Artificial intelligence is reshaping industries worldwide. According to recent research from the International Data Corporation (IDC), AI may contribute USD $19.9 Trillion to the global economy through 2030 and could help drive 3.5% of global GDP. Beyond the more obvious economic benefits of AI, the technology is often cited as having the potential to revolutionise administrative processes around the world, such as supply chain management, healthcare administration, regulatory compliance, and all aspects of taxation, from compliance to advisory and dispute resolution.
This article discusses how AI could reshape not just tax compliance but tax administration as a whole, by automating audits, assisting with record-keeping, detecting fraud, flagging risks, streamlining controversies, and improving revenue collection. With the ability to analyse vast datasets in real-time, AI may be able to identify discrepancies, flag potential tax risks, and even provide predictive insights to governments. If implemented effectively, these advancements could make tax systems more efficient and help reduce the administrative burden on taxpayers while improving compliance. However, the extent to which AI will deliver on these promises is yet to be showcased by any government.
The implementation of AI in taxation requires careful governance. Ensuring transparency, mitigating bias, and maintaining taxpayer privacy are critical challenges that tax authorities must address. Further, while AI is frequently promoted as a tool for efficiency, questions remain as to whether AI-driven decision-making will lead to fairer outcomes or simply amplify existing systemic issues.
The Australian National Audit Office (ANAO) recently released its report assessing the Australian Taxation Office’s (ATO) capabilities to adopt AI. The audit (yes – that’s right – an audit. Taste of the ATO’s own medicine?) evaluated whether the ATO has effective governance, design, deployment, and monitoring arrangements for AI systems. While AI may present significant opportunities for tax compliance and administration, the audit highlighted areas where the ATO strategy and systems currently lack the necessary foundations for smooth AI integration.
Key findings of the ANAO’s audit of the ATO
The ANAO’s report concluded that the ATO has only partly effective arrangements in place to support AI adoption. While the agency has made progress in integrating AI into its operations, it lacks comprehensive governance structures and risk management frameworks specific to AI systems.
Governance gaps identified in the audit include the absence of clearly defined enterprise-wide roles and responsibilities, insufficient central oversight of AI use across the organisation, and the need for a dedicated AI risk management framework. The ATO has established governance bodies to oversee AI adoption, including a Data and Analytics Governance Committee formed in September 2024 and the appointment of a Chief Data Officer as the accountable official for AI use in November 2024. However, these governance structures are still in their infancy and it is unclear whether they will be sufficient to manage the complexities of AI adoption.
The report additionally found that the ATO has not sufficiently integrated ethical and legal considerations into AI design, raising concerns about the potential for bias, privacy breaches, lack of transparency, and accountability issues.
Monitoring and evaluation were also found to be lacking. The ATO had no structured framework for regularly assessing AI models in production, with 74 per cent of AI models missing required data ethics assessments. While the agency has since developed a monthly report on AI strategy implementation, it has not yet established a structured evaluation approach. Without robust monitoring and governance systems in place, there is a risk that AI-driven tax administration could create more problems than it solves.
In response to the above, the ANAO recommended that the ATO:
- develop and implement AI-specific governance and risk management frameworks;
- clearly define roles and responsibilities related to AI oversight;
- establish formal policies and procedures for AI design, development, and deployment;
- integrate ethical and legal considerations into AI systems more comprehensively; and
- implement monitoring and reporting mechanisms to assess AI effectiveness over time.
AI and tax: global perspectives
AI is increasingly being explored as a core tool in tax administration worldwide. A recent International Monetary Fund (IMF) opinion piece highlighted how AI has the potential to improve tax compliance, fraud detection, and revenue collection. Governments globally are investing in AI-driven solutions with the aim of enhancing efficiency and improve enforcement mechanisms. However, the success of these initiatives varies significantly, and long-term effects remain uncertain.
AI systems can analyse large volumes of data to detect patterns indicative of tax evasion, fraudulent claims, or underreported income. Machine learning models can assist in identifying high-risk taxpayers, allowing tax authorities to allocate resources more efficiently. Where AI is deployed to analyse blockchain transactions, it could offer a powerful (even draconian) tool to analyse transaction information, automate collection, and audit tax compliance.
The IMF article contends that AI can assist tax authorities by enabling real-time risk assessments, providing early warnings for potentially non-compliant behaviour. AI’s predictive capabilities could also assist tax authorities to forecast revenue more accurately. That said, predictive analysis carries risk, including the potential for over-reliance on models that may not be the most accurate or unbiased.
