Faculty of Commerce, Law and Management (ETDs)

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    Factors Influencing Artificial Intelligence Adoption in South African Organisations: A Technology, Organisation, Environment (TOE) Framework
    (University of the Witwatersrand, Johannesburg, 2023) Hoosen, Kaneez Fathima; Cohen, Jason
    Artificial intelligence (AI) refers to the formation of machines that mimic human intelligence and encompasses various technologies. AI technology is changing the landscape for South African organisations and how they operate. Using current literature and other online reports by auditing firms, the study aimed to identify a suite of AI technologies used by South African organisations. Technologies such as robotic process automation, image and speech recognition, machine learning and chatbots were defined. In addition, this research paper investigated the factors influencing AI technology adoption by South African organisations. The technology, organisation and environment factors of the TOE framework were examined to understand adoption decisions. It was important to close this gap as lack of understanding of how factors influence AI decisions, and an undefined suite of AI technologies could impact adoption decisions. A cross sectional relational research design was chosen for the study. A survey instrument was used and administered through a web-survey to 252 IT decision makers or IT leaders from South African organisations who served as key informants for their organisations. Responses were received from 55 organisations. Reliability and validity tests were used to evaluate the consistency and reliability of the data and to evaluate whether measures correctly represent the variables that they intend to measure. Correlation analysis, stepwise and multiple regression were used to test the hypotheses of the conceptual model. It was found that of the suite of AI technologies, robotics process automation followed by machine learning and image recognition had the highest levels of adoption. Results showed that data availability and top management support were supported as the most significant technology, organization, environment (TOE) factors influencing AI technology adoption in South African organisations. It was found that perceived technology benefits, IT infrastructure, resource capability and normative pressure were also strongly correlated to AI technology adoption. Financial resources and competitive pressure were not supported as determinants. Artificial intelligence is receiving much attention in both practice and research. This study addresses the gap in the current body of knowledge on AI adoption in South Africa by making use of the TOE framework to study adoption of artificial intelligence technologies in organisations. Useful insights are provided to South African organisations so that they can benchmark their adoption against other industry players and manage their response to those factors most significant for AI adoption
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    The impact of ICT adoption on business performance among SMEs in South Africa
    (University of the Witswatersrand, Johannesburg, 2023) Manyama, Alson; Msimango-Galawe, Jabulile
    Despite the high rate of ICT adoption in South Africa, little is known about the impact of ICT adoption on business performance among SMEs; thus, a study such as this was necessary to reduce the failure rate of SMEs during their first five years. Design/methodology/approach – In South Africa, SME survey data were collected using purposive sampling, with a sample size of 385, and multiple regression was used for analysis. Findings - H1, H2 & H3 were accepted at p-value < 0.001 statistically significant level. Based on the multiple regression analysis results (R-value = .938; R-square = .966; p-value = 0.001). It is therefore evident that there is a statistically significant relationship between technology, organization and external environmental factors and business performance. Conclusions – The results indicate that technological, organisational, and environmental contexts have direct and statistically significant relationships with business performance. Research limitations/implications – Due to the study's limited scope and phases, additional data are required to apply the findings to other industries/sectors/countries. Implications/practical applications – The study's findings have significant implications for SME managers and owners who are promoting ICT adoption within their organisations. This study seeks to educate managers on the significance of external assistance for small and medium-sized enterprises (SMEs), particularly those lacking the competencies, skills, or an ICT division. Adoption of ICT provides small and medium-sized enterprises with access to real-time data, advanced analytics, and reporting tools. This allows managers to make well-informed decisions based on current and accurate information. In order to capitalize on this advantage, managers should prioritize developing data-driven decision-making capabilities and ensuring that employees have the necessary skills to interpret and analyse data. Originality/value – The paper contributes to the expanding literature on innovation adoption by utilising T- O-E frameworks to explain the technology adoption by SME
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    The adoption of artificial intelligence in financial services in South Africa
    (2022) Qwabaza, Anele
    Artificial intelligence (AI) is one of the driving forces behind disruptive innovations and has transformed how organisations interact and deliver services to their customers. While factors that enable the successful implementation of AI in organisations were previously studied, these studies are still in the early stages. Therefore, the objective of this study was to investigate the success factors for AI adoption by South African financial services companies, using an integration of the diffusion of innovation (DOI) theory and the technology-organisation-environment (TOE) framework. This study also aimed to understand the relative effect of factors affecting AI adoption in financial services in South Africa. The study was administered using an online survey targeting employees of South African financial services organisations. Structural equation modelling (SEM) was used to analyse the data. The results show that only complexity and technical capabilities significantly influenced AI adoption, with managerial capabilities indirectly influencing the adoption of AI in South African financial services. Therefore, when adopting AI in their organisations, the leadership of financial services organisations should consider the costs associated with AI applications, the time taken to innovate using AI, and the application of AI. External environmental factors, government involvement, competitive pressure, and vendor partnerships all had statistically significant results for AI adoption. In addition, this study also aimed to understand the assimilation of AI by customers after adoption by organisations, using the technology acceptance model (TAM). The data was collected using an online survey targeting external customers of financial services organisations, and it was analysed using SEM. The results show that vi perceived ease of use and perceived usefulness are important indicators of how customers experience AI applications of financial services organisations. Therefore, financial services organisations should ensure an optimal level of ease of use and prioritise utilitarian benefits when designing and adopting AI applications.