurity talent shortage, organizations must not only retain their existing analysts, but also help them work more efficiently. On top of that, organizations are recognizing that human-only defenses are inadequate to counter the evasive and persistent threats posed by AI-driven attacks.

AI reduces analyst burnout: AI can reduce the strain on SOC teams by offloading rote tasks, auto-remediating the majority of Tier 1 tickets, and upleveling the skills of junior analysts. This frees up senior analysts to focus their expertise on critical threats and strategic projects to help their organization achieve a stronger security posture overall.

Human expertise must remain the final line of defense: Done the right way, AI-powered SOCs keep humans “in the loop” as the ultimate decision-makers for high-stakes threats following rigorous, multi-tiered AI evaluation and case enrichment that helps human analysts take informed, decisive action.

“By 2028, AI in threat detection and incident response will rise from 5% to 70%, to primarily augment, not replace staff.” 

Source: Gartner Inc.

How Torq’s AI capabilities supercharge SecOps

Torq has been very deliberate in how we’ve extended the capabilities of the Torq platform using AI to solve real problems for SOCs with products and features like:

  • AI Workflow Builder: Simply describe your desired security automation workflow in natural language, and Torq’s AI Workflow Builder will generate a tailored solution in seconds. Rather than spending hours manually building workflows from scratch, your team is freed up to focus on more strategic security initiatives.
  • AI Case Summaries: Help your team make the right decisions quickly by presenting them with a concise, insightful, and verifiable AI-generated summary of each case. No more wading through pages of logs and incident details! The easy-to-read summaries empower SOC teams to work faster, make informed decisions with confidence, and seamlessly transition between shifts by giving the incoming team clear case context backed by citations.
  • Socrates, the AI SOC Analyst: Socrates intelligently automates alert triage, incident investigation, and response, extending your SOC teams’ capabilities and improving response times across the board. Socrates can autonomously execute runbooks written in natural language, auto-remediating 95% of cases within minutes. For critical cases that require human intervention, your analysts can collaborate with Socrates using natural language to summarize case details, enrich cases with additional investigation and threat intelligence, and trigger remediation workflows.

The future of the SOC: Better, faster human decision making through AI automation and insights

When deployed effectively, AI in the SOC extends and enhances the capabilities of your existing staff so they can make better decisions, faster. 

So, what does the future of SOC automation look like? Sophisticated AI technology continuously learning from historical data and real-time incidents to generate insights and recommendations, automate routine security tasks, and auto-remediate the majority of alerts, with a top layer of human analysts providing strategic oversight for critical cases. This means faster, more proactive responses to threats and vulnerabilities — and a more secure future for organizations everywhere.

Want to learn how Torq transforms SOC operations with AI-driven Hyperautomation? Explore HyperSOC.