The enterprise version is not a bigger questionnaire. It is a cross-function operating read that survives board, risk, and audit review.
An enterprise AI Audit gives finance leaders one operating read across vendor AI tools, embedded SaaS AI, internal agents, Shadow AI, usage depth, spend waste, value evidence, risk exposure, workforce fluency, and framework-mapped evidence gaps.
Enterprise audits need cross-function coverage.
The audit has to cross IT, security, finance, risk, compliance, operations, product, and business teams. Each group sees a different part of the AI estate.
CIO: inventory, usage, tooling, spend, workflow integration.
CISO: Shadow AI, policy exceptions, data exposure, incident readiness.
CFO: cost per outcome, duplicate spend, utilization, value evidence.
Board: value, risk, material findings, and funded next moves.
The evidence must point to live systems.
Enterprise AI changes through tools, prompts, models, integrations, and user behavior. Static surveys age quickly. The audit needs source pointers and repeatable evidence.
System inventory with owner and scope.
Usage and workflow evidence by role.
Eval coverage and baseline status for internal agents.
Exception log, remediation owner, and review cadence.
The output should force a sequence.
The value of an enterprise AI Audit is a decision surface. The audit should make it obvious whether the next move is transformation, governance, fluency, consolidation, or a narrower follow-up.
Expand high-value workflows with enough evidence to scale.
Fix material exposure before more AI reaches regulated work.
Train roles where usage is high but outcomes are weak.
AI Audit questions, answered plainly.
Questions buyers actually ask.
Enterprise-grade means it covers the full AI estate, ties findings to owners and materiality, and produces evidence that leadership, risk, compliance, and audit teams can review.
Yes. That is usually the point. The audit shows which governance gaps are material and which operating gaps should be fixed first.
The board gets a concise read on AI value, AI risk, Shadow AI, evidence gaps, and the next funded workstream.
Keep the audit path moving.
AI Trust for Finance
Read the finance-specific trust scope.
12 Levers
Map enterprise findings to the operating model.
Services
See how the Audit sequences into TrustEvals services.
Turn the AI read into a decision.
Bring one workflow, vendor, or AI portfolio. We will map the evidence needed for finance leaders to fund, ship, or stop it.