Does AI improve audit quality or only efficiency?
AI can improve both quality and efficiency, but quality gains only appear when the workflow is designed around evidence, methodology and review. Faster weak work is still weak work.
Quality can improve through:
- more consistent execution across teams;
- broader review of available evidence;
- clearer links between evidence and conclusions;
- earlier identification of missing or contradictory information;
- stronger process and system understanding;
- more reviewer time focused on judgement rather than file cleanup.
Efficiency comes from removing manual preparation, repeated evidence handling and duplicated documentation. The two benefits reinforce each other when the system produces better-prepared work before review.
There are also risks: overreliance, hidden assumptions, automation bias and confident unsupported output. That is why firms need controlled use cases, validation and visible auditor approval.
Platformed's position is that audit AI should raise the standard of the work while reducing the manual cost of producing it. If a product can only demonstrate speed, it is solving too small a part of the audit problem.
References: FRC generative and agentic AI guidance · Platformed customer examples