A literature review of artificial intelligence research in business and management using machine learning and ChatGPT

Aug 3, 2026

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This paper investigates applying AI models and topic modelling techniques to enhance computational literature reviews in business, management, and information systems. The study emphasizes the importance of impactful journals and the need for interdisciplinary research, particularly for addressing AI’s ethical and regulatory challenges. It demonstrates that machine learning can identify research topics, while ChatGPT supports topic labelling, content generation, and more efficient academic writing. By combining methods, the research uncovers thematic structures, reveals gaps, highlights emerging areas, and proposes a methodology for selecting influential papers to bridge computational and traditional reviews.

LanguageEnglish

CategoryResearch & Report

FormatPDF

Pages26

Reading Time1 h 6 min

AccessFree to download

Introduction

Background on AI in business and management

Capabilities of machine learning and large language models

Opportunities and risks for organizations and society

A literature review of artificial intelligence research in business and management using machine learning and ChatGPT Author: Guler, N ; Kirshner, SN; Vidgen , R Publication details: Data and Information Management v. 8 Chapter No. 3 2543-9251 (ISSN) Publication Date: 2024-09-01 Publisher DOI: [https://doi.org/10.1016/j.dim.2024.100076](https://doi.org/10.1016/j.dim.2024.100076) License: [https://creativecommons.org/licenses/by/4.0/](https://creativecommons.org/licenses/by/4.0/) Link to license to see what you are allowed to do with this resource. Downloaded from [http://hdl.handle. net/1959.4/103460](http://hdl.handle. net/1959.4/103460) in [https://](https://)[ ](https://)[unsworks. unsw.edu.au](unsworks. unsw.edu.au) on 2025-04-18 8 (2024) 100076 Contents lists available at ScienceDirect Data and Information Management journal [homepage: www.journals.elsevier.com/data-and-information-management](homepage: www.journals.elsevier.com/data-and-information-management) | A literature review of artificial intelligence research in business and management using machine learning and ChatGPT
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Nazmiye Guler, Samuel N. Kirshner
University of New South Wales Business School, Sydney, 2052, Australia | | | | | --- | --- | --- | --- | | Richard Vidgen
University of New South Wales Business School, Sydney, 2052, Australia University of Hull, School of Management, Hull, HU6 7RX, UK | | | | | A R T I C L E I N F O | | A B S T R A C T | | | Keywords:
Artificial intelligence
Machine learning
Topic modelling Computational literature reviews ChatGPT | | This paper investigates applying AI models and topic modelling techniques to enhance computational literature reviews in business, management, and information systems. The study highlights the significance of impactful journals and emphasises the need for interdisciplinary and transdisciplinary research, especially in addressing AI’s ethical and regulatory challenges. We demonstrate the effectiveness of combining machine learning and ChatGPT in the literature review process. Machine learning is used to identify research topics, and ChatGPT assists researchers in labelling the topics, generating content, and improving the efficiency of academic writing. By leveraging topic modelling techniques and ChatGPT, we uncover and label topics within the literature, shedding light on the thematic structure and content of the research field, allowing researchers to uncover meaningful insights, identify research gaps, and highlight rapidly expanding research areas. Additionally, we contribute to the literature review process by introducing a methodology that identifies impactful papers, helping to bridge the gap between computational literature reviews and traditional literature reviews. | | 1. Introduction Artificial Intelligence (AI) has emerged as a disruptive force, transforming industries, reshaping our lives and work, and significantly impacting businesses, institutions, and societies. Driven by advancements in machine learning and deep learning, as well as the exponential growth of available data, AI technologies have enabled machines to handle complex tasks such as natural language processing, image recognition, and decision-making (Brynjolfsson & Mcafee, 2014; Jordan & Mitchell, 2015; Shollo et al., 2022). AI’s rapid evolution has led to its widespread adoption, with applications ranging from automating mundane tasks to enhancing productivity and enabling new forms of human-computer collaboration across various sectors, including healthcare, finance, manufacturing, and education (Agrawal et al., 2019; Autor, 2015, pp. 237–260; Chui et al., 2018; Dwivedi et al., 2021). The technology offers significant potential for businesses and society by improving efficiency, reducing costs, and providing better decision-making capabilities (Dwivedi et al., 2023; Ransbotham et al., 2017). Combined with big data, AI has the potential to surpas

FAQs

How does the paper use machine learning in the literature review process?

Machine learning is used to identify and extract research topics from the literature. It helps reveal the field’s thematic structure.

What role does ChatGPT play in this review methodology?

ChatGPT assists researchers by labelling topics, generating content, and improving the efficiency of academic writing.

Which challenges does the paper highlight regarding AI adoption?

The paper discusses organizational concerns such as job displacement and algorithmic bias, along with societal risks including privacy invasion and manipulation of public opinion.

Aug 3, 2026

Upload by Miles