By: James Pickett | 07/14/25
The IRS faces a daunting challenge: enforcing tax compliance across millions of taxpayers with limited resources. Traditional audit methods, which rely heavily on manual review and random selection, are increasingly inadequate for detecting sophisticated tax avoidance schemes and processing the growing volume of complex returns.
To address these challenges, the IRS is investing significant resources bolstered by funding from the Inflation Reduction Act into modernizing its operations with advanced technologies, including artificial intelligence. The agency’s strategic plan for 2025 and beyond explicitly prioritizes AI and data analytics to enhance enforcement, streamline operations, and improve taxpayer services.
AI enables the IRS to process vast datasets, identify patterns of non-compliance, and automate time-consuming tasks. This technological shift is not just about efficiency; it is also about keeping pace with increasingly complex business structures, global transactions, and evolving tax avoidance strategies. As a result, the IRS is not only using AI to select audit targets but also to support agents in drafting documents, analyzing filings, and even providing real-time feedback to taxpayers during the filing process.
The core application of AI in IRS audits is in the selection and risk scoring of tax returns. Machine learning models and advanced analytics sift through enormous volumes of tax data to flag returns that exhibit anomalies or patterns associated with non-compliance. For example, the IRS has used AI to identify high-risk intercompany transactions, detect base erosion and profit-shifting schemes, and scrutinize complex partnership structures.
Recent initiatives include the use of AI to select 76 of the most significant partnerships in the country for audit, as well as 60 large corporations with average assets exceeding $24 billion. AI models analyze a wide range of data points, including prior year returns, tax account information, and behavioral patterns, to assess the likelihood of errors, fraud, or aggressive tax positions.
Importantly, the IRS is exploring both in-house and commercial AI solutions, with a strong emphasis on maintaining data privacy and compliance with statutory confidentiality requirements, such as those found in IRC section 6103.
1. Enhanced Efficiency and Coverage:
AI enables the IRS to process and analyze far more returns than would be possible with manual review alone. For instance, in 2022, the IRS audited over 700,000 returns, with each agent managing approximately 10 audits, many of which involved thousands of documents and took years to resolve. AI can dramatically reduce the time required for document review, drafting, and case analysis.
2. Improved Targeting and Reduced “No-Change” Audits:
By leveraging AI-driven risk scoring, the IRS can more effectively identify returns with a high probability of non-compliance, thereby reducing the number of audits that result in no changes and allowing resources to be focused on the most significant cases.
3. Consistency and Impartiality:
AI models, when properly designed and monitored, can apply consistent criteria across all returns, potentially reducing human bias and subjectivity in audit selection. However, as discussed below, this benefit depends on careful oversight and ongoing bias testing.
4. Support for IRS Agents:
Generative AI tools can assist agents in drafting revenue agent reports, information document requests, and deficiency notices, freeing up time for higher-level analysis and decision-making.
As the IRS expands its use of AI in audits, businesses, especially those with complex structures or significant cross-border activity, should take proactive steps to mitigate risk and ensure compliance:
1. Strengthen Documentation and Internal Controls:
AI-driven audits are more likely to flag inconsistencies, anomalies, or aggressive tax positions. Businesses should ensure that all positions are well-documented, with clear supporting evidence and rationale.
2. Review Historical Filing Patterns:
Since AI models often compare current returns to prior years and industry benchmarks, businesses should review their historical filings for consistency and address any unexplained variances.
3. Monitor Related-Party Transactions and Expense Classifications:
The IRS is focusing on areas such as the distinction between business and personal expenses, as well as related-party transactions. Businesses should ensure these are adequately documented and substantiated.
4. Invest in Compliance Technology:
While the IRS is utilizing AI for audits to enhance enforcement, businesses can also leverage AI to complete taxes more efficiently by using AI-powered tools to improve compliance, identify potential risks, and streamline documentation. As the IRS using AI for audits becomes more widespread, adopting similar technology can help businesses stay proactive and reduce the likelihood of triggering an audit.
5. Stay Informed and Engage with Advisors:
Given the evolving nature of AI initiatives, businesses should stay informed about new developments and consult with tax professionals to understand how these changes may impact their risk profile.
6. Prepare for Transparency and Appeals:
AI-driven decisions must still comply with due process and taxpayer rights. Businesses should be prepared to request explanations for audit selections and to challenge any determinations through established procedures.
Yes, the IRS is actively using AI for audit selection and risk scoring, particularly for large partnerships, corporations, and high-wealth individuals. The agency has announced and piloted several AI-driven initiatives, with plans to expand these efforts in the coming years.
AI systems analyze vast amounts of tax data to detect anomalies, patterns, or behaviors associated with non-compliance. These models flag returns with higher risk scores, allowing the IRS to focus audits on cases most likely to involve errors, fraud, or aggressive tax positions.
IRS AI models review tax return data, prior year filings, tax account information, and sometimes behavioral patterns. For complex entities, AI may also analyze related-party transactions, expense classifications, and industry benchmarks to assess compliance risk.
AI audits are designed to improve targeting rather than necessarily increase the overall number of audits. However, businesses with complex or unusual filings may face a higher likelihood of being selected if their returns trigger AI risk indicators.
Yes, businesses can benefit from using AI-powered compliance tools to identify potential risks, ensure accurate filings, and streamline documentation. As the IRS’s artificial intelligence capabilities grow, leveraging similar technology can help businesses stay ahead of potential issues and reduce audit risk.
Conclusion:
The integration of AI in IRS audits marks a significant shift in tax administration. While the promise of greater efficiency and fairness is real, businesses must be mindful of the new risks and expectations that come with AI-driven enforcement. By strengthening compliance practices and embracing technology, companies can better navigate the evolving landscape of IRS AI audits.
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