UK Audit Firms Expand AI Usage Amid Regulatory Risk Warnings

Major accounting firms in the UK are expanding their deployment of artificial intelligence across audit operations as they seek to improve review depth and operational efficiency. The transition is changing how corporate transactions are examined, while giving rise to concerns around regulatory accountability, model reliance, and junior auditor training.

According to reporting by the Financial Times, major practices including KPMG and EY are deploying artificial intelligence tools across both UK and global operations. These systems screen corporate ledger entries for fraud and anomalies, review work performed by junior staff, and help direct professional scrutiny toward higher risk areas. By replacing traditional statistical sampling with automated screening, auditors can evaluate entire transaction datasets.

Matthew Campbell, chief technology officer for UK audit at KPMG, noted that artificial intelligence allows firms to review the full flow of corporate financial transactions rather than relying on a limited sample. Catherine Burnet, head of audit at KPMG UK, stated that technology is making the auditor role more interesting for professional staff.

At EY, which employs 85,000 auditors globally and executes roughly twice as many annual audits as its peers, management views artificial intelligence as a practical tool to reduce workload pressure on review teams.

Scrutiny and Regulatory Expectations

The push toward automation follows years of intense regulatory pressure on UK audit quality following high profile corporate collapses, including the 2018 failure of Carillion. KPMG received a £21 million fine in 2023 over its audit work for Carillion. In response, both KPMG and EY have built proprietary cloud software platforms designed to improve audit thoroughness.

Despite technological changes, audit firms retain full legal accountability for their official opinions. Financial regulators require auditors to explain the explicit technical reasoning behind judgments on asset valuations and complex transactions.

Industry specialists point out that artificial intelligence serves primarily to triage risk rather than replace professional judgment. Software tools can still produce false negatives or misinterpret unfamiliar transaction structures.

Training Concerns and Commercial Pressures

The broader adoption of software agents also introduces structural questions for workforce development. Graduate training in accounting has traditionally relied on basic review tasks, many of which are now handed to automated tools.

Addressing these workforce concerns, Richard Harrison, UK assurance digital leader at EY, explained that the firm uses technology to support auditors rather than replace them, using software prompts to assist staff instead of dictating answers.

Commercial factors are also influencing adoption strategies. While the Financial Reporting Council and leading audit practices emphasize that audit quality remains the primary objective, cost reductions present a clear incentive. KPMG has already asked its own external auditor, Grant Thornton UK, to reflect artificial intelligence efficiency gains in lower audit fees.

At the same time, strict UK independence rules limit how far audit practices can convert artificial intelligence capabilities into new advisory revenue streams, as non audit services remain restricted for audit clients.

Source: Traders Union.