EVALUATING ARTIFICIAL INTELLIGENCE-ENABLED TRANSFORMATION FRAMEWORKS FOR ENTERPRISE TAX SYSTEM MODERNIZATION: A SECONDARY RESEARCH ANALYSIS OF INTELLIGENT INTEGRATION AND REGULATORY COMPLIANCE

Authors

  • Nihar Mukesh Author

DOI:

https://doi.org/10.64751/5hnwtz39

Abstract

Enterprise tax systems continue to face challenges associated with fragmented data, manual processes, regulatory complexity, and limited real-time visibility. This research evaluates AI-enabled transformation frameworks for enterprise tax modernization through secondary research analysis. The study examines AI capabilities, intelligent integration approaches, governance requirements, and future transformation opportunities. Findings highlight that AI can improve automation, accuracy, compliance efficiency, and strategic decision-making when supported by effective integration and governance mechanisms. The research contributes a conceptual understanding of intelligent tax ecosystems and provides insights for responsible enterprise AI adoption.

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Published

2026-09-12

How to Cite

Nihar Mukesh. (2026). EVALUATING ARTIFICIAL INTELLIGENCE-ENABLED TRANSFORMATION FRAMEWORKS FOR ENTERPRISE TAX SYSTEM MODERNIZATION: A SECONDARY RESEARCH ANALYSIS OF INTELLIGENT INTEGRATION AND REGULATORY COMPLIANCE . American Journal of AI Digital Transformation and Regenerative Pharmacist, 2(3), 166-175. https://doi.org/10.64751/5hnwtz39