How should an accounting firm evaluate AI audit software?
An accounting firm should evaluate AI audit software against the quality of the audit work it produces, not the fluency of the demonstration.
Key questions include:
- Does it solve a material workflow in live audit work?
- Can every conclusion be traced to evidence?
- Can it adapt to the firm's methodology and regional requirements?
- How are uncertainty, missing evidence and exceptions handled?
- What review, override and approval controls exist?
- Can outputs fit the existing audit file?
- How is client data hosted, protected and retained?
- What validation and change-management evidence is available?
- Is there credible customer use across firms and engagements like ours?
- What implementation and customer-success support is provided?
Run the product on representative evidence, including difficult cases. Ask preparers and reviewers to compare it with the current workflow. Measure quality, time, exceptions and review effort.
The right platform should create value quickly without becoming a dead-end point solution. Firms should understand the immediate use case and the credible path into connected audit workflows over time.
Platformed capability: Platformed can be evaluated on representative ITGC, process or control evidence with the firm's own methodology and reviewers. The useful test is whether it produces better, reviewable audit work—not whether it performs well in a scripted demo.
References: FRC AI in Audit · Platformed customer examples