AI is being used at both ends of the Australian tax compliance process — by the ATO to detect discrepancies and by accountants to prepare and lodge returns more efficiently. Understanding both sides of this equation is increasingly important for practitioners.

How the ATO Uses AI and Data Matching

The Australian Taxation Office has been using data matching and analytics for many years. Its current capabilities are significantly more sophisticated than they were even five years ago.

The ATO receives data from a wide range of third parties including employers (via Single Touch Payroll), financial institutions, share registries, state and territory revenue offices, and government agencies. This data is matched against tax returns to identify discrepancies.

The ATO's analytics systems flag returns that appear inconsistent with the data it holds. This can trigger a review, audit, or amended assessment. The ATO publishes information about its data matching programs on its website — these are worth reviewing to understand what data the ATO is collecting and matching.

For accountants, the practical implication is that errors or omissions in tax returns are more likely to be detected than they were in the past. This reinforces the importance of accurate, complete reporting.

How Accountants Are Using AI for Tax Compliance

Automated Data Collection and Entry

AI-powered tools reduce the time spent collecting and entering data for tax returns. Bank feed integrations in Xero, MYOB, and QuickBooks automatically import and categorise transactions. Document capture tools like Hubdoc and Dext extract data from invoices and receipts. Pre-filling from the ATO (available through tax agent portals) populates income and other data directly from ATO records.

These tools reduce manual entry errors and speed up the preparation process. They do not, however, eliminate the need for review — categorisation errors and missing items still occur and need to be caught.

BAS Preparation

All major accounting platforms support automated BAS preparation based on the transactions recorded in the system. AI-assisted categorisation helps ensure transactions are coded correctly for GST purposes. Direct lodgement via the Standard Business Reporting (SBR) framework allows BAS to be submitted to the ATO directly from the software.

The main risk in automated BAS preparation is incorrect transaction coding. If transactions are miscategorised — for example, a GST-free supply coded as taxable — the BAS will be incorrect. Regular review of categorisation rules and spot-checking of transactions remains important.

Tax Return Preparation

Tax agent software such as CCH iFirm, Handisoft, and MYOB Tax integrates with ATO systems to pre-fill data and streamline return preparation. AI features in these platforms are evolving, with some tools beginning to flag potential issues or suggest deductions based on the data entered.

ChatGPT and similar tools are used by some practitioners to research tax issues, draft client communications, and explain complex concepts. These tools do not have access to ATO systems or real-time legislative updates — any information they provide must be verified against primary sources.

Identifying Anomalies and Risks

Some accounting and practice management tools include analytics features that flag unusual transactions or patterns in client data. These can help identify potential issues before lodgement — for example, a significant change in a client's income or expense profile that might attract ATO scrutiny.

Professional Obligations and AI

The Tax Practitioners Board (TPB) has published guidance on the use of AI by registered tax practitioners. The key principles are:

Competence. Practitioners must maintain the competence required to provide tax agent services. Using AI tools does not reduce this obligation — you need to understand the tools you use and their limitations.

Professional judgement. AI outputs must be reviewed and assessed using professional judgement. You cannot delegate your professional responsibility to an AI system.

Accuracy. You remain responsible for the accuracy of returns and other documents you lodge or provide. Errors introduced or missed by AI tools are your responsibility.

Confidentiality. Client information must be handled in accordance with your confidentiality obligations. Before using any AI tool with client data, review the tool's data handling policies.

Supervision. If staff are using AI tools in the preparation of tax returns or other compliance work, appropriate supervision and review processes must be in place.

Practical Risk Management

For practices using AI tools in tax compliance work, a few practical steps help manage risk:

Document your review process. If AI tools assist in preparing a return, document what was reviewed and by whom. This supports your professional obligations and provides a record if questions arise later.

Verify pre-filled data. ATO pre-fill data is generally reliable but is not always complete or current. Review pre-filled information against source documents before lodging.

Check categorisation rules regularly. Automated categorisation rules in accounting software can become outdated or incorrect over time. Periodic review of rules — particularly for clients with changing business activities — reduces the risk of systematic errors.

Stay current with ATO guidance. The ATO publishes guidance on data matching programs, compliance focus areas, and common errors. Reviewing this guidance helps you understand where the ATO is focusing its attention.

Understand tool limitations. AI tools — including those built into accounting software — have limitations. They can make errors, particularly with unusual transactions or complex scenarios. Understanding where a tool is likely to struggle helps you focus your review effort.

Looking Ahead

The ATO has indicated that it will continue to invest in data analytics and compliance technology. For accountants, this means the compliance environment will continue to evolve. Staying informed about ATO data matching programs, maintaining strong review processes, and using AI tools thoughtfully are all part of managing compliance risk effectively in this environment.