The promise of agentic AI in the security operations center (SOC) is obvious.
Faster investigations, systems that can act on their own and the ability to keep pace with threats that no longer arrive neatly packaged.
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Field CTO and Strategic Advisor at Splunk.
The idea of AI tools making decisions can sound abstract, but the shift it represents is not. Moving from automation to agentic AI changes how work gets done, how responsibility is shared and how much control leaders are willing to hand over.
The security industry has been here before. Only a few years ago, many SOC teams were still cautious about automation software. Concerns about visibility and accountability slowed adoption, even when the benefits were clear.
Large language models changed that dynamic by showing how adaptable AI could be, but they also introduced a new kind of uncertainty. Unlike scripted workflows, these systems interpret context and make judgment calls along the way.
Agentic AI takes that a step further, operating for extended periods and shaping investigations as they unfold. That shift creates real opportunity, but it also forces security leaders to rethink what trust looks like when decisions are no longer made entirely by people.
When automation gives way to judgement
In traditional SOC environments, decisions followed a defined path. Automation earned its place in the SOC by staying within clear boundaries handling specific tasks and behaving in ways teams could anticipate.
When something went wrong, the cause was usually clear: a rule misfired, a configuration needed adjusting, or a data source was missing.
Agentic AI changes that decision structure. These systems work with incomplete information and shifting context. They can run investigations over longer periods, pull together signals and decide what deserves attention next. That flexibility is what makes them useful, but it also changes how people relate to the technology.
For security leaders, this is more than a technical upgrade. It changes the nature of the decision they are being asked to make.
Approving agentic AI means delegating judgement, which requires a different kind of confidence in how decisions are made. That distinction is subtle in how systems are governed and in how comfortable leaders feel relying on them.
Who answers when AI makes a call
In leadership discussions about agentic AI, the tone often shifts. In security operations, incidents may involve multiple teams and processes, but responsibility ultimately sits with named leaders. That does not change when AI systems are introduced.
When systems act independently, responsibility does not disappear along with human involvement. An AI does not explain its reasoning to a board or provide reassurance to a regulator. Those conversations are still with the organization and in most cases, with the CISO.
This reality is what reshapes leadership conversations about agentic AI. Early excitement gives way to a more cautious line of questioning. The focus moves away from what the technology can do and towards what happens when something goes wrong.
This makes autonomy harder to treat as a purely technical decision. Leaders need to be clear about who owns these systems, how much authority they are given and where human judgement is expected to intervene. Those boundaries are most effective when they are set deliberately.
Clarity here changes how autonomy feels. When responsibility is understood, leaders are better placed to rely on systems that act on their behalf.
What helps leaders to trust what they cannot see
When systems operate beyond immediate human oversight, visibility becomes critical. Decisions that appear without context can leave teams uneasy, even when the outcome seems sensible.
Security professionals are used to working with complex systems, but complexity alone is not the issue. What matters is being able to see how conclusions are reached.
This is where observability starts to play a practical role. To give analysts and leaders something to anchor to, we need systems that can show progress, surface interim findings and leave investigation trails.
When work unfolds over hours or days, visibility reduces the sense of risk. Actions feel less opaque when they can be traced as they happen.
The option to interrupt or redirect a system mid-task also changes how autonomy is experienced. Knowing that a human can step in makes oversight feel intentional, rather than reactive. Interfaces are starting to reflect this shift, with AI able to surface its reasoning during investigations instead of delivering a single answer at the end.
Where human judgement still matters most
In any SOC, human expertise has the greatest impact at the point where decisions are made. As agentic AI takes on more repetitive and operational work in the SOC, time spent gathering basic context or working through alert queues begins to fall away.
What replaces it is work that relies more heavily on judgement, such as reviewing decisions and shaping workflows.
This change can feel uncomfortable, particularly for teams who built experience and knowledge through repetition. At the same time, it creates new opportunities. Junior analysts are exposed to higher-level thinking earlier, while senior analysts spend less time firefighting and more time improving decision quality across the SOC.
The result is a redistribution of judgement, rather than a reduction in human involvement. What changes is not the need for people, but their type of workload and where they have the greatest impact. Context, direction and oversight become central as systems take on more execution.
What trust looks like in an AI-enabled SOC
Agentic AI is already influencing how security operations work. For leaders, the challenge has shifted from capability to confidence. The question now is whether these systems can be relied on to act in line with how the organization expects risk to be handled.
Trust grows through familiarity. Seeing how systems behave over time, understanding how decisions are made and knowing where responsibility sits all plays a part. Confidence increases when leaders can follow what is happening and experts can step in when needed.
The SOC is unlikely to become fully autonomous. People and systems will continue to work closely together, with humans retaining responsibility and oversight. The task for security leaders is to create the conditions where that collaboration works smoothly and predictably.
How well they create this collaborate culture will shape how comfortably agentic AI is adopted and how much value it ultimately delivers.
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