https://ir.zou.ac.zw/files/original/6ca4e4addde94d863605738e97441bcd.pdf 17cd243c455cc223ef9ceb73f9de049d Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Staff Publications Text A resource consisting primarily of words for reading. Examples include books, letters, dissertations, poems, newspapers, articles, archives of mailing lists. Note that facsimiles or images of texts are still of the genre Text. Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource THE ROLE OF ARTIFICIAL INTELLIGENCE IN REVENUE MANAGEMENT IN ZIMBABWE Creator An entity primarily responsible for making the resource KEITH TICHAONA TASHU1 TAFADZWA MOYO SYLVESTER MARUMAHOKO Description An account of the resource The government of Zimbabwe has continued with the economic management of protectionism since independence in 1980, which was being used by the former colonial government. The new black government embarked on huge expenditure on capital (infrastructure) such as roads, schools and hospitals and this drove up government spending against government revenue. Despite efforts to optimise revenue, the nation’s socio-economic conditions have worsened and are marked by a high inflationary environment, low utilisation of industrial capacity and decreases in Gross Domestic Product (GDP). The financial flexibility is limited due to weak tax revenue performance amidst increasing current spending and a shrinking tax foundation. Poor revenue collections from the formal economy have compelled the government to resort to the taxation of the informal economy, but the big challenge is that the government seems reluctant to embrace technology for the taxation in this sector, yet technology has already advanced such that developing countries are already embracing emerging technology like Artificial Intelligence (AI) and Machine Learning (ML) in revenue management. The research aims to evaluate the revenue structure in Zimbabwe, challenges affecting revenue generation in Zimbabwe and the role of AI in revenue optimisation. The research made use of extant qualitative research methods. Research findings indicate that revenue generation in Zimbabwe is mostly affected by complex tax system, capacity constraints, smuggling, corruption, low tax morale, inadequate information and inadequate checks and balance. The role of AI in revenue optimisation includes revenue forecasting, assessing economic conditions, real time policy adjustments, detecting fraud and corruption, identifying tax inefficiencies and optimizing resource allocation. It can be concluded that, by employing AI-driven predictive models, the government can allocate tax revenue more precisely to fund infrastructure projects, such as healthcare facilities, schools and roads, ultimately improving living standards and economic outcomes in underdeveloped regions. Publisher An entity responsible for making the resource available ZIMBABWE JOURNAL OF BUSINESS, ECONOMICS AND MANAGEMENT Date A point or period of time associated with an event in the lifecycle of the resource 2025 Artificial Intelligence Public Finance Revenue Taxation