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

Abstract

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.