AI: A Larger Firm’s Perspective

Why It Matters

AI boosts audit efficiency, risk detection, and client service, but requires strict governance to protect data integrity and professional judgement.

Key Takeaways

• OCR and pattern recognition already automate data extraction.
• Generative AI can draft workpapers but may hallucinate.
• Large firms focus on analytics, automation, sophisticated solutions.
• Human‑centric governance and EDP essential for client confidentiality.
• Emerging agentic AI may automate evidence‑gathering tasks.

Pulse Analysis

The audit profession is moving from experimental AI discussions to operational reality. Tools such as optical character recognition, pattern‑recognition analytics, and automated anomaly detection have already been embedded in routine procedures, accelerating document review and expanding risk‑based testing to full‑population analyses. The recent surge of generative AI platforms—ChatGPT, Microsoft Copilot, Claude—adds a new layer, enabling auditors to draft working papers, summarize contracts, and generate preliminary risk narratives with a single prompt. While these capabilities promise faster turnaround and deeper insight, they also introduce variability that firms must manage.

The primary obstacle remains governance. Generative models can produce convincing yet inaccurate outputs, known as hallucinations, making rigorous verification indispensable. Data protection concerns intensify when confidential client information is fed into cloud‑based AI services; enterprises therefore require AI solutions with Enterprise Data Protection (EDP) and strict vendor contracts. RSM’s ‘human‑centric AI integration’ model, reinforced by the AUTOMAT prompting framework, exemplifies how firms can harness AI while preserving professional scepticism. Regulatory bodies across the UK, EU, and US are drafting guidance, urging firms to document AI usage, maintain audit trails, and ensure human sign‑off on all AI‑generated work.

Looking ahead, agentic AI—systems capable of autonomous, multi‑step tasks—could reshape evidence‑gathering by navigating client environments and extracting relevant data without constant human direction. Early adopters that combine such technology with robust training programs and dedicated centres of excellence will differentiate themselves through higher‑quality audits and enhanced client service. However, the competitive edge will depend on continuous skill development, transparent governance, and alignment with evolving standards. As AI becomes a permanent fixture, the audit profession’s core principles—scepticism, judgement, and evidence‑based conclusions—will be amplified rather than replaced.