Direct answer
Place generated analysis and agent actions inside existing access, change, review, reconciliation, and retention controls.
1. Inventory
Apply this stage to AI for CFOs by naming the executive owner, affected workflow, current evidence, unresolved questions, and the artifact that must exist before the review advances.
Decision test: Planning and scenario analysis
AI can help finance teams interrogate governed planning data, draft scenario narratives, and expose assumption changes. The CFO still owns the scenario design, baseline, probability treatment, and decision made from it.
- Which planning model and dimensions ground the answer?
- Can every assumption be traced to an owner and date?
- How are generated scenarios kept out of the approved plan until review?
Failure modes to test: fabricated drivers; silent use of stale actuals; false precision in scenario probabilities.
2. Risk and assertion mapping
Apply this stage to AI for CFOs by naming the executive owner, affected workflow, current evidence, unresolved questions, and the artifact that must exist before the review advances.
Decision test: Close, reconciliation, and variance investigation
AI can organize exceptions, explain candidate variances, and help a controller navigate supporting records. It should not post, certify, or clear an exception without the existing accounting policy, evidence, and approval chain.
- What evidence links a suggestion to the subledger and general ledger?
- Who can accept a proposed match or explanation?
- Are access and journal-entry rights segregated from the assistant?
Failure modes to test: incorrect matches; unreviewed journal proposals; loss of audit trail.
3. Preventive controls
Apply this stage to AI for CFOs by naming the executive owner, affected workflow, current evidence, unresolved questions, and the artifact that must exist before the review advances.
Decision test: Cash visibility and liquidity decisions
AI can summarize bank, receivables, payables, and forecast signals when those feeds are timely and reconciled. Treasury decisions still require authorized positions, counterparty limits, and named human approval.
- What is the freshness and completeness of each cash source?
- How are restricted cash and intercompany balances treated?
- Can the system initiate a payment or only recommend an action?
Failure modes to test: stale balances; missed restrictions; excessive transactional authority.
4. Detective controls
Apply this stage to AI for CFOs by naming the executive owner, affected workflow, current evidence, unresolved questions, and the artifact that must exist before the review advances.
Decision test: Working-capital exception management
AI can prioritize collection, payment, inventory, and dispute exceptions for review. A defensible workflow preserves customer and supplier context, contractual terms, cash policy, and the difference between predicted behavior and an approved action.
- Which policies constrain recommendations?
- How are relationship and dispute facts represented?
- What outcome is measured after a recommendation is accepted?
Failure modes to test: harmful customer treatment; supplier disruption; optimization against the wrong cash metric.
5. Evidence and testing
Apply this stage to AI for CFOs by naming the executive owner, affected workflow, current evidence, unresolved questions, and the artifact that must exist before the review advances.
Decision test: Spend intelligence and procurement challenge
AI can normalize spend descriptions, surface anomalies, and prepare questions for procurement. The CFO should require category definitions, coverage, confidence, contract context, and a realization method before treating an opportunity estimate as savings.
- What proportion of spend was classified and at what confidence?
- Does the opportunity reflect contract and demand constraints?
- How will negotiated value be reconciled to the P&L or cash result?
Failure modes to test: double-counted opportunities; misclassified spend; booked savings without realization evidence.
Evidence packet to retain
Apply this guide as a record of judgment, not as a disposable checklist. Keep the scope, current baseline, representative scenario, participating people, source materials, decision rights, observed exceptions, outcome measures, unresolved claims, and the date on which the conclusion must be reviewed again.
- Planning and scenario analysis: AI can help finance teams interrogate governed planning data, draft scenario narratives, and expose assumption changes. The CFO still owns the scenario design, baseline, probability treatment, and decision made from it.
- Close, reconciliation, and variance investigation: AI can organize exceptions, explain candidate variances, and help a controller navigate supporting records. It should not post, certify, or clear an exception without the existing accounting policy, evidence, and approval chain.
- Cash visibility and liquidity decisions: AI can summarize bank, receivables, payables, and forecast signals when those feeds are timely and reconciled. Treasury decisions still require authorized positions, counterparty limits, and named human approval.
- Working-capital exception management: AI can prioritize collection, payment, inventory, and dispute exceptions for review. A defensible workflow preserves customer and supplier context, contractual terms, cash policy, and the difference between predicted behavior and an approved action.
The final packet should distinguish what an official source establishes, what was observed during evaluation, what a provider or participant reported, what the reviewing team inferred, and what remains unknown. That separation is essential when the result will influence an executive, employee, customer, investor, or regulated decision.
Evaluation worksheet
| Question | Required record | Approval condition |
|---|---|---|
| What changes? | Current and proposed workflow | Boundary and owner are explicit |
| What supports the output? | Source, rights, lineage, quality, and version | Material inputs are traceable |
| Who decides? | Review, approval, exception, and escalation rights | A real person has time and authority |
| What would prove value? | Baseline, population, period, measure, and exclusions | Activity is not substituted for outcome |
| When do we stop? | Thresholds, incidents, change triggers, and fallback | Exit is practical and controlled |
Final approval gate
Approve only when the role-specific decision is clear, the evidence supports the conclusion at the claimed level, material unknowns remain visible, ownership conflicts are disclosed, and the implementation can be monitored and reversed. Reject a universal winner conclusion when the evidence supports only conditional fit.
The publication supports research and executive decision preparation. It does not provide legal, financial, accounting, employment, clinical, cybersecurity, investment, procurement, or implementation advice.