How Much Authority Should AI Have in the SOC?
AI and Cybersecurity
How Much Authority Should AI Have in the SOC?
What Securonix’s 2026 research Reveals about AI adoption, human oversight and accountability in the SOC.
Simon Hunt, Chief Product Officer, Securonix
Almost every respondent to Securonix’s 2026 survey reported a larger budget for AI in cybersecurity automation, and 87% said their organizations already use it in that work. Leaders are deciding which actions these systems can take on their own and which require a person’s approval. Whether an action needs human approval should depend on how much it could disrupt the business and how easily it can be reversed.
Human Oversight Remains Central
53% of respondents favor a human-in-the-loop approach to AI in cybersecurity. Across the specific SOC use cases surveyed, an average of 48% use AI to recommend actions that a person approves, while 13%, on average, report fully autonomous use. An average of 32% believe those use cases will always require human involvement.
AI can sort through large volumes of alerts and surface relevant evidence quickly. An analyst still has to consider the business context before approving a response. Blocking an account or isolating a system may contain a threat, but it can also interrupt legitimate work.
Analysts need enough context to assess what the system found, why it recommends an action and what that action could affect. Approval rules should specify which actions can proceed automatically and which require review.
Governance Inside the Workflow
Technology issues, management understanding and buy-in, siloed departments, and questions about trust and third-party tools remain adoption challenges. 42% describe their organization’s governance as defined or managed, while 27% describe it as optimized.
A policy written for an experiment may not be sufficient once AI is embedded in alert triage, investigation and response. Teams need clear ownership, approval boundaries and records of the actions AI takes. A record of each action lets leaders review performance and decide whether to adjust the system’s authority.
AI adoption draws funding from across the business, and its actions may touch systems and processes owned by other teams. Security leaders need agreement on who sets the limits, who reviews exceptions and who is accountable when an automated action affects business operations.
Security Leaders Measuring Value
Organizations are evaluating AI through security and operational outcomes, including faster detection and response, reduced investigative workload, improved analyst productivity and higher-quality detections. Cost reduction and tool consolidation rank lower.
Leaders are looking for more capacity to handle threats and investigations. To judge whether AI is delivering, teams need baselines for response times, investigation workload and detection quality. They also need to track where analysts spend the time returned to them.
A system that processes more alerts has not necessarily improved security. Leaders need to know whether the team is identifying threats earlier, making better decisions and resolving incidents with less wasted effort.
Analysts’ Roles are Changing
35% of organizations are retraining analysts to focus on investigation quality, decision-making and threat interpretation. 33% report growing demand for skills in AI governance, validation and oversight. 31% are hiring specialists as traditional cybersecurity roles evolve.
AI can take on repetitive analysis, giving experienced staff more room to examine complex cases. Routine alert work has also been a training ground for junior analysts. Security leaders will need to preserve ways for newer employees to learn how to interpret evidence, recognize patterns and build sound judgment.
Checking system findings, supervising workflows and challenging recommendations are becoming part of the analyst’s work. Analysts need the authority to question a result and enough experience to explain why.
Extending Security to AI Agents
As agents move from assistance into action, security teams will need to know what each one was asked to do, which systems it touched and whether its behavior still fits the task. I see that as one of the defining changes ahead for the SOC. Human oversight can only work when analysts have enough visibility to recognize when an agent’s actions have changed and enough context to judge the risk.
For the industry, that sets a higher bar for security vendors. They need to connect agent identity and behavior with evidence from across the environment, then give analysts a clear way to investigate and intervene. Agent and Entity Behavior Analytics can help provide that view. The SOC’s authority will depend on its ability to account for what its agents do, especially when their actions depart from expectations.
Read Securonix’s “The Evolution of Cybersecurity Automation” Research Report.
