Dr. Sutthi Suntharanurak, State Audit Advisor ,
State Audit Office of the Kingdom of Thailand
In today’s fast-evolving audit landscape, public sector auditing faces new challenges—ranging from the growing complexity of government operations to the increasing expectations for transparency and accountability. With this, the introduction of Generative Artificial Intelligence (AI) in performance audits becomes not just a technological option but a strategic necessity. Performance audits, grounded in the 3Es: Economy, Efficiency, and Effectiveness, aim to assess whether public resources are utilised in the best possible manner. However, the performance audit could extend the audit criteria to 6Es and even 8Es with environment, equity, ethics, emergency preparedness, and engaging with stakeholders.
The advent of AI has the potential to revolutionize these audits, yet the path forward is fraught with both opportunities and challenges.
What Generative AI Brings to the Table: The Opportunities?
1. Speed and Precision in Data Analysis
In performance audits, auditors scrutinize through vast amounts of financial and operational data. This often involves weeks, if not months, of manual analysis. Generative AI, equipped with machine learning algorithms, can now process these datasets within hours—quickly identifying patterns, anomalies, and inefficiencies. This not only reduces the time required for audits but also enhances the precision with which auditors can pinpoint areas of concern. For instance, AI can automatically detect performance gaps in large-scale public projects by comparing expected outcomes to actual performance metrics in real-time
2. Automation of Routine Audit Tasks
Generative AI has the ability to perform repetitive tasks like drafting initial audit reports, synthesizing large datasets, and generating stakeholder questionnaires. This automation enables auditors to shift their focus from administrative work to higher-value activities, such as risk analysis and strategic recommendations. By streamlining everyday processes, AI frees up auditors’ time for critical analysis, ensuring that human judgment is applied where it matters the most.
3. Real-time Monitoring and Dynamic Reporting
The future of performance auditing may well lie in real-time audits. Generative AI can continuously monitor public sector operations, providing auditors with live data on financial performance, compliance, and project execution. Instead of traditional end-of-period audits, AI can flag issues as they occur, allowing for immediate intervention and correction. This shift could transform how performance audits contribute to proactive governance and public accountability.
Opportunities of Generative AI for Performance Audit
What a Generative AI Works in Practice: Case in Point
Consider a large infrastructure project where auditors must assess whether resources are being used effectively. Traditionally, auditors would review reports and conduct field visits at intervals. With AI, auditors can feed data—such as construction timelines, financial expenditures, and labour efficiency—into the system. AI analyzes the data against project benchmarks, highlighting any deviations, inefficiencies, or potential budget overruns. The result? Auditors can intervene in real-time, offering corrective suggestions before issues escalate.
How to Balance the Benefits with the Risks: The Challenges
1. Data Quality and Integrity
The saying "garbage in, garbage out" applies more than ever when using AI. Generative AI’s performance depends on the quality of the data it processes. If the underlying data is inaccurate, incomplete, or biased, the AI-generated results will be similarly flawed. This raises the stakes for auditors, who must ensure that the data being analyzed is reliable and clean. Without proper data governance, AI’s outputs could lead to erroneous conclusions that damage the credibility of the audit process.
2. Accountability in AI-Driven Audits
While AI can generate reports and flag anomalies, its reasoning often lacks transparency. How did it arrive at a particular conclusion? Can auditors defend these findings in court or before a public inquiry? This lack of interpretability makes it difficult to hold AI accountable. In public sector audits, where transparency is paramount, auditors must ensure that they can justify AI-generated findings with clear and understandable reasoning. This means that human auditors remain central to interpreting and validating AI’s outputs.
3. Ethical and Legal Hurdles
The use of AI in performance audits raises ethical concerns, particularly around privacy and data security. Government agencies deal with sensitive data, and AI systems are not immune to breaches or manipulation. Furthermore, the legal frameworks governing AI in public auditing are still evolving, leaving grey areas around responsibility and liability. Auditors must navigate these legal and ethical challenges to ensure that the use of AI does not compromise the integrity of the audit process.
4. Training and Skill Gaps
For many auditors, the transition to AI-driven audits requires a significant upskilling effort. Generative AI brings a new dimension to auditing that traditional auditors may not be fully prepared for. Understanding how AI works, interpreting its results, and applying human judgment in conjunction with machine-generated insights will require dedicated training programs. As AI becomes more prevalent, auditors will need to become both technologists and analysts, blending traditional audit skills with AI literacy.
Conclusion: What Lies Ahead
The integration of Generative AI into performance audits offers a wealth of opportunities—faster data analysis, automation of routine tasks, and real-time monitoring are just a few examples. However, the challenges are equally significant. Issues around data quality, accountability, ethics, and auditor training must be addressed to fully realize AI’s potential.
How Should the Auditing Community Respond?
The path forward requires a balanced approach. Supreme Audit Institutions and public auditors must harness the power of Generative AI while preserving the principles of transparency, accountability, and ethical governance. The future of performance audits is not about replacing human auditors with machines but about creating a collaborative system where AI enhances human capabilities.
As we move toward this new era, auditors must remain vigilant. The success of AI in public auditing will depend on our ability to manage its risks while maximizing its opportunities. In doing so, we can ensure that AI becomes a tool for better governance, improved public accountability, and a more efficient audit process—serving the public interest with greater precision and insight.
This future holds the potential to redefine the role of performance audits, and it is a future we should actively shape, rather than passively observe.