Trust in the Age of AI: How Auditors Can Ensure Data Accuracy

AI's Growing Role in Auditing

Artificial Intelligence (AI) is no longer a futuristic concept; it is actively reshaping the auditing profession. From analysing vast datasets to detecting anomalies invisible to the human eye. AI audit tools promise faster, sharper, and more predictive audits.

Yet, trust remains a critical issue. If everyday users question AI-generated news or images, how can boards and investors rely on financial data interpreted by algorithms?

This concern is far from hypothetical. The Auditing and Assurance Standards Board (AUASB) highlights both the risks and rewards of AI in audit processes. Similarly, Chartered Accountants ANZ (CA ANZ) and ACCA stress that while technology can transform auditing, human oversight must remain central.

So, how do auditors balance innovation with trust?

The Rise of AI in Auditing

AI is already enhancing traditional audit methods. It can process entire populations of data, extract insights from unstructured documents, and identify patterns that human auditors might miss.

The Audit and Technology Playbook published by CA ANZ and CPA Australia in 2024 outlines how AI is redefining audit scope and efficiency. With machines handling repetitive analysis, auditors can focus on higher-value tasks such as exercising judgment, interpreting results, and advising stakeholders.

For firms looking to align with best practices, our guide on ASQM 1 compliance offers practical steps to ensure quality management in tech-enabled audits.

Why Trust Is Central to AI-Driven Audits

Despite AI’s capabilities, trust remains the cornerstone of external auditing. Auditors provide assurance that financial statements are accurate and reliable; this role cannot be delegated to machines.

Trust is built through:

Regulatory standards like ASQM 1
Professional scepticism
Transparency in AI use

The AI Transparency Statement released by AUASB and AASB in 2025 mandates clear documentation, tool selection, testing, monitoring, and reporting. Auditors must explain how AI influenced conclusions and how outputs were validated.

This transparency strengthens public confidence in financial reporting and aligns with our external audit services that prioritise ethical and accountable use of technology.

How Auditors Build Confidence in AI-Enabled Audits

External auditors are uniquely positioned to lead in this space. Here’s how they can reinforce trust:

1. Governance and Risk Assessment

Every AI tool must be evaluated for accuracy, security, and relevance before deployment. Firms with clear approval processes signal responsible use of technology.

2. Human Oversight and Interpretation

AI should be seen as a partner, not a replacement. Auditors must interrogate outputs, test assumptions, and apply context. Transparency with boards and clients is essential—explaining in plain language how AI contributed to the audit and how results were verified.

3. Upskilling and Digital Literacy

Tomorrow’s auditors need more than accounting knowledge. They require digital literacy, data ethics, and an understanding of regulatory frameworks. Our AI audit training programs help firms prepare for this shift.

4. Sensitivity Analysis

Running scenarios with different assumptions demonstrates that conclusions are resilient. This evidence-based approach reassures stakeholders that results are robust.

5. Ethical Culture

A clear charter covering fairness, accountability, and transparency ensures AI operates within an ethical framework. This culture must be embedded across audit teams.

Real-World Example: AI in Financial Consolidation

Consider a company using AI to consolidate financial data across divisions. The system generates polished reports but lacks internal review.

During audit, external auditors uncover inconsistencies double-counted revenues and misclassified expenses. By tracing data and applying scepticism, they correct the outputs and restore confidence.

This example illustrates the risks of unchecked reliance on AI. Human judgment remains essential to ensure accuracy and accountability.

Boards and management must understand that while AI can accelerate reporting, its outputs must be reviewed, reconciled, and interpreted before being shared with investors.

Tech-Enabled, Trust-Reliant Auditing

The future of auditing is not about choosing between technology and trust; it is about integrating both. With strong governance, ethical frameworks, transparency, and continuous learning, external auditors can ensure that AI strengthens audit quality.

At National Audits Group, we embrace this opportunity to lead responsibly. Our commitment to ethical AI use, rigorous oversight, and transparent reporting helps protect public confidence while delivering sharper, forward-looking audits.

William McConnell, Auditor, National Audits Group

References

AUASB. (2025). Impact of AI on Auditors. https://www.auasb.gov.au/news/impact-of-ai-on-auditors
Chartered Accountants ANZ & ACCA. (2024, October 9). Audit and Technology Playbook: A Practitioner’s Guide. https://library.charteredaccountantsanz.com/bib/93412
AASB & AUASB. (2025, March 27). Artificial Intelligence (AI) Transparency Statement. https://www.aasb.gov.au/about-the-aasb/artificial-intelligence-ai-transparency-statement