The IRS has a massive volume of tax returns and financial data to analyze each year, making it impractical to manually review every single return for potential issues or discrepancies. AI and machine learning techniques allow the IRS to efficiently sift through this vast amount of data and identify high-risk returns or areas that warrant further examination or auditing.
By training artificial intelligence models on historical audit data, tax compliance patterns and various risk factors, the IRS can develop predictive models that can analyze new tax returns and flag potential issues or anomalies. These risk factors can include inconsistencies between reported income and third-party information, disproportionate deductions or credits, complex business structures, transactions with tax havens and other indicators of potential non-compliance.
The AI models can assign risk scores or rankings to tax returns based on the likelihood of under-reported income, improper deductions, or other violations. The IRS can then prioritize audits and examinations based on these risk scores, focusing their limited resources on the returns or areas with the highest potential for uncovering tax issues.
Additionally, AI can help the IRS identify emerging patterns or trends in tax evasion schemes, allowing them to proactively adjust their audit selection criteria and strategies to address new types of non-compliance as they arise.
It’s important to note that while AI will play a significant role in identifying potential audit candidates, human tax examiners and agents should still be involved in the actual audit process, reviewing the flagged returns, gathering additional information, and making final determinations. AI will serve as a tool to enhance efficiency and prioritization, but human expertise and judgment remain crucial in the audit and examination process.
By leveraging AI in this way, the IRS can better allocate its limited audit resources, increase the effectiveness of its enforcement efforts, and ultimately improve overall tax compliance and revenue collection.