Topic starter
02/08/2026 11:53 am
TL;DR: Legacy SOAR, built on static playbooks and custom scripting, cannot keep pace with machine-speed threats or alert overload, according to torq, which says AI-native SOC automation should replace it with autonomous investigation, adaptive triage, and governance built into the operating model. The shift is not cosmetic: coverage, speed, and auditability now depend on architecture, not more playbooks.
Editorial analysis by NHI Mgmt Group, based on content published by torq: “SOAR is Dead. Here’s What Replaces It in 2026.”.
By the numbers:
- 83% of SOC analysts struggle with alert volume, according to torq.
Key questions
Q: What breaks when a SOAR platform is not built for modern SOC work?
A: Traditional SOAR breaks when it is asked to automate judgment-heavy security work that depends on context, uncertainty, and changing inputs.
Q: Why do AI-native SOC platforms change the risk model for automation?
A: They move decision-making from predefined scripts to runtime reasoning.
Q: What are the signs that a SOC automation programme is not working well?
A: A SOC automation programme is struggling when analysts still spend most of their time on repetitive triage, alerts remain noisy and unprioritized, and response steps vary by person or shift.
Practitioner guidance
- Map alert coverage against real workload Measure how much of your Tier 1 queue is actually investigated, not just routed, and identify where static playbooks still leave gaps in coverage and response speed.
- Test runtime governance before expanding autonomy Validate approval gates, scope restrictions, and immutable audit trails on high-impact actions before allowing automated containment or remediation in production.
- Reduce engineer dependency in workflow ownership Document which automations depend on individual scripting knowledge, then redesign the most fragile workflows so analysts can maintain them without specialist intervention.
Bottom line: Legacy SOAR breaks down because static playbooks and hand-built integrations cannot keep pace with modern alert volume and threat variation.
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02/08/2026 1:01 pm
Static playbook automation has reached its governance limit: the core failure is not a lack of effort, but a design assumption that every meaningful scenario can be anticipated and scripted. That assumption breaks in environments where threats evolve faster than the playbook lifecycle, and the result is coverage that looks automated while remaining structurally incomplete. Practitioners should judge SOC automation by how it handles the unexpected, not by how many workflows have been written.
A few things that frame the scale:
- 67% of organisations still rely heavily on static credentials despite the risks they pose to agentic AI deployments, according to the 2026 Infrastructure Identity Survey.
- Only 13% of organisations feel extremely prepared for the reality of agentic AI despite the majority racing toward autonomous adoption, according to the 2026 Infrastructure Identity Survey.
A question worth separating out:
Q: How should security teams govern autonomous SOC actions without losing control?
A: Security teams should set explicit approval boundaries for every autonomous action, then require logging, rollback, and ownership for each one. The key is to separate recommendation from execution so that automated classification does not quietly become automated remediation. Treat the SOC platform as a privileged non-human identity, not just a tool.
👉 Read our full editorial: Legacy SOAR is giving way to AI-native SOC automation