AI in security operations: what does the governance gap look like?

TL;DR: The central theme being alert overload, complexity and the need to use AI practically rather than as hype in Stellar Cyber’s RSAC 2026 podcast features Sumitomo Chemical CISO Erwin Eimers on how AI is reshaping security operations, according to Stellar Cyber. The governance issue is no longer whether AI can assist the SOC, but how teams control its scope, workflow fit and decision quality.

Editorial analysis by NHI Mgmt Group, based on content published by Stellar Cyber: “Sumitomo Chemical On AI, Working With Stellar Cyber, & More. Erwin Eimers, America CISO.”.

Key questions

Q: How should security teams use AI in the SOC without losing human control?

A: Use AI to remove repetitive work, enrich alerts, and accelerate triage, but keep humans accountable for escalation, containment, and exception handling.

Q: When does alert overload become a governance problem rather than a tooling problem?

A: Alert overload becomes a governance problem when teams cannot separate signal from noise fast enough to contain active risk.

Q: What should organisations do first before giving AI more SOC authority?

A: Start by mapping the identities, permissions and approval paths behind the AI workflow.

Practitioner guidance

• Define AI-assisted SOC decision boundaries Separate summarisation, recommendation and execution so that each workflow has a clearly bounded authority level and documented human review point.
• Inventory every identity used by security automation Track analyst accounts, service accounts, API tokens and any agent identities that can enrich cases or trigger response actions.
• Measure decision quality, not just alert volume Review false positives, false negatives, escalation accuracy and the proportion of cases where the model rationale is preserved for audit.

Bottom line: AI is being used to scale security operations, but the real question is whether it improves governance quality or simply accelerates existing weaknesses.

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