<?xml version="1.0" encoding="UTF-8"?>
<article article-type="research-article" xml:lang="en" xmlns:xlink="http://www.w3.org/1999/xlink">
<front>
<journal-meta>
<journal-id journal-id-type="publisher">global-journal-of-management-and-business-research</journal-id>
<journal-title-group>
<journal-title>Global Journal of Management and Business Research</journal-title>
</journal-title-group>
<issn publication-format="print">0975-5853</issn>
<issn publication-format="electronic">2249-4588</issn>
<publisher><publisher-name>Global Journals Publishing Group Incorporated</publisher-name></publisher>
<self-uri xlink:href="https://globaljournals.org/journal-seo-export/jats/145856.xml" />
</journal-meta>
<article-meta>
<article-id pub-id-type="doi">10.34257/GJMBRA145856</article-id>
<article-id pub-id-type="publisher-id">145856</article-id>
<title-group>
<article-title>Artificial Intelligence and Tax Governance: Toward Responsible Digital Fiscal Administration in a Southern African Country</article-title>
<subtitle>AI and Fiscal Governance in Tax Administration</subtitle>
</title-group>
<contrib-group>
<contrib contrib-type="author"><name><surname>Rodolfo</surname><given-names>Dr. Bruno Couto De Abreu</given-names></name><xref ref-type="aff" rid="aff1" />
</contrib>
</contrib-group>
<aff id="aff1">MOZAMBIQUE, Catholic University of Mozambique</aff>
<pub-date publication-format="electronic" date-type="pub" iso-8601-date="2026-01-06">
<day>06</day>
<month>01</month>
<year>2026</year>
</pub-date>
<volume>25</volume>
<issue>A6</issue>
<fpage>11</fpage>
<lpage>19</lpage>
<abstract><p>This study examines the transformative role of Artificial Intelligence (AI) in modernising tax administration and enhancing fiscal governance in emerging economies, with an empirical focus on Country in the Southern African region. It explores how AI-driven digital fiscal administration is reshaping the tax landscape through automation, predictive analytics, and data-driven decision-making. Using a qualitative and exploratory design, the research integrates a systematic literature review with comparative case studies from Brazil and Singapore to contextualise international lessons for developing economies. The findings reveal that AI can substantially improve operational efficiency, predictive auditing, and transparency in tax collection processes, highlighting its transformative potential within fiscal institutions. These findings directly inform the development of the proposed AI-Driven Tax Governance Framework, which connects technological innovation with institutional, legal, and citizen-centric dimensions of responsible AI adoption.</p></abstract>
<kwd-group kwd-group-type="author-generated">
<kwd>artificial intelligence</kwd>
<kwd>digital fiscal governance</kwd>
<kwd>tax modernization</kwd>
<kwd>emerging economies</kwd>
<kwd>southern</kwd>
<kwd>fiscal transparency.</kwd>
</kwd-group>
<self-uri content-type="pdf" xlink:href="https://globaljournals.org/GJMBR_Volume25/2-Artificial-Intelligence-and-Tax-Governance.pdf" />
<self-uri content-type="html" xlink:href="https://globaljournals.org/scholarly-articles/artificial-intelligence-and-tax-governance-toward-responsible-digital-fiscal-administration-in-a-southern-african-country/" />
</article-meta>
</front>
<body>
<sec>
<title>Full Text</title>
<p>This study examines the transformative role of Artificial Intelligence (AI) in modernising tax administration and enhancing fiscal governance in emerging economies, with an empirical focus on Country in the Southern African region. It explores how AI-driven digital fiscal administration is reshaping the tax landscape through automation, predictive analytics, and data-driven decision-making. Using a qualitative and exploratory design, the research integrates a systematic literature review with comparative case studies from Brazil and Singapore to contextualise international lessons for developing economies. The findings reveal that AI can substantially improve operational efficiency, predictive auditing, and transparency in tax collection processes, highlighting its transformative potential within fiscal institutions. These findings directly inform the development of the proposed AI-Driven Tax Governance Framework, which connects technological innovation with institutional, legal, and citizen-centric dimensions of responsible AI adoption.</p>
</sec>
</body>
</article>