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Trust in artificial intelligence for its adoption and use in organisational decision-making

Mini Dissertation (MPhil (Corporate Strategy))--University of Pretoria, 2024.

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Other Authors: Bogie, Jill
Format: Thesis
Language:English
Published: University of Pretoria 2025
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access_status_str Open Access
author2 Bogie, Jill
author_browse Bogie, Jill
author_facet Bogie, Jill
collection Thesis
dc_rights_str_mv © 2024 University of Pretoria. All rights reserved. The copyright in this work vests in the University of Pretoria. No part of this work may be reproduced or transmitted in any form or by any means, without the prior written permission of the University of Pretoria.
description Mini Dissertation (MPhil (Corporate Strategy))--University of Pretoria, 2024.
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institution University of Pretoria (South Africa)
language English
last_indexed 2026-06-10T12:37:23.532Z
license_str Other — see source repository
provenance_str_mv Harvested via OAI-PMH from UPSpace — University of Pretoria Institutional Repository
publishDate 2025
publishDateRange 2025
publishDateSort 2025
publisher University of Pretoria
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spelling oai:repository.up.ac.za:2263/101685 Trust in artificial intelligence for its adoption and use in organisational decision-making Bogie, Jill ichelp@gibs.co.za Hulme-Jones, Graeme Edward UCTD Artificial intelligence (AI) Trust in AI Explainable AI xAI Transparency Adoption and use Mini Dissertation (MPhil (Corporate Strategy))--University of Pretoria, 2024. Considering the recent developments and mainstream attention on Artificial Intelligence, organisations are facing increased pressure to realise the potential benefits which this new generation of tools and techniques seek to unlock. However, to responsibly leverage and benefit from the advantages which AI promises to offer, those responsible for decision-making in organisations need to be willing to trust the technology. For these reasons, this qualitative research study focused on trust in artificial intelligence for its adoption and use in organisational decision-making, and the key related concepts of explainable AI (xAI) and transparency. The theoretical relevance of this research was to develop insights into, and new understanding of how trust in AI is formed for decision-making in organisations, as well as to reveal new insights and understanding of the relationship between the key concepts of xAI and transparency which lead to trust in AI. The study followed a qualitative, exploratory design with a phenomenological approach, to explore the lived experiences of the research phenomena from the perspective of individuals responsible for organisational decision-making. A total of 19 semi-structured interviews were conducted, with participants who were exposed to or had experience of Artificial Intelligence and its impact on their organisations. The participants were drawn from a setting of worldwide organisations, across 16 diverse sectors, from healthcare and financial services to defence and aviation. Rich insights and understanding of the main theoretical concepts and research phenomena were revealed through a systematic, thematic analysis. Several similarities were identified between the findings of the study and the literature, adding to the theoretical body of knowledge, while eight nuances of difference provided potential refinements, and three distinct differences highlighted potential extensions. Lastly, a conceptual framework was developed and refined through each stage of the research, culminating in a view of the potential research contributions in relation to extant theory. The research outcomes extended the theoretical understanding of trust formation in AI, for its adoption and use in organisational decision-making environments, while leading to actionable insights for organizations aiming to build trust in AI technologies. Gordon Institute of Business Science (GIBS) MPhil (Corporate Strategy) Unrestricted Gordon Institute of Business Science (GIBS) SDG-09: Industry, innovation and infrastructure 2025-03-25T08:13:51Z 2025-03-25T08:13:51Z 2025-05-05 2024-11 Mini Dissertation * A2025 http://hdl.handle.net/2263/101685 en © 2024 University of Pretoria. All rights reserved. The copyright in this work vests in the University of Pretoria. No part of this work may be reproduced or transmitted in any form or by any means, without the prior written permission of the University of Pretoria. application/pdf University of Pretoria
spellingShingle UCTD
Artificial intelligence (AI)
Trust in AI
Explainable AI
xAI
Transparency
Adoption and use
Trust in artificial intelligence for its adoption and use in organisational decision-making
title Trust in artificial intelligence for its adoption and use in organisational decision-making
title_full Trust in artificial intelligence for its adoption and use in organisational decision-making
title_fullStr Trust in artificial intelligence for its adoption and use in organisational decision-making
title_full_unstemmed Trust in artificial intelligence for its adoption and use in organisational decision-making
title_short Trust in artificial intelligence for its adoption and use in organisational decision-making
title_sort trust in artificial intelligence for its adoption and use in organisational decision making
topic UCTD
Artificial intelligence (AI)
Trust in AI
Explainable AI
xAI
Transparency
Adoption and use
url http://hdl.handle.net/2263/101685