Development of an artificial intelligence framework to combat tax noncompliance in Botswana

Abstract

Orientation: The article focuses on the recognition that artificial intelligence technologies can be a key solution to effectively mitigate growing tax noncompliance in Botswana.
Research purpose: The purpose of this study is to design and propose an artificial intelligence framework that can effectively address and minimise tax noncompliance in Botswana.
Motivation for the study: The motivation for this study is to address the persistent issue of tax noncompliance in Botswana, which undermines effective revenue generation. By developing an artificial intelligence framework, the study aims to enhance the efficiency and effectiveness of tax administration, fostering greater compliance and fiscal stability.
Research design, approach and method: Guided by disruptive innovation theoretical lens, this study adopts a qualitative research approach, using in-depth interviews with key participants from the Botswana Unified Revenue Service (BURS) and the business community. The data collected were analysed using thematic analysis to identify key patterns and insights related to tax compliance issues.
Main findings: The findings indicate that current compliance measures are insufficient to address the complexities of tax noncompliance. Furthermore, the BURS has not yet implemented an innovative and tailored framework designed to effectively mitigate tax noncompliance in Botswana and still incur significant tax revenue leakages.
Practical/managerial implications: The implementation of the framework may help to combat tax noncompliance, resulting in increased tax revenue and voluntary tax compliance.
Contribution/value-added: This study makes a significant contribution to the body of knowledge by developing a modern and comprehensive framework tailored specifically to address tax noncompliance in Botswana.