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ZENODO
Journal . 2026
License: CC BY
Data sources: ZENODO
ZENODO
Journal . 2026
License: CC BY
Data sources: Datacite
ZENODO
Journal . 2026
License: CC BY
Data sources: Datacite
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Artificial Intelligence as An Enabler of Income Tax Compliance in India: Shaping the Future of Tax Administration

Authors: Siddhija Ramesh Nair;

Artificial Intelligence as An Enabler of Income Tax Compliance in India: Shaping the Future of Tax Administration

Abstract

Technological advancements are transforming governance worldwide, and artificial intelligence (AI) has emerged as a key driver of reform in public administration. In India, the Income Tax Department is increasingly leveraging AI to enhance compliance, reduce human discretion, and strengthen taxpayer trust. This paper examines how AI enables income tax compliance in India by exploring initiatives such as faceless assessments, pre-filled returns, data analytics, risk profiling, and automated communication. Practical examples from professional experience illustrate how AI identifies missing information, prevents disputes, and streamlines refunds. While AI improves efficiency and transparency, challenges such as data privacy, algorithmic bias, and digital accessibility require careful attention. Responsible deployment of AI has the potential to make India’s tax system more efficient, fair, and trustworthy.

Keywords

Artificial Intelligence; Income Tax Compliance; Tax Administration; Digital Governance; India

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
Green