The First Week Check: What IT Managers Should Validate When Using AI in the SOC

As AI becomes embedded in security operations, many IT and security managers are starting the year with AI already active in their SOC workflows. That’s a positive step — but it also changes what “operational hygiene” looks like.

AI doesn’t fail loudly when something is wrong. It fails quietly. That’s why the first week of the year is an ideal time to validate how AI is actually behaving inside the SOC — not in theory, but in daily operations.

This isn’t about tuning models or adding new capabilities. It’s about confirming that AI is operating within expected boundaries, under human oversight, and delivering the outcomes it was introduced to achieve.

1. Confirm Where AI Is Actually Making Decisions

• Prioritizing alerts

• Enriching incidents with context

• Assisting triage decisions
• Suggesting response actions

• Which SOC workflows rely on AI recommendations?
• Where does human approval remain mandatory?
• Are those boundaries documented and understood?

2. Review Alert Volume and Prioritization Shifts

AI often changes alert dynamics gradually. Over time, teams may see fewer alerts surface or see different alerts rise to the top.

During the first week, review:

• Changes in alert volume compared to pre-AI baselines
• Shifts in alert priority distribution
• Any categories that appear over- or under-represented
  
  

The goal isn’t to reverse changes, but to ensure they are intentional and explainable. Reduced noise is good. Reduced visibility is not.

3. Validate Analyst Trust and Usage

AI effectiveness depends on analyst interaction. If analysts don’t trust AI outputs, they’ll bypass them. If they trust them blindly, risk increases.

Early in the year, check:

• Are analysts reviewing AI-driven classifications?
• Are AI recommendations being overridden — and why?
• Is feedback being captured and fed back into workflows?
  
  

Healthy AI usage shows engagement, not avoidance or unquestioned acceptance. Human oversight is a feature, not a failure.

4. Check for Drift After Environmental Change

The start of the year often brings change:

• New users
• New applications
• New business workflows
• Infrastructure updates
  
  

AI models trained on last year’s patterns may misinterpret these changes if not monitored. Review whether:

• AI confidence scores have shifted unexpectedly
• Certain behaviors are being flagged more frequently
• False positives are clustering around new activity

This isn’t a reason to disable AI — it’s a reason to observe and recalibrate where needed.

5. Confirm Visibility and Auditability

IT managers are accountable for outcomes, audits, and incident explanations. That doesn’t change when AI is involved.

During the first week, validate:

• Can you explain why an alert was prioritized?
• Can you trace AI-influenced decisions during an incident?
• Do you have visibility into AI-driven workflows?

If AI outputs can’t be explained to leadership or auditors, governance gaps exist — regardless of detection performance.

6. Align AI Behavior With SOC Objectives

Finally, step back and ask a simple question:

Is AI helping the SOC achieve its goals?  Those goals usually include:

• Reduced alert fatigue

• Faster triage
• Clearer prioritization
• Better analyst focus

That’s where managed SOC oversight, tuning, and orchestration matter most.