AI IN TAXATION, GST AND TAX ADMINISTRATION: TRANSFORMING COMPLIANCE, REVENUE COLLECTION AND TAXPAYER SERVICE
Abstract
Artificial Intelligence (AI) is increasingly transforming the way governments design, administer and enforce tax systems. Tax administration is particularly suitable for AI because it involves large volumes of structured and unstructured data, repetitive compliance processes, risk assessment, fraud detection and continuous interaction with taxpayers. In India, the digital transformation of taxation has progressed through income-tax e-filing, faceless assessment, the Goods and Services Tax Network (GSTN), e-invoicing, e-way bills, automated return processing and data analytics. These systems create an extensive digital information environment in which AI and machine learning can support tax compliance, identify anomalous transactions, improve taxpayer services and assist tax authorities in allocating limited administrative resources. This paper examines the role of AI in taxation, with particular emphasis on GST and Indian tax administration. It analyses major applications including fraud detection, input tax credit verification, risk-based scrutiny, taxpayer assistance, automated document processing, predictive analytics and compliance management. The paper also evaluates the benefits and limitations of AI, including privacy concerns, algorithmic bias, cybersecurity, explainability, data quality and the danger of excessive automation. International evidence indicates rapid adoption of AI by tax administrations, while India's expanding digital tax infrastructure provides a substantial foundation for further AI-enabled administration. The paper argues that AI should primarily function as a decision-support and risk-management technology, with appropriate human oversight rather than completely replacing statutory decision-making. A governance framework based on transparency, accountability, data protection, human review and continuous auditing is therefore essential for trustworthy AI-enabled taxation.