International Journal For Multidisciplinary Research

E-ISSN: 2582-2160   •   Impact Factor: 9.24

A Widely Indexed Open Access Peer Reviewed Multidisciplinary Bi-monthly Scholarly International Journal

Call for Paper Volume 7, Issue 4 (July-August 2025) Submit your research before last 3 days of August to publish your research paper in the issue of July-August.
Submit Research Paper Join as a Reviewer

Plagiarism is checked by the leading plagiarism checker TurnItIn

Call for Paper

Volume 7 Issue 4
July-August 2025

Submit your research paper

Indexing Partners
Academia Advanced Sciences Index Bielefeld Academic Search Engine CiteSeer DRJI Google Scholar Independent Search Engine & Directory Network ISI (International Scientific Indexing) Issuu Mendeley Research Networks
RefSeek ResearcherId - Thomson Reuters ResearchGate Scirus Scribd Semantic Scholar UTeM - Universiti Teknikal Malaysia Melaka Wiki for Call for Papers WorldCat Zenodo

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

Author(s) Ms. ATHIRA T A Thazhathuveettil
Country India
Abstract 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.
Keywords rtificial Intelligence, Tax Preparation, Algorithmic Bias, Tax Compliance, Digital Taxation, Machine Learning, Tax Technology
Field Business Administration
Published In Volume 7, Issue 4, July-August 2025
Published On 2025-08-14
DOI https://doi.org/10.36948/ijfmr.2025.v07i04.53468
Short DOI https://doi.org/g9w7hz
View / Download PDF File

Share this



E-ISSN 2582-2160
CrossRef

CrossRef DOI is assigned to each research paper published in our journal.

IJFMR DOI prefix is
10.36948/ijfmr

Downloads
Research Paper Format Copyright Permission Form and Undertaking Form Cover Page Vol 7 Isu 4Cover Page Vol 7 Isu 3Cover Page Vol 7 Isu 2

All research papers published on this website are licensed under Creative Commons Attribution-ShareAlike 4.0 International License, and all rights belong to their respective authors/researchers.

CC-BY-SA Open Access

About IJFMR
Fees & Payment
Current Issue
Publication Archive 		Submit Research Paper
Track Submission Status
Publication Guidelines
Publication Ethics
Peer Review & Plagiarism 		Join as a Reviewer
Editors & Reviewers
Reviewer Referral Program
Get Reviewer Membership Certi. 		Website/Journal Policies
Usage Policy
Content Policies
Privacy Policy
Contact Us +91-9687-828-838 editor@ijfmr.com