P1
Finance Operating Model
LegacyAutonomous
- Legacy
- The close, reconciliations, and FP&A run on spreadsheets and manual keying with no AI.
- Autonomous
- AI runs the routine close and forecast end to end, with finance steering exceptions.
AIR FOR FINANCE
Your Close, Your Forecast, Your Controls Now Run on AI Whether You Govern It or Not
AIR scores how deliberately your finance team has built AI into the close, forecasting, controls, and reporting, and how defensible that stays under audit.
AI is already drafting variance commentary, board decks, and forecasts inside finance teams, and an ungoverned model touching the general ledger is a control gap your auditors will eventually name.
What AIR measures
Five pillars, read for Finance.
The same five pillars of AI readiness, framed in the work, systems, and stakes that CFOs and finance leaders actually face.
P1Finance Operating Model
How systematically AI is embedded in the close, reconciliations, FP&A, and reporting cadence rather than living in one analyst's spreadsheet.
P2Planning & Controls Model
How AI changes what finance produces, from faster close and richer variance analysis to forward-looking forecasts and tighter controls.
P3Finance Talent & Capability
How broadly AI fluency runs across FP&A, controllership, and treasury, with roles redefined and ownership beyond a single power user.
P4Governance, Audit & Risk
The finance team's AI policy, data protection over financial records, QC of AI output, and alignment with SOX and audit expectations.
P5Finance Tool Standardization
A deliberate, owned AI stack for finance with controlled access to ledger and forecast data and visible, defensible spend.
The AIR rating
Six tiers, Legacy to Autonomous.
AIR places Finance on a six-tier readiness ladder from 0 to 100, overall and for every pillar. The climb runs from digital but not intelligent, to a compounding, AI-native edge.
6
Autonomous
85–100AI-native advantage. Compounding intelligence and speed, a durable edge competitors can't copy fast.
5
Integrated
68–84Woven through the business. AI shapes the operating model, pricing, and talent, and ROI is proven.
4
Operational
51–67AI in the core, governed. Embedded at named steps with SOPs, policy, and measured gains.
3
Adopting
34–50Pockets, not a system. Real use in places, uneven and undocumented.
2
Reactive
17–33Experimenting at the edges. Scattered pilots that live in a few people's heads, ungoverned.
1
Legacy
0–16Digital, not intelligent. AI is absent or anecdotal, work is hour-priced, the stack sprawls, and no policy exists.
The point
One score tells you that you are behind; five tiers tell you exactly where to start.
The deep diagnostic
Every pillar, climbed for Finance.
The matrix is a 5-by-6 grid: your five pillars of AI readiness scored against the same six tiers, from Legacy to Autonomous. A single overall score tells you roughly where you sit; it hides where you are dangerously behind and where you are quietly ahead. Reading a tier per pillar turns one vague number into five specific, fixable verdicts, so you act on the truth instead of an average.
P2
Planning, Reporting & Controls
LegacyAutonomous
- Legacy
- Planning, reporting, and controls produce backward-looking outputs at a fixed, slow cadence.
- Autonomous
- Finance runs always-on planning and self-monitoring controls that compound the firm's decision speed.
P3
Finance Talent & Capability
LegacyAutonomous
- Legacy
- No one in finance has working AI skills and the topic is absent from roles.
- Autonomous
- The whole function is AI-native, continuously upskilling, and treats fluency as table stakes.
P4
Finance Governance & Risk
LegacyAutonomous
- Legacy
- No AI policy exists and any use would sit outside SOX controls and data rules.
- Autonomous
- Governance is automated and self-monitoring, turning AI control rigor into an audit advantage.
P5
Finance Tool Standardization
LegacyAutonomous
- Legacy
- There is no AI tooling in finance beyond the ERP and spreadsheets.
- Autonomous
- The owned, integrated stack is a defensible asset that compounds finance's advantage.
Governance and compliance
Where the rules bite.
How Finance's regulatory reality maps onto AIR readiness. Each row is a control your governance pillar has to carry.
| Regime | Pillar | What AI readiness requires |
|---|---|---|
| Sarbanes-Oxley (SOX) Section 404 | P4 | AI used in financial reporting falls within ICFR scope and needs documented, tested controls over its output. |
| Segregation of Duties | P4 | AI agents acting in close or payments must not collapse separation between preparer and reviewer roles. |
| Audit Trail and Evidence Standards (PCAOB) | P2 | AI-generated journal entries, accruals, and commentary need traceable inputs and human sign-off for audit evidence. |
| US GAAP / IFRS Reporting Integrity | P2 | AI-assisted estimates and disclosures must reconcile to source data and reflect approved accounting policy. |
| Data Protection for Financial Records (GLBA / GDPR where applicable) | P5 | Ledger, payroll, and customer financial data sent to AI tools requires controlled, lawful data handling. |
| Records Retention and Model Documentation | P1 | AI models and prompts that influence reported numbers should be versioned and retained alongside working papers. |
Illustrative mapping for AI-readiness planning, not legal, audit, or accounting advice; validate against current SOX, GAAP, and data-protection requirements with qualified counsel and your external auditor.
The stakes
What stalling looks like.
Unverified numbers reach the board
An AI-drafted forecast or variance narrative carries a confident but wrong figure into a board deck. Without a reconciliation step, the error is found after the decision, not before it.
Ledger data leaks into public models
An analyst pastes the trial balance or unpublished results into a consumer AI tool to speed up commentary. Material non-public financial data now sits outside your control and outside your retention policy.
Broken audit trail
AI proposes journal entries or accrual estimates with no record of the inputs, prompt, or reviewer. When auditors ask how a number was derived, finance cannot reproduce or evidence it.
Segregation of duties quietly erodes
An AI agent both prepares and approves entries or initiates and reconciles payments. A control that auditors rely on is bypassed without anyone redesigning the process.
Forecast model drift goes unnoticed
An AI forecasting model trained on old conditions keeps producing plausible numbers as the business shifts. Nobody owns monitoring its accuracy, so confidence outlives correctness.
Start now
Signature quick wins for Finance.
Concrete first moves you can make before the full diagnostic, one per pillar where it matters most.
P4Days
Publish a finance AI policy
Write a one-page rule on what financial data can go into which AI tools, and require human sign-off before any AI output touches the ledger or a filing.
P5Weeks
Approve a finance AI tool list
Name the two or three AI tools finance may use, route ledger and forecast access through controlled connectors, and shut off shadow consumer tools.
P2Weeks
Automate first-draft variance commentary
Pilot AI that drafts month-end variance narratives from the actuals-versus-budget data, with the controller editing and approving before distribution.
P1Days
Log AI use in the close checklist
Add a column to the close calendar marking which steps used AI, capturing the prompt and reviewer so the work is reproducible and audit-ready.
P3Days
Run an FP&A AI fluency session
Train the FP&A and controllership team on safe prompting, hallucination checks, and reconciliation discipline so fluency is not stuck with one power user.
P4A quarter
Map AI touchpoints to SOX controls
List where AI now touches financial reporting and confirm each point has a tested control, owner, and segregation of duties before the next audit.
Find out where your team stands.
The old transformation is finished. The new one is scored.