The usage of artificial intelligence (AI) by the Income Tax department to build regression models is aimed at identifying deviations and errors in tax filing. The department is exploring this technology to simplify the process of analyzing the data they have gathered and creating a regression model to pinpoint deviations in tax filings.
The goal of implementing AI in this context is to streamline the process and make it more efficient. The Income Tax department has been increasingly adopting technology and data analytics to ease the compliance burden on taxpayers and detect tax evasions. Some of the initiatives they have taken include using pre-filled Income Tax Return (ITR) forms to improve the filing process, implementing faceless assessments and appeals to reduce the need for physical interaction with the department, and employing technology platforms like Centralised Public Grievance Redress and Monitoring System (CPGRAMS), e-Nivaran, and Aaykar Seva Kendras (ASK) for grievance redressal.
With the information gathered under the faceless assessment scheme, the regression model will help the department segregate deviations and assess them separately without the need for extensive human intelligence involvement. This utilization of AI is likely to enhance the department's ability to detect tax non-compliance and efficiently address it.
In another context, Shankar Viswanathan, the Chief Information Officer of Sundaram Clayton Ltd, mentioned the company's plan to build a new factory with mobile robots powered by 5G technology to transport materials within the facility. The factory will also employ various IoT devices, generating substantial data. An AI engine will process this data to optimize efficiency in the factory's operations. This project aims to create the first fully 5G-wired factory in the country, showcasing the potential benefits of integrating AI and 5G technology into industrial processes.
Overall, the adoption of AI in different sectors, including taxation and manufacturing, is a promising development that can lead to increased efficiency and better decision-making capabilities.
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