AI Inspector General Audit Response Playbook
A federal agency received a draft OIG report with 7 findings, including 2 material weaknesses in internal controls and 1 finding of improper payments totaling $4.8M. The agency has 30 days to submit its management response before the report is finalized and released publicly.
When to use this playbook
- Use this playbook when the decision looks like the situation above: A federal agency received a draft OIG report with 7 findings, including 2 material weaknesses in internal controls and 1 finding of improper payments totaling $4.8M.
- It is a fit when you have source files in hand and need a structured, reviewable analysis — not a generic chat answer about "Inspector General Audit Response".
- Do not use it as a substitute for licensed, legal, clinical, or authorized official judgment in the domain.
What you'll need
- Draft OIG report (7 findings, full text)
- Supporting documentation for each finding
- OMB A-123 internal control requirements
- IPERA requirements
- Prior year OIG report and management response
Attachments: Documents (Documents)
The Prompt
You are a federal agency CFO developing the management response to an OIG audit report with 7 findings. I am attaching: Work only from the attached source files. If a conclusion is not supported, say so. Produce: 1. Assess each finding: factually accurate, partially accurate, or incorrect — and what documentation supports a challenge? 2. For the 2 material weaknesses, develop the corrective action plan: specific controls, responsible officials, measurable milestones. 3. For the $4.8M improper payments, calculate the correct figure and identify whether IPERA reporting obligations are triggered. 4. Identify which findings should be concurred (accepted) vs. non-concurred (disputed with evidence). 5. Draft the management response opening narrative that frames the agency's commitment to improvement and positions it favorably for Congressional scrutiny. Call out where independent models are likely to disagree, and list follow-up documents a reviewer should request.
What to expect
- Per-finding factual accuracy assessment
- Material weakness corrective action plan
- Improper payment recalculation and IPERA assessment
- Concur/non-concur recommendation
- Management response opening narrative draft
Review before you act
- Validate this output against source files before relying on it: Assess each finding: factually accurate, partially accurate, or incorrect — and what documentation supports a challenge?.
- Validate this output against source files before relying on it: For the 2 material weaknesses, develop the corrective action plan: specific controls, responsible officials, measurable milestones.
- Validate this output against source files before relying on it: For the $4.8M improper payments, calculate the correct figure and identify whether IPERA reporting obligations are triggered.
- Validate this output against source files before relying on it: Identify which findings should be concurred (accepted) vs. non-concurred (disputed with evidence).
- Confirm every cited figure, date, counterparty, or requirement against the attached originals — models compress and can drop a qualifier.
- Treat disagreement between models as a review item, especially on classification, materiality, and recommended next action.
- Do not authorize an operational, clinical, legal, credit, or enforcement action solely because the models agree.
Why compare models on this
For Inspector General Audit Response, running the same attachments across independent models is useful because the hard part is classification and completeness, not fluency. The workflow is already designed to surface per-finding factual accuracy assessment; material weakness corrective action plan; improper payment recalculation and ipera assessment; concur/non-concur recommendation. Those are comparison artifacts — they only exist if more than one model runs. Models disagree on exemption applicability, IG finding risk, and how aggressive a budget narrative can be. Those disagreements belong with counsel and the authorizing official.
See governed multi-model AI on your own prompt
Compare GPT-5, Claude, and Gemini side by side, with human review and a decision record built in.

