Mariemuthu, Clayton2020-10-142020-10-142019-02-28Mariemuthu, Clayton O'ryan, (2019). The adoption of artificial intelligence by South African banking firms :a Technology, Organisation and Environment (TOE) framework, University of the Witwatersrand, https://hdl.handle.net/10539/29818https://hdl.handle.net/10539/29818A research report submitted in partial fulfilment of the requirements for the degree of Master of Commerce in the field of Information SystemsArtificial intelligence (AI) is the creation of intelligent machines that have the ability to work and act like humans and comprises various technologies. AI-powered technology is having a transformative effect on industries such as banking. This study investigated the adoption of AI technologies by South African banking firms. The investigation into the factors that explain the current extent of adoption was focused through the lens of the Technological, Organisational and Environmental (TOE) framework. Through a review of existing literature and online resources, this study firstly identified a basket of AI technologies perceived as relevant for South African banking firms. Six technologies that represent the basket of AI technologies were identified, namely: machine learning, robotic process automation, expert systems, virtual assistants, natural language processing, and pattern recognition. Secondly, the study aimed to determine the current state of adoption of the AI technologies. Thirdly, the study aimed to determine the factors influencing the adoption of AI technologies by banking firms. A systematic literature review was undertaken to determine the technological, organisational and environmental factors that influence technology adoption. A model using pre-determined TOE factors was developed and tested. The cross-sectional, quantitative study was undertaken via a self-administered, online questionnaire to a sample of 307 respondents from South African banking business units, resulting in 62 responses. Diffusion curves were used to illustrate the current adoption of AI technologies. The results revealed that robotic process automation is the most diffused technology, while natural language processing was the least diffused technology. The results also revealed a significant intention to adopt AI technologies in the next three years. The data was subjected to reliability and validity tests which established that the construct measures rendered consistent and reproducible results, and accurately depicted the constructs they were assigned to measure. Thereafter, correlations analysis was utilised to test the model’s hypotheses, and a multiple and stepwise regression were used as further tests of the model. Results revealed that AI technology skills, top management support, firm size and competitive pressure were positively related to the adoption of AI technologies, while perceived benefits, information technology infrastructure, cost, competitive pressure, regulation and mimetic pressure were not supported. AI technologies is a contemporary topic and is gathering a great deal of attention in both academia and practice. By applying the TOE framework, this study has provided a theoretical contribution and addressed a research gap in existing literature, specifically demonstrating that AI adoption is a function of all three contexts, i.e. technological, organisational and environmental. This study also provides a practical contribution for banking firms as they can understand the current adoption status of the average South African bank. Furthermore, for firms considering the adoption of AI technologies, this study offers insights into the relative influence of the TOE factors, and provides guidance to facilitate benchmarking and processes of adoption.Online resource (125 leaves)enBanks and banking, Mobile--South AfricaBanks and banking--South AfricaTechnological innovationsThesis