Run a peak-load simulation against those conditions | AIGP
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Run a peak-load simulation against those conditions: Which evidence resolves the capacity uncertainty?

AIGP Understanding How to Govern AI Deployment and Use Hard

A peak-load simulation tests whether human review remains available under the stated workload constraints.

The question

An EU customer-service deployment routes 40% of cases to human review during peak periods. Unresolved cases may affect vulnerable customers. Under the organization’s internal approval process, applicable EU AI Act obligations must be met. Approval requires evidence covering local peak volume, handling time, queue growth, and reviewers’ authority to intervene. Which evidence resolves the capacity uncertainty?

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  1. Run a peak-load simulation against those conditions. ✓
    A realistic simulation tests volume, handling time, backlog growth, and whether reviewers can intervene when required.
  2. Accept the vendor’s referral forecast after a desktop review.
    A supplier forecast may omit local demand, interruptions, handling time, and backlog effects.
  3. Check average reviewer satisfaction.
    Satisfaction does not establish whether reviewers can process peak referrals within required response conditions.
  4. Pilot normal demand, then extrapolate staffing capacity to peak periods.
    Normal-demand results cannot establish queue behavior or timely intervention during the stated peak risk.
The trap
Capacity is an oversight control: test realistic demand, processing time, backlog, and intervention requirements.

How to remember it

A peak-load simulation tests whether human review remains available under the stated workload constraints.

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