Tackling your board's next big question

In last week’s Boardroom Brief, we talked to CFOs who were gleefully eyeing up discounts and better terms with auditors to claim their share of AI efficiencies. But audit firms want to reinvest any savings into improving audit quality. Is this a trade-off CFOs want? And how should CFOs track the impact of AI on audit quality?

This is the second in a three-part series. Next week, we’ll dive into how AI is closing the gap between small and large audit firms and what that means for CFOs.

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Speculation about the impact of AI on the audit market is rife. “The audit industry will be 80% automated soon.” “It could cut the audit workforce in half.” That kind of thing. And let’s not forget that new AI-driven efficiencies should also reduce audit costs.

But let’s take a reality check. The wider context is a stubborn history of inadequate audit quality. In the US, for example, the Public Company Accounting Oversight Board has consistently recorded “unacceptable” rates of audit deficiency (inability to spot misstatements) over the last 15 years.

The picture isn't any prettier globally. The International Forum of Independent Audit Regulators tracks audit quality across more than 50 countries. In 2014, nearly half of all inspected audits had at least one significant deficiency. By 2022, that rate edged down to 26%. It's been climbing back up ever since, reaching 35% in 2025, meaning more than one in three audits failed to meet basic auditing standards.

While audit firms have made improvements over the last two years, deficiency rates remain a massive issue.

“Audit quality has been constrained by resourcing and sampling limitations, but AI removes those constraints. Firms can now assess larger volumes of transactions rather than samples,” said Amy Wang, CFO at procurement platform Procurify. “AI is a genuine opportunity to improve deficiency rates. The focus should be on making those quality improvements tangible and transparent. Fee reductions may be a byproduct.”

That’s the lens CFOs should use to evaluate AI's arrival in the audit space: It should first be about raising standards, and only then about reducing fees.

The Big Four audit firms alone are investing billions in AI to improve both efficiency and quality.

EY, for example, is not just layering AI on old processes. It’s fundamentally redefining its service through a $1 billion investment in technology and people. This includes rolling out a multi-agent framework that orchestrates tasks across 160,000 engagements.

Richard Jackson, EY Global and Americas Assurance AI leader, said the main aim is to automate routine work like reconciliations, tie-outs, and data matching. This gives teams capacity to:

But there’s a way to go.

“Expectations of audit quality are increasing and will continue to do so. While there’s been progress, it’s still an industry-wide issue. That’s why our focus with AI is on quality first, not cost—raise the standard of audit and the efficiency benefits follow, not the other way around,” said Becky Shields, partner and head of digital transformation at Moore Kingston Smith. “If you step back, reducing fees isn’t really the main issue. Missing a material risk or getting something wrong is more significant.”

Shields added that in practice, the “quality-first” stance includes:

“It also improves how we challenge. By surfacing patterns and outliers more clearly, teams can focus their time on areas that matter most,” said Shields. 

But with all that spending, are CFOs seeing all the promised insights, efficiencies, and quality improvements from auditors on the ground?

“We’re not fully there yet. It’s incremental. AI is present, but the audit process still seems human and process-heavy,” said Ying Miao, CFO at Converge Marketing. She added that AI should help audit evolve toward a more insight-driven function. 

Improvements such as automated reconciliations work best where clients have cleaner, structured data upstream, said Miao. However, she is noticing faster iteration cycles because auditors can triage issues earlier.

“Internally, we've used AI to assess our accounting processes and surface potential gaps before audit. For example, walking through our core accounting close end-to-end with an AI-assisted review to identify control weaknesses and process inconsistencies. That has strengthened the quality of what we bring to audit,” said Wang. “The expectation is that auditors will eventually apply similar rigor, but we're not there yet.”

That said, Procurify is seeing real efficiency gains, said Wang. Its audits are moving faster, teams are doing more with less, and the overall working relationship with auditors has improved.

“But we're still waiting for the quality improvement story to be as compelling. We’re tracking that as we evaluate the relationship,” said Wang.

In such a fast-moving landscape, audit market benchmarking data will always lag reality. CFOs need to work hard and be proactive to stay ahead of their board’s questions and next tender process. To do that, CFOs should:

AI is beginning to do what it promised: surface risks faster, test fuller populations, and free up senior judgment for the work that actually matters. However, with more than one in three audits still falling short of basic standards, the industry is nowhere near declaring victory.

But for the first time in a long time, there's a credible mechanism for improvement that doesn't rely on hiring more people or tightening regulation.

CFOs should be watching that closely. The fee conversation can wait.

Answer your board’s next big question:

Dive into last week’s Playbook for the launch of our “Working Capital Warfare” series.

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