What We Do Not Know: GPT Use in Business and Management

• URL: http://arxiv.org/abs/2504.05273v1
• Date: Mon, 07 Apr 2025 17:11:53 GMT
• Title: What We Do Not Know: GPT Use in Business and Management
• Authors: Tammy Mackenzie, Branislav Radeljic, Leslie Salgado, Animesh Paul, Rubaina Khan, Aizhan Tursunbayeva, Natalie Perez, Sreyoshi Bhaduri,
• Abstract summary: This systematic review examines peer-reviewed studies on application of GPT in business management.<n>We provide a description of current research and identify knowledge gaps on the use of GPT in business.<n>We discuss gaps in knowledge of GPT potential consequences on employment, productivity, environmental costs, oppression, and small businesses.
• Score: 0.0
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: This systematic review examines peer-reviewed studies on application of GPT in business management, revealing significant knowledge gaps. Despite identifying interesting research directions such as best practices, benchmarking, performance comparisons, social impacts, our analysis yields only 42 relevant studies for the 22 months since its release. There are so few studies looking at a particular sector or subfield that management researchers, business consultants, policymakers, and journalists do not yet have enough information to make well-founded statements on how GPT is being used in businesses. The primary contribution of this paper is a call to action for further research. We provide a description of current research and identify knowledge gaps on the use of GPT in business. We cover the management subfields of finance, marketing, human resources, strategy, operations, production, and analytics, excluding retail and sales. We discuss gaps in knowledge of GPT potential consequences on employment, productivity, environmental costs, oppression, and small businesses. We propose how management consultants and the media can help fill those gaps. We call for practical work on business control systems as they relate to existing and foreseeable AI-related business challenges. This work may be of interest to managers, to management researchers, and to people working on AI in society.

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