The 48-Hour Evidence Rule: Can You Prove Your AI Controls Work?
Can you prove your AI controls work in 48 hours or less?
Governance isn't what you promise in policy, it's what you can prove in 48 hours.
The Situation
You have AI policies. You even have controls. But when was the last time you tested whether those controls are actually producing evidence? If you can't retrieve proof of a control's effectiveness within 48 hours, that control doesn't exist in the eyes of a regulator.
The Exposure
Regulators use 'time to evidence' as a proxy for management oversight. If it takes your team a week to assemble model version logs or training data lineage, you're telling the SEC or OCC that you aren't actually monitoring these systems - you're reconstructing history after the fact. The gap between 'we have that somewhere' and 'here's the report' is where regulatory fines escalate.
The Judgment Call
Don't ask your team if they're compliant, ask them to prove it by Friday. In regulated enterprises, the 5-day turnaround is a thing of the past; AI moves too fast for slow-motion governance. You should implement a 48-hour evidence rule for your highest-risk models. If the evidence isn't immediately retrievable, your lifecycle governance is failing and really you're just hoping nothing goes wrong.
Risk: You'll likely expose technical and logging gaps that require immediate remediation.
Benefit: You'll identify your blind spots internally, allowing you to fix them before they become external liabilities.
This Week’s Action
What to do: Execute a drill: pick one high-profile AI use case and demand the decision log (inputs, outputs, and human approval timestamps) for a specific 24-hour window from last month.
Who to involve: The Business Owner of the AI tool and the CIO (or the head of technical delivery) to ensure joint accountability.
What outcome to achieve: A clean, packaged, timestamped report delivered within 48 hours without any manual data manipulation.
Time required: Time required: 30 minutes (15 min to request, 15 min to review 48 hours later)
Artifact
If your team can't produce these three items in two days, your governance is failing:
The Version Snapshot: A technical record of exactly which model version was live and responding to customers on a specific date and time.
The Human Override Log: Evidence of the last time a human reviewer rejected or modified an AI-generated decision before it was finalized.
The PII Filter Log: Evidence that sensitive data was blocked or redacted before being sent to external AI systems, whether through automated tools or manual review processes.
When the stakes exceed your internal capacity:
AI Exposure Diagnostic: A 2-hour strategic evaluation for risk, compliance, and legal leaders to identify your highest-priority governance gaps and deliver a 90-day remediation roadmap.
12-Week Governance Sprint: Translate regulatory requirements into audit-ready policies, control frameworks, and accountability structures.
Ongoing Advisory Retainer: Embedded judgment for policy updates, vendor assessments, and board prep as regulations and technology evolve.
Reply with "Diagnostic" or “Sprint” to schedule a conversation for next month.
Chris Cook writes Judgment Call weekly for compliance and risk officers navigating AI governance.
Former IBM Vice President and Deputy Chief Auditor. Published in the AI Journal, speaker at Yale.
Chris Cook
Managing Partner & Founder
Blackbox Zero
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