AI-Powered Tax Preparation: Accuracy, Bias, and Compliance Implications of Automated Tax Systems

The integration of artificial intelligence (AI) into tax preparation systems represents a fundamental transformation in how individuals and businesses comply with tax obligations. This study examines the accuracy, bias, and compliance implications of AI-powered tax preparation tools, analyzing their impact on taxpayer behavior, audit outcomes, and revenue collection. Through a mixed-methods approach combining quantitative analysis of 50,000 tax returns processed by AI systems and qualitative interviews with 200 taxpayers and 50 tax professionals, this research reveals significant disparities in AI performance across demographic groups and income levels. While AI systems demonstrate superior accuracy for standard returns (97.3% vs. 94.1% for human preparers), they exhibit systematic biases against minority taxpayers and complex financial situations. The findings indicate that AI adoption could exacerbate existing inequalities in tax compliance while potentially reducing overall preparation costs by 40-60%. This research provides critical insights for policymakers, technology developers, and tax practitioners navigating the digital transformation of tax administration.