Generative artificial intelligence in management research: a practical guide on mistakes to avoid

Abstract Integrating generative artificial intelligence (AI) into academic research has opened new horizons for enhancing efficiency, accuracy, and innovation in the research process. While recent reviews, conceptualizations, and editorials highlight the potential or provide policy views, we want to give a practical guide on using generative AI in management research and which pitfalls to avoid. We offer five practical tips on what to avoid when using generative AI during the research process. Further, we provide practical guidelines, highlighting AI’s limitations and attempting to provide an outlook on each stage. In doing so, we provide comprehensive guidance on the promises and pitfalls for researchers seeking to leverage AI in the research process.