Artificial Intelligence Affordances for Organisational Change: Perspectives from South African Artificial Intelligence Practitioners

dc.contributor.advisorBrown, Irwin
dc.contributor.authorAchmat, Luqman
dc.date.accessioned2024-03-28T09:38:09Z
dc.date.available2024-03-28T09:38:09Z
dc.date.issued2023
dc.date.updated2024-03-28T08:21:19Z
dc.description.abstractArtificial intelligence (AI) technologies have been in use for several decades, but have seen substantial growth and commercialisation in the last decade, largely due to the available and growing ubiquitous access to more affordable computing resources. While some organisations have adopted these technologies fairly quickly, others grapple with understanding how these technologies would strategically benefit the organisation. The purpose of this research is to address this gap by theorising how AI could be positioned to influence strategic organisational change. It does so by delineating the AI features and drawing on affordance theory to explicitly identify the affordances, the types of organisational change and the constraining conditions under which such AI-related affordances may influence organisational change. This qualitative study adopts an interpretive epistemology, while lending itself towards a constructivist ontology. By adopting a qualitative interview strategy for data collection, and a thematic analysis to analyse the data, this study abductively theorises how AI affords organisational change from the perspective of the AI practitioner. It uses the Trajectory of Affordances as the underpinning lens to explore this phenomenon. Eight key affordances are identified: (i) Analysing risk, (ii) analysing needs, (iii) forecasting, (iv) assessing efficiency and effectiveness, (v) providing prediction criteria, (vi) translating information, (vii) tailoring information, and (viii) improving predictability as an affordance that results from an outcome or organisational change influenced by one or more of the other affordances.
dc.identifier.apacitationAchmat, L. (2023). <i>Artificial Intelligence Affordances for Organisational Change: Perspectives from South African Artificial Intelligence Practitioners</i>. (). ,Faculty of Commerce ,Department of Information Systems. Retrieved from http://hdl.handle.net/11427/39269en_ZA
dc.identifier.chicagocitationAchmat, Luqman. <i>"Artificial Intelligence Affordances for Organisational Change: Perspectives from South African Artificial Intelligence Practitioners."</i> ., ,Faculty of Commerce ,Department of Information Systems, 2023. http://hdl.handle.net/11427/39269en_ZA
dc.identifier.citationAchmat, L. 2023. Artificial Intelligence Affordances for Organisational Change: Perspectives from South African Artificial Intelligence Practitioners. . ,Faculty of Commerce ,Department of Information Systems. http://hdl.handle.net/11427/39269en_ZA
dc.identifier.ris TY - Thesis / Dissertation AU - Achmat, Luqman AB - Artificial intelligence (AI) technologies have been in use for several decades, but have seen substantial growth and commercialisation in the last decade, largely due to the available and growing ubiquitous access to more affordable computing resources. While some organisations have adopted these technologies fairly quickly, others grapple with understanding how these technologies would strategically benefit the organisation. The purpose of this research is to address this gap by theorising how AI could be positioned to influence strategic organisational change. It does so by delineating the AI features and drawing on affordance theory to explicitly identify the affordances, the types of organisational change and the constraining conditions under which such AI-related affordances may influence organisational change. This qualitative study adopts an interpretive epistemology, while lending itself towards a constructivist ontology. By adopting a qualitative interview strategy for data collection, and a thematic analysis to analyse the data, this study abductively theorises how AI affords organisational change from the perspective of the AI practitioner. It uses the Trajectory of Affordances as the underpinning lens to explore this phenomenon. Eight key affordances are identified: (i) Analysing risk, (ii) analysing needs, (iii) forecasting, (iv) assessing efficiency and effectiveness, (v) providing prediction criteria, (vi) translating information, (vii) tailoring information, and (viii) improving predictability as an affordance that results from an outcome or organisational change influenced by one or more of the other affordances. DA - 2023 DB - OpenUCT DP - University of Cape Town KW - Information System LK - https://open.uct.ac.za PY - 2023 T1 - ETD: Artificial Intelligence Affordances for Organisational Change: Perspectives from South African Artificial Intelligence Practitioners TI - ETD: Artificial Intelligence Affordances for Organisational Change: Perspectives from South African Artificial Intelligence Practitioners UR - http://hdl.handle.net/11427/39269 ER - en_ZA
dc.identifier.urihttp://hdl.handle.net/11427/39269
dc.identifier.vancouvercitationAchmat L. Artificial Intelligence Affordances for Organisational Change: Perspectives from South African Artificial Intelligence Practitioners. []. ,Faculty of Commerce ,Department of Information Systems, 2023 [cited yyyy month dd]. Available from: http://hdl.handle.net/11427/39269en_ZA
dc.language.rfc3066eng
dc.publisher.departmentDepartment of Information Systems
dc.publisher.facultyFaculty of Commerce
dc.subjectInformation System
dc.titleArtificial Intelligence Affordances for Organisational Change: Perspectives from South African Artificial Intelligence Practitioners
dc.typeThesis / Dissertation
dc.type.qualificationlevelMasters
dc.type.qualificationlevelMCom
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