Security operations centers (SOCs) face pressure as cyberthreats become more sophisticated, and cybersecurity talent remains difficult to find. Traditional automation streamlines repetitive tasks through predefined rules.
Meanwhile, agentic artificial intelligence (AI) can plan and execute multistep security workflows, relying on human oversight for critical decisions. Organizations that want to benefit from these capabilities must first prepare their people and processes. These steps ensure their SOC is ready to support autonomous AI without compromising operational control.
What Is Agentic AI in a Security Operations Center?
Rather than simply responding to individual prompts, agentic AI can pursue goals with greater autonomy by reasoning through complex situations and executing multistep actions. Unlike traditional AI assistants that generate recommendations, it can adapt its approach as new information becomes available.
Agentic AI’s rapid momentum reflects this shift, with adoption reaching 35% in just two years, according to the 2025 Artificial Intelligence and Business Strategy report. Another 44% of companies plan to deploy this technology in the near future.
Within an SOC, agentic AI can independently investigate alerts and coordinate actions across multiple security tools while continuously updating analysts on its progress and findings. It can also adjust investigations as new threat intelligence and environmental changes emerge. This feature reduces the need for constant manual intervention. Even with these advanced capabilities, human oversight remains essential for high-risk decisions to ensure autonomous actions align with in-house policies.
How Agentic AI Can Transform SOC Operations
Agentic AI can accelerate alert triage by correlating telemetry across endpoints to identify the incidents that pose the highest risk. Instead of forcing analysts to manually sift through thousands of alerts, AI agents continuously evaluate security data. This enables them to automatically surface the threats that require immediate attention. This capability addresses a common operational challenge, as 52% of companies report that their IT teams spend too much time on manual data collection for security operations.
Agentic AI also streamlines incident investigations by automatically enriching indicators of compromise with threat intelligence before submitting likely root causes. Beyond investigations, the algorithm monitors historical and real-time data for suspicious behaviors. It can uncover hidden attack patterns that traditional detection methods might overlook.
What Prevents Many SOCs From Becoming AI-Ready?
Despite the growing interest in autonomous security operations, many businesses struggle with fragmented security tools and inconsistent data quality. These limitations reduce visibility and make it harder for AI systems to produce reliable outcomes. In fact, 52% of security executives agree that the fragmentation of their security solutions limits their ability to deal with threats effectively.
Common obstacles include disconnected security platforms that operate in isolation and legacy infrastructure that cannot easily integrate with modern AI-driven workflows. These issues slow incident response and prevent the model from reaching its full potential. Because AI relies on accurate and comprehensive information, organizations need high-quality security data to see meaningful improvements in SOC performance.
How Security Leaders Can Prepare Their SOC for Agentic AI
To ensure AI can deliver accurate outcomes at scale, security leaders must establish strong data and operational foundations.
Build a Unified Security Data Foundation
Agentic AI performs best when it has access to well-organized security data from across the environment. Consolidating logs and cloud security events into a unified view gives AI agents the context they need to correlate activity and identify meaningful threats.
Before introducing autonomous AI, companies should improve data quality by removing duplicates, correcting inconsistencies and standardizing formats. These processes ensure the system can generate accurate insights rather than amplify existing problems.
Foster Collaboration Across Security, IT and Engineering
Successful agentic AI adoption depends on strong alignment between SOC analysts, security architects and infrastructure teams. Much like a command center that may look impressive but fails to deliver in practice without consistent communication among teams, an AI-powered SOC cannot succeed if key stakeholders work in isolation.
Firms should establish shared objectives and define clear ownership for AI workflows. This way, every team understands its responsibilities and can respond consistently as autonomous capabilities evolve.
Strengthen Governance and Human Oversight
Strong governance becomes even more important as organizations give models greater authority to perform security tasks. Leaders should determine which activities AI can execute independently and which require human authorization. This approach reduces unnecessary risk while maintaining operational efficiency.
Comprehensive audit trails and clear accountability for AI-generated decisions are equally essential. Analysts and compliance teams must understand why specific actions were taken. These safeguards also address growing concerns about AI adoption, as one survey found that 61% of respondents are wary about trusting AI systems. Moreover, 71% agree that AI should be regulated. Organizations should ensure their governance frameworks align with applicable regulations so autonomous AI operates within established risk boundaries.
Start With Low-Risk Automation
Businesses should begin by piloting agentic AI in repetitive workflows such as security reporting before expanding its responsibilities. This phased approach allows security teams to identify areas for improvement without exposing critical response activities to unnecessary risk. At the same time, workforce development should remain a priority, as 77% of businesses identified reskilling and upskilling as key objectives for employees working alongside AI.
Gradual adoption also gives analysts time to build trust in AI-generated recommendations while gaining hands-on experience with new tools and workflows. As operational processes mature, businesses can safely extend agentic AI into more complex response activities. This creates a stronger foundation for long-term autonomous security operations.
Preparing the SOC for the Next Generation of AI
Agentic AI represents the next evolution of security operations, moving toward autonomous execution to enhance speed and accuracy. Companies with well-defined processes will realize the greatest value from agentic AI in SOCs, creating a foundation for responsible AI-driven operations. As the technology matures, leaders should prepare their teams to confidently adopt autonomous security operations while maintaining human oversight.
