Orientation: Artificial intelligence (AI) is implemented in tax administration to reduce tax noncompliance and improve tax ratio. Despite these highly publicised benefits, BURS continue to use traditional measures to enforce tax compliance behaviour in Botswana than current AI technologies within its operational divisions.
Research purpose: The purpose of the study is to develop an AI framework to combat tax noncompliance in Botswana.
Motivation for the study: A lacuna was discovered, highlighting the need for a framework that can effectively eradicate tax noncompliance in Botswana. The aim is that BURS fully embrace AI, thereby improving revenue [collection] yields and tax compliance in Botswana.
Research design, approach and method: In order to accomplish the objectives of this study, a qualitative-exploratory, descriptive and contextual research paradigm grounded within phenomenological examination was employed. Sixteen (N=16) interviews were carried out to collect qualitative data. Semantic thematic data analysis was used to analysis data and for theme identification.
Main findings: The findings reveal that most transactions in Botswana are cash based which fuels tax noncompliance. High level of cash transactions was witnessed in second hand car dealership, Indian and Chinese business owners. The participants further highlight that most business transactions in Botswana are cashless that should be a part of the AI framework to enhance tax compliance.
Practical/ managerial implications: The study demonstrates the potential impact of AI in solving tax noncompliance. The framework presented in this study provides conditions and guideline for BURS to implement permanent solutions to achieve total compliance and sustainable economic growth.
Contribution/value-add: A framework is developed and recommended for use by BURS that is explicitly aimed at providing practical solutions to tax noncompliance in Botswana.