Impact of AI on SME'S in Developing Countries: A case of Limpopo Province, South Africa
| dc.contributor.advisor | Madzvamuse, S. | |
| dc.contributor.advisor | Nekhavhambe, N. | |
| dc.contributor.author | Chitara, Humen Farook | |
| dc.date | 2026 | |
| dc.date.accessioned | 2026-09-23T07:57:16Z | |
| dc.date.issued | 2026-09 | |
| dc.description | M. Com in Business Information Systems | |
| dc.description | Department of Business Information Systems | |
| dc.description.abstract | Artificial intelligence (AI) is rapidly revolutionizing company operations across industries by improving decision-making, increasing operational efficiency, and generating competitive advantages. While AI use has increased rapidly in developed economies, its use by Small and Medium-sized Enterprises (SMEs) in underdeveloped countries is restricted and underexplored. This study investigates the impact of AI on SME performance in Limpopo Province, South Africa, with a focus on identifying the technological, organisational, and environmental factors influencing its adoption. Although SMEs play a vital role in economic development and employment creation, they often face challenges such as limited infrastructure, low digital literacy, financial constraints, and inadequate institutional support that hinder effective AI integration. Grounded in the Technology–Organisation–Environment (TOE) framework and the Diffusion of Innovation (DOI) theory, this study employs a mixed-methods approach within the pragmatist paradigm to provide a comprehensive understanding of the dynamics of AI adoption. A sequential explanatory design is used, with the quantitative phase testing hypotheses drawn from the conceptual framework. This phase investigates how variables such as Relative Advantage, Complexity, Top Management Support, Financial Readiness, External Support, and Competitive Pressure influence SME performance. This paper combines theoretical insights with facts to create practical policy guidelines to encourage AI adoption by SMEs. The findings demonstrate that AI adoption positively influences SME performance, while also highlighting context-specific challenges unique to developing-country environments. The research offers practical recommendations for policymakers, institutions, and business leaders to foster inclusive AI adoption in developing countries like South Africa. | |
| dc.identifier.apacitation | Chitara, H. F. (2026). <i>Impact of AI on SME'S in Developing Countries: A case of Limpopo Province, South Africa</i>. (). . Retrieved from | en_ZA |
| dc.identifier.chicagocitation | Chitara, Humen Farook. <i>"Impact of AI on SME'S in Developing Countries: A case of Limpopo Province, South Africa."</i> ., , 2026. | en_ZA |
| dc.identifier.citation | Chitara, H.F. 2026. Impact of AI on SME'S in Developing Countries: A case of Limpopo Province, South Africa. . . | en_ZA |
| dc.identifier.ris | TY - Dissertation AU - Chitara, Humen Farook AB - Artificial intelligence (AI) is rapidly revolutionizing company operations across industries by improving decision-making, increasing operational efficiency, and generating competitive advantages. While AI use has increased rapidly in developed economies, its use by Small and Medium-sized Enterprises (SMEs) in underdeveloped countries is restricted and underexplored. This study investigates the impact of AI on SME performance in Limpopo Province, South Africa, with a focus on identifying the technological, organisational, and environmental factors influencing its adoption. Although SMEs play a vital role in economic development and employment creation, they often face challenges such as limited infrastructure, low digital literacy, financial constraints, and inadequate institutional support that hinder effective AI integration. Grounded in the Technology–Organisation–Environment (TOE) framework and the Diffusion of Innovation (DOI) theory, this study employs a mixed-methods approach within the pragmatist paradigm to provide a comprehensive understanding of the dynamics of AI adoption. A sequential explanatory design is used, with the quantitative phase testing hypotheses drawn from the conceptual framework. This phase investigates how variables such as Relative Advantage, Complexity, Top Management Support, Financial Readiness, External Support, and Competitive Pressure influence SME performance. This paper combines theoretical insights with facts to create practical policy guidelines to encourage AI adoption by SMEs. The findings demonstrate that AI adoption positively influences SME performance, while also highlighting context-specific challenges unique to developing-country environments. The research offers practical recommendations for policymakers, institutions, and business leaders to foster inclusive AI adoption in developing countries like South Africa. DA - 2026-09 DB - ResearchSpace DP - Univen KW - Artificial intelligence KW - SME'S KW - Developing countries KW - South Africa KW - AI Adoption KW - TOE-DOI framework KW - SME Performance LK - https://univendspace.univen.ac.za PY - 2026 T1 - Impact of AI on SME'S in Developing Countries: A case of Limpopo Province, South Africa TI - Impact of AI on SME'S in Developing Countries: A case of Limpopo Province, South Africa UR - ER - | en_ZA |
| dc.identifier.uri | https://hdl.handle.net/11602/3527 | |
| dc.identifier.vancouvercitation | Chitara HF. Impact of AI on SME'S in Developing Countries: A case of Limpopo Province, South Africa. []. , 2026 [cited yyyy month dd]. Available from: | en_ZA |
| dc.language.iso | en | |
| dc.relation.requires | ||
| dc.rights | University of Venda | |
| dc.subject | Artificial intelligence | |
| dc.subject | UCTD | en_ZA |
| dc.subject | Developing countries | |
| dc.subject | South Africa | |
| dc.subject | AI Adoption | |
| dc.subject | TOE-DOI framework | |
| dc.subject | SME Performance | |
| dc.title | Impact of AI on SME'S in Developing Countries: A case of Limpopo Province, South Africa | |
| dc.type | Dissertation |
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