Harnessing generative AI to drive responsible business research and accelerate social impact

Abstract

Purpose This paper aims to examine how generative artificial intelligence (GenAI) can strengthen the evaluation of responsible business research by identifying work with high potential for social impact in business. It focuses on ChatSDG+RR7, a GenAI tool grounded in the United Nations sustainable development goals (SDGs) and Responsible Research in Business and Management (RRBM)’s seven principles of responsible research. The study explores how AI can support the peer review process in selecting and promoting research that advances meaningful societal outcomes. The question addressed is whether AI can be used effectively to assist in the peer review process. Design/methodology/approach ChatSDG+RR7 was used in the peer review process for the RRBM Honor Roll to evaluate submissions based on their alignment with responsible research standards. The study used a comparative design to examine the reliability and rigor of AI-only, human-only and AI–human collaborative evaluations of responsible business research. Findings ChatSDG+RR7 enhanced the human-only peer review process by increasing consistency, reducing bias and improving efficiency. It delivered more standards-based and comprehensive assessments. AI assistance more effectively identifies and promotes responsible research focused on advancing social impact in business than human-only evaluations. Originality/value This study offers new insights into how AI can strengthen peer review by assessing the substantiveness of a paper’s social impact focus. It introduces a novel AI tool that enhances the visibility of responsible research and supports scholars and institutions in aligning academic work with meaningful societal and global challenges.

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