Generative AI for Methodological Contributions in Information Systems Research

Generative AI models such as ChatGPT have gained widespread popularity for performing a variety of business tasks, demonstrating exemplary capabilities in human-like interactions. However, a central question remains: To what extent can these models be applied to tasks beyond text summarization, editing, and conversational use? In this study, we examine the application of Generative AI models to non-writing tasks, focusing specifically on their role in supporting research and scholarship in the field of information systems. We explore how these models can enhance research methodologies and enable scholars to address questions that were previously difficult to tackle. To investigate this, we analyzed recently published articles in leading information systems journals and assessed how Generative AI models have influenced research methods and contributed to the advancement of the field.

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Publication Details

Journal
Journal of the Association for Information Systems
Published
2025-08-15
Primary Topic
Particle accelerators and beam dynamics
Type
article
Field-Weighted Citation Impact
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article

Generative AI for Methodological Contributions in Information Systems Research

Journal of the Association for Information Systems
Particle accelerators and beam dynamics
article

Generative AI for Methodological Contributions in Information Systems Research

article en

Abstract

Generative AI models such as ChatGPT have gained widespread popularity for performing a variety of business tasks, demonstrating exemplary capabilities in human-like interactions. However, a central question remains: To what extent can these models be applied to tasks beyond text summarization, editing, and conversational use? In this study, we examine the application of Generative AI models to non-writing tasks, focusing specifically on their role in supporting research and scholarship in the field of information systems. We explore how these models can enhance research methodologies and enable scholars to address questions that were previously difficult to tackle. To investigate this, we analyzed recently published articles in leading information systems journals and assessed how Generative AI models have influenced research methods and contributed to the advancement of the field.

Journal of the Association for Information Systems
Louisiana State University (US)
Quality Education
Openalex Percentile: Top 35%
Particle accelerators and beam dynamics
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Generative AI for Methodological Contributions in Information Systems Research · Journal of the Association for Information Systems (2025) | TGRS Research Map | TGRS