Continued from P1

Andhra Pradesh’s presentation, titled “Use of AI/ML and Automation in GST Tax Administration — From Case Selection to Litigation,” was included as a dedicated agenda item.

The Commercial Taxes Department explained how AI-based systems are being used for case selection and allocation, return scrutiny under Section 61, audit under Section 65, inspection under Section 67 and litigation before the First Appellate Authority, GST Appellate Tribunal and High Court.

The system integrates data from four sources and uses 19 analytical reports and a 35-parameter risk matrix to identify and classify cases before they reach officers. High-value cases are routed for additional scrutiny through statutory mechanisms.

The department also demonstrated its Legal-AI Officer Assistant, trained on GST laws and about 22,000 judgments from courts and tribunals. It has been extended across three litigation forums and is assisting officers with drafting instructions, para-wise remarks, and replies for more than 13,700 cases.

The department presented data comparing AI-assisted operations with the earlier manual system. During six months of AI-driven return scrutiny, revenue detection reached Rs 743.43 crore, compared with Rs 365.75 crore during the comparable legacy period. Detection per case also rose sharply to Rs 27.63 lakh, against Rs 3.08 lakh under the earlier process.

The department stressed that AI does not replace statutory decision-making. It generates drafts and analytical inputs, while officers take decisions and digitally sign notices and orders, ensuring traceability.

The presentation received strong interest from participating States. Tamil Nadu, Bihar, Rajasthan, Chhattisgarh, Kerala, Assam and Meghalaya have sought details of the system and are planning visits to Andhra Pradesh to study its architecture and workflow.

The Revenue Secretary commended AP’s initiative as a model that other States could consider adopting. The state also outlined plans to extend AI to refund processing, registration monitoring, cancellation, recovery proceedings, revision and review petitions and advance rulings. It sought greater GSTN data and API support from the Centre to expand the system further.