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A framework to understand the role of generative AI to enhance customer experience and personalisation in marketing
Dissertation (MIT (Information Systems))--University of Pretoria, 2026.
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| Format: | Thesis |
| Language: | English |
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University of Pretoria
2026
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| _version_ | 1867613506274066432 |
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| access_status_str | Open Access |
| author2 | Weilbach, Lizette |
| author_browse | Weilbach, Lizette |
| author_facet | Weilbach, Lizette |
| 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 | Dissertation (MIT (Information Systems))--University of Pretoria, 2026. |
| format | Thesis |
| id | oai:repository.up.ac.za:2263/108511 |
| institution | University of Pretoria (South Africa) |
| language | English |
| last_indexed | 2026-06-10T12:37:13.890Z |
| license_str | Other — see source repository |
| provenance_str_mv | Harvested via OAI-PMH from UPSpace — University of Pretoria Institutional Repository |
| publishDate | 2026 |
| publishDateRange | 2026 |
| publishDateSort | 2026 |
| 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:2263/108511 A framework to understand the role of generative AI to enhance customer experience and personalisation in marketing Weilbach, Lizette u17031690@tuks.co.za Coetzer, Willem Adriaan UCTD Sustainable Development Goals (SDGs) Generative artificial intelligence (GenAI) Customer experience Personalisation Marketing Dissertation (MIT (Information Systems))--University of Pretoria, 2026. Organisations are trying to utilise Generative Artificial Intelligence (AI) to improve customer experience and personalisation in marketing. However, the lack of clear guidance results in the production of unavoidable risks and inconsistent outcomes. What is missing is a coherent, evidence-based framework that guides the understanding of the role of generative AI to enhance customer experience and personalisation in marketing. Literature emphasises that personalised, trust-centred stakeholder interactions across service ecosystems result from customer experience advantages. In contrast, the unguided use of generative AI could damage brand trust and fail to deliver any meaningful improvement. This study applied a qualitative research design using semi-structured interviews with 15 marketing professionals The data was analysed though a deductive thematic analysis guided by the Service Dominant Logic (SDL) theory. Eight key themes emerged from the data and were synthesised into a seven-layered framework framework steered by the SDL theoretical lens that clarifies the organisational preconditions, decision-making gates, AI-enabled capabilities, customer touchpoints, experience outcomes, governance controls, and learning feedback loops necessary for value co-creation. The findings reveal that generative AI acts as a process enhancer rather than a stand-alone tool, creating value when foundational enablers are in place and when generative AI implementation initiatives are guided by structured decision gates. The framework operationalises the SDL constructs of value co-creation, service ecosystems, and marketing, within an AI-mediated marketing context, and demonstrates how these concepts can be applied in practice through ethical governance and continuous learning. Practically, the framework provides marketers with a systematic model for responsible generative AI implementation, verifying enablers, applying decision gates, configuring capabilities, aligning touchpoints, measuring value-in-use, and scaling only when outcomes are stable. This research advances understanding by translating SDL principles into actionable guidance for AI-enabled marketing. It shows that generative AI enhances customer experience and personalisation only when it is strategically integrated, ethically governed, and continuously refines within a co-creative service system. Informatics MIT (Information Systems) Unrestricted Faculty of Engineering, Built Environment and Information Technology None 2026-02-20T09:41:40Z 2026-02-20T09:41:40Z 2026-04 2026 Dissertation * A2026 http://hdl.handle.net/2263/108511 10.6084/m9.figshare.31366105 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 Sustainable Development Goals (SDGs) Generative artificial intelligence (GenAI) Customer experience Personalisation Marketing A framework to understand the role of generative AI to enhance customer experience and personalisation in marketing |
| title | A framework to understand the role of generative AI to enhance customer experience and personalisation in marketing |
| title_full | A framework to understand the role of generative AI to enhance customer experience and personalisation in marketing |
| title_fullStr | A framework to understand the role of generative AI to enhance customer experience and personalisation in marketing |
| title_full_unstemmed | A framework to understand the role of generative AI to enhance customer experience and personalisation in marketing |
| title_short | A framework to understand the role of generative AI to enhance customer experience and personalisation in marketing |
| title_sort | framework to understand the role of generative ai to enhance customer experience and personalisation in marketing |
| topic | UCTD Sustainable Development Goals (SDGs) Generative artificial intelligence (GenAI) Customer experience Personalisation Marketing |
| url | http://hdl.handle.net/2263/108511 |