Four insights from the literature on the effects of AI on audit practice

1. AI is improving audit quality and efficiency

The literature consistently shows that, when properly implemented, AI strengthens audit effectiveness. AI helps auditors to identify fraud risks, detect misstatements, analyze entire populations of transactions rather than samples, and reduce human error. What is more, it automates repetitive and time-consuming tasks, allowing audits to be completed more efficiently. Key message: Overall, AI is enhancing both the effectiveness and efficiency of audit engagements, supporting the profession’s ability to provide timely and reliable assurance.

2. AI changes auditors’ work experience in both positive and negative ways

AI introduces new demands on individual auditors by requiring additional skills and creating uncertainty about future professional roles. These developments may increase mental load and psychological strain. At the same time, AI reduces auditors’ workload and involvement in repetitive tasks, enabling them to focus on more meaningful and value-adding work. The result is a dual effect, where AI simultaneously increases stress while also improving job experience and perceived meaningfulness of auditors’ work. Key message: Understanding how AI affects auditors’ well-being, engagement, motivation, and job satisfaction is highly relevant.

3. Professional judgment becomes the central challenge

An important concern emerging from the literature is the effect of AI on auditors’ professional judgment and skills. As AI increasingly handles data collection, processing, and basic analytical work, auditors have fewer opportunities to engage in experiential learning, which is essential for building professional judgment and expertise. Reduced exposure to traditional audit tasks may hinder the development of professional expertise and skepticism, particularly among junior auditors. This risk is amplified by the fact that AI can sometimes produce inaccurate outputs that require careful critical evaluation. This creates a challenge: AI imperfections increase the need for critical judgment while potentially weakening some of the mechanisms through which that judgment is developed. Key message: Future success with AI in auditing will depend not only on technological capabilities but also on maintaining and strengthening auditors’ professional skepticism, independent judgment, and ability to challenge AI-generated outputs.

4. AI should be viewed as an interconnected system of benefits and risks

The literature review demonstrates that AI simultaneously creates resources and demands for audit practice. Improvements in accuracy and efficiency may coexist with deskilling, increased cognitive demands, and challenges to professional judgment. These effects do not operate independently. They influence and potentially offset one another. Key message: The ultimate impact of AI on auditing will depend not on any single effect, but on how its benefits and risks combine and evolve over time.