AI SOAR

Expanded Definition

AI SOAR refers to security orchestration and response capabilities that use AI to support triage, investigation, prioritisation, or remediation. The important distinction is not whether automation exists, but whether AI is only accelerating fixed playbooks or is influencing decisions about which action to take next.

In security operations, that distinction matters because conventional SOAR executes predefined logic, while AI SOAR may score alerts, summarise evidence, recommend response steps, or adapt routing based on context. Definitions vary across vendors, and no single standard governs this yet, so the term should be read as a capability label rather than a formal product class. NIST positions orchestration and response within broader security governance under the NIST Cybersecurity Framework 2.0, but it does not separately codify AI SOAR as a control category.

The most common misapplication is calling any rule-based automation “AI SOAR,” which occurs when an organisation uses pre-scripted response logic and adds a simple chatbot or classifier without changing the decision process.

Examples and Use Cases

Implementing AI SOAR rigorously often introduces governance and validation overhead, requiring organisations to weigh faster containment against the risk of opaque or incorrect automated action.

• Alert triage in a SOC, where AI groups duplicate events, ranks likely incidents, and prepares analyst summaries before a case is opened.
• Phishing response, where the system correlates mailbox telemetry, URL reputation, and user reports to decide whether to isolate a message, block a sender, or escalate.
• Identity-related containment, where suspicious login patterns trigger automated session revocation or step-up checks, aligning with identity controls discussed in the NIST Cybersecurity Framework 2.0.
• Cloud incident handling, where AI helps map alerts across SIEM, EDR, and CNAPP signals so analysts can reduce investigation time without manually stitching together evidence.
• Change-aware response, where the platform adjusts playbook execution if active remediation would interfere with a critical business service or an ongoing forensic hold.

Why It Matters for Security Teams

AI SOAR matters because response speed alone is not a security outcome if the underlying actions are wrong, unreviewable, or out of policy. For security teams, the governance question is whether AI is limited to recommendation support or is being allowed to initiate containment, modify cases, or trigger downstream automation with real operational impact.

That distinction becomes especially important in environments with privileged access, human approvals, or shared service accounts, where a mistaken automated action can lock out responders, disrupt production, or erase evidence. Teams should also consider how AI-generated recommendations are logged, explained, and overridden, particularly when incident handling must be auditable under frameworks such as the NIST Cybersecurity Framework 2.0. In practice, AI SOAR is useful when it reduces operator burden without hiding the basis for response decisions.

Organisations typically encounter the limits of AI SOAR only after an automated containment action blocks a legitimate service or a flawed recommendation delays escalation, at which point response governance becomes operationally unavoidable.

Related resources from NHI Mgmt Group

• What should security teams do before replacing SOAR with agentic AI?
• Why do AI SOC agents complicate identity governance more than traditional SOAR?
• What do security teams get wrong about SOAR versus AI SOC?
• What is the difference between agentic AI and SOAR in a SOC?