How should an audit firm calculate ROI from AI?
An audit firm should calculate AI ROI by comparing the full cost of the current workflow with the cost and value of the AI-assisted workflow across a representative engagement portfolio.
Include four value pools:
- Preparation time: hours removed from evidence handling, documentation and testing.
- Review and rework: fewer hours spent correcting inconsistent or weak first drafts.
- Downstream audit effort: more targeted substantive work or control reliance where appropriate.
- Client and commercial value: better reporting, additional services, capacity growth or stronger margins.
Then include the real costs: software, implementation, methodology configuration, training, review during rollout, integration and ongoing governance.
Model the result by engagement type. A simple private-company audit and a complex multi-system audit will not create the same saving. Use conservative assumptions and validate them with live-file data.
The most credible ROI model shows the mechanism, not only the multiple. For example: process work takes fewer preparer hours, needs less senior correction and supports a more targeted audit response. That gives a managing partner something they can test against the firm's own economics.
Platformed capability: Platformed can be evaluated at workflow level: evidence collection, preparation, review, follow-up and downstream impact. Use representative live-file data and the firm's own rates; Platformed should not substitute a generic vendor percentage for the firm's economics.
References: Platformed customer examples · Platformed financial audit