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ChatGPT in business analysis : a human-AI collaboration perspective on augmentation and professional practice

Dissertation (MIT (Information Systems))--University of Pretoria, 2025.

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Other Authors: Weilbach, Lizette
Format: Thesis
Language:English
Published: University of Pretoria 2026
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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, 2025.
format Thesis
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institution University of Pretoria (South Africa)
language English
last_indexed 2026-06-10T12:39:12.888Z
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:2263/108491 ChatGPT in business analysis : a human-AI collaboration perspective on augmentation and professional practice Weilbach, Lizette rockyeth@gmail.com Abbas, Rocky UCTD Sustainable Development Goals (SDGs) Generative AI (GenAI) Business Analysis ChatGPT Human-AI Collaboration (HAC) Professional practice Dissertation (MIT (Information Systems))--University of Pretoria, 2025. The growing presence of generative artificial intelligence tools such as ChatGPT is reshaping professional work practices, yet there is still limited empirical evidence on how they are used in business analysis. While organizations are rapidly adopting AI technologies, little is known about how business analysts (BAs) integrate ChatGPT into their daily activities, the value it offers, and the challenges it presents. This is critical, business analysis relies on human judgment, contextual understanding, and ethical responsibility. The rise of GenAI therefore raises questions about trust, accountability, and professional competence, making it essential to understand how BAs navigate its use in practice. To address this problem, the study adopted a qualitative research approach. Fourteen BAs, across sectors including finance, logistics, healthcare, mining, and government, were interviewed using semi-structured interviews. Data-analysis followed a two-phase process: first, a deductive thematic analysis guided by the research questions, and second, the application of the Human-AI Collaboration (HAC) lens to interpret the findings. Results show that BAs mainly use ChatGPT as a support tool for routine and low-risk tasks such as drafting documents, summarizing information, clarifying language, and generating initial ideas. Reported benefits include time savings, improved clarity, and reduced mental effort. However, key limitations involve accuracy, lack of real time data, weak contextual awareness, and limited domain knowledge. Trust in ChatGPT varied with task risk, and BAs consistently retained final control over outputs, especially in regulated or high stakes contexts. Ethical concerns around data privacy, accountability, and compliance also influenced usage. Overall, ChatGPT’s role remains within automation and augmentation, rather than collaboration. While it enhances efficiency and supports analytical work, it does not replace the core human dimensions of business analysis. Effective use of GenAI therefore depends on strong human oversight, ethical awareness, and adaptive judgment. Future BAs will need to combine analytical expertise with AI literacy and governance awareness to ensure that automation strengthens, rather than weakens, professional value. Informatics MIT (Information Systems) Unrestricted Faculty of Engineering, Built Environment and Information Technology SDG-09: Industry, innovation and infrastructure SDG-08: Decent work and economic growth 2026-02-20T07:36:23Z 2026-02-20T07:36:23Z 2026-05 2025 Dissertation * A2026 http://hdl.handle.net/2263/108491 10.25403/UPresearchdata.31366303 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 AI (GenAI)
Business Analysis
ChatGPT
Human-AI Collaboration (HAC)
Professional practice
ChatGPT in business analysis : a human-AI collaboration perspective on augmentation and professional practice
title ChatGPT in business analysis : a human-AI collaboration perspective on augmentation and professional practice
title_full ChatGPT in business analysis : a human-AI collaboration perspective on augmentation and professional practice
title_fullStr ChatGPT in business analysis : a human-AI collaboration perspective on augmentation and professional practice
title_full_unstemmed ChatGPT in business analysis : a human-AI collaboration perspective on augmentation and professional practice
title_short ChatGPT in business analysis : a human-AI collaboration perspective on augmentation and professional practice
title_sort chatgpt in business analysis a human ai collaboration perspective on augmentation and professional practice
topic UCTD
Sustainable Development Goals (SDGs)
Generative AI (GenAI)
Business Analysis
ChatGPT
Human-AI Collaboration (HAC)
Professional practice
url http://hdl.handle.net/2263/108491