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The impact of socio-materiality and AI technology adoption within the manufacturing industry
Mini Dissertation (MBA)--University of Pretoria, 2024.
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| Other Authors: | |
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| Format: | Thesis |
| Language: | English |
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University of Pretoria
2025
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| _version_ | 1867613500426158080 |
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| access_status_str | Open Access |
| author2 | Balkissoon, Rishal |
| author_browse | Balkissoon, Rishal |
| author_facet | Balkissoon, Rishal |
| 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 (MBA)--University of Pretoria, 2024. |
| format | Thesis |
| id | oai:repository.up.ac.za:2263/102031 |
| institution | University of Pretoria (South Africa) |
| language | English |
| last_indexed | 2026-06-10T12:37:08.286Z |
| 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 |
| publisherStr | University of Pretoria |
| record_format | dspace |
| source_str | UPSpace — University of Pretoria Institutional Repository |
| spelling | oai:repository.up.ac.za:2263/102031 The impact of socio-materiality and AI technology adoption within the manufacturing industry Balkissoon, Rishal ichelp@gibs.co.za Naidoo, Nishen UCTD Artificial intelligence (AI) Embedded technologies Mini Dissertation (MBA)--University of Pretoria, 2024. Artificial intelligence (AI) embedded technologies are becoming a trend in the fourth Industrial revolution. These technologies are known for bringing groundbreaking efficiencies and superior quality to the products being produced in South Africa’s manufacturing industry. With evidence of South Africa’s high unemployment rate and low skilled workforce the operationalising of this AI embedded solutions strategy has become a challenge. The researcher aims to collect qualitative data through semi-structures interviews from the manufacturing sectors leadership to understand their challenges and use this data to form strategic actions to ease the implementation of these AI embedded technologies. The researcher will start with desktop research to understand the existing literature and structure this research to solve the gaps that may exist and focus the data collection within the South African Context. The researcher will then find leaders who meet the criteria of possessing experience with these AI embedded technologies. The researcher will then collect the open codes of data from the interviews and fine the axial and selected codes which will allow the themes to emerge. The research will then analyse these themes to understand the effect that the workforce has on the implementation of AI embedded technologies and use this data to form strategic actions to mitigate these risks. Gordon Institute of Business Science (GIBS) MBA Unrestricted Gordon Institute of Business Science (GIBS) SDG-09: Industry, innovation and infrastructure 2025-04-11T09:28:14Z 2025-04-11T09:28:14Z 2025-05-05 2024-11 Mini Dissertation * A2025 http://hdl.handle.net/2263/102031 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) Embedded technologies The impact of socio-materiality and AI technology adoption within the manufacturing industry |
| title | The impact of socio-materiality and AI technology adoption within the manufacturing industry |
| title_full | The impact of socio-materiality and AI technology adoption within the manufacturing industry |
| title_fullStr | The impact of socio-materiality and AI technology adoption within the manufacturing industry |
| title_full_unstemmed | The impact of socio-materiality and AI technology adoption within the manufacturing industry |
| title_short | The impact of socio-materiality and AI technology adoption within the manufacturing industry |
| title_sort | impact of socio materiality and ai technology adoption within the manufacturing industry |
| topic | UCTD Artificial intelligence (AI) Embedded technologies |
| url | http://hdl.handle.net/2263/102031 |