The Story: Two Audit Seasons, One Difference
Last year, your team burned weeks assembling evidence, reconciling spreadsheets, and explaining “what really happened” to auditors.
Next year, you either repeat that…
Or you walk in with live dashboards, pre-packaged evidence, and a clear story of how AI gives you continuous assurance, not last-minute chaos.
The difference isn’t a 5-year roadmap.
It’s what you do in the next 90 days.
Here’s the plan → simple, pointed, and executable.
Phase 1 (Days 1–30): Decide Where AI Actually Works
Objective: Focus. Stop talking about “AI in GRC” in general and pick a few battles to win.
Pick 2–3 painful workflows
Examples: evidence collection for SOC 2/ISO, access reviews, policy–regulation mapping.
For each, write down:
Hours/month spent
Number of people involved
Typical delays and failure points
Define what “better” means:
Time cut in half, fewer escalations, cleaner evidence trail, fewer repeat findings.
You’re not transforming the universe. You’re choosing where AI must earn its keep.
Phase 2 (Days 31–60): Pilot, Measure, Explain
Objective: Prove AI helps and that you can defend how it works.
Plug AI into those workflows to:
Draft comparisons (policy ↔ regulation).
Pull and label evidence from source systems.
Cluster/score risks, incidents, or exceptions.
Draw a hard line between:
AI suggestions vs. human decisions.
Capture before/after metrics:
Cycle time, manual steps removed, issues caught earlier.
Log everything:
Inputs, outputs, overrides, rationale.
Create a one-page “How AI is used in this process” you’d be comfortable showing a regulator.
If you can’t explain it in plain language, it’s not ready.
Phase 3 (Days 61–90): Wire It Into Governance
Objective: Stop treating AI as a side experiment and make it part of your GRC system.
Feed AI outputs into your GRC platform as:
Risks, issues, control test results, evidence objects.
Treat AI findings as first-class evidence:
Track how often they’re confirmed or overridden by humans.
Record why they’re overridden.
Tune based on reality:
Reduce noise where AI over-flags.
Tighten thresholds where it misses obvious issues.
Decide which pattern to scale next:
Once one workflow is stable and explainable, extend the same pattern to others.
Now AI isn’t a toy. It shows up in the same place as everything else you’re accountable for.
What You Do This Week
Name your 2–3 high outcome yield workflows.
Assign one owner for the 90-day AI compliance push.
Schedule a 30-minute check-in with your leadership team in 30 days to show:
Where you’re using AI
How it’s governed and controlled
The concrete risk reduction and efficiency gains
That’s it.
Every control tells a story. Share yours and continue the dialogue with me on LinkedIn.
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