What Goes Around Comes Around: KPMG’s AI-Driven Fee Argument Raises Uncomfortable Questions About Audit Pricing Models

KPMG’s recent request for lower audit fees has ignited debate across the risk, audit and compliance landscape. In discussions with its external auditor, Grant Thornton UK, KPMG reportedly argued that the rollout of AI would make elements of accounting and audit work cheaper to deliver – and that the auditor’s pricing should reflect this shift.

On the surface, the logic is straightforward: automation reduces effort, effort drives cost, and fees should fall. But the implications could trigger a fundamental change in the way audit processes have been conducted for decades. This is not just a conversation about efficiency – it is an early signal of a pricing inflection point for audit.

Traditionally, audit has been priced as a periodic regulatory requirement, anchored to hours, seniority and review depth. AI challenges this model. If aspects of audit execution become faster or more automated, firms face a choice: defend existing fees by arguing that human oversight still dominates cost, or rethink audit pricing altogether.

This divergence is seen in responses to the KPMG case. One camp believes fees should remain largely unchanged. Human auditors are still required to verify, validate and ultimately stand behind AI-generated outputs. AI may reduce the friction of starting from a blank canvas, but judgment, challenge and final sign-off remain manual. Governance gaps reinforce this caution: our 2025 global corporate survey highlights that only 56% of organizations have implemented a comprehensive AI governance policy, limiting how far automation can safely replace human assurance.

The opposing view is more disruptive. Some risk practitioners argue that AI does not weaken audit’s value proposition – rather, it enhances it. By embedding AI directly into compliance cycles, firms could move toward a subscription-based Audit as a Service (AAAS) model. Continuous monitoring would replace point-in-time reviews, delivering ongoing insights into control effectiveness, early risk signals and non-compliance exposure. In this model, AI supports continuous assurance, not cheaper assurance – making the case for repriced, potentially higher-value audit offerings.

KPMG’s position could be highly consequential. If it uses AI to justify lower fees with its own external auditor now, the same logic will inevitably be applied by KPMG’s own clients. Whether this represents cost discipline or a strategic misstep remains to be seen. What is clear, regardless, is that AI is forcing a rethink of pricing models in risk management services. Firms should consider the implications of trade-offs in audit integrity that may increasingly be normalized in the pursuit of efficiency – a key trend to watch, outlined in our 10 predictions for 2026 report.