Quality control when volume increases

AI accelerates production — proposals, content, code, reports — faster than review processes adapt. Quality slips show up as client revisions, returns, support tickets, reputation damage. Volume without QC is anti-adaptive.

Define quality tiers. Tier A outputs (client-facing, financial, regulatory) require checklist review and named approver. Tier B (internal drafts) allow lighter sampling. Tier C (exploratory) can move fast with clear 'not approved' labeling.

Build checklists from past failures — the top ten errors that reached clients. AI can pre-screen for missing sections, inconsistent numbers, off-brand language; humans verify judgment calls.

Track defect rate per workflow post-adaptation. If defects rise while speed improves, rebalance automation versus review — don't celebrate throughput alone.

QC is cultural. Praise catches, not only speed records. Teams under pressure to 'use AI more' will skip review unless leadership measures quality explicitly. Adaptation scales when customers can't tell you rushed — because you didn't.