Generative AI for decision-making: A multidisciplinary perspective

Abstract

Generative artificial intelligence (GenAI) is rapidly reshaping decision-making across multiple domains, including health, law, business, education, and tourism. This study synthesizes the fragmented research on GenAI to provide a comprehensive framework for understanding its role in enhancing decision-making accuracy, efficiency, and personalization. Employing a systematic literature review and thematic analysis, this study categorizes diverse applications, from clinical diagnostics and legal reasoning to financial advisement and educational support, highlighting both innovative practices and persistent challenges. The analysis of 101 articles reveals that, while GenAI significantly improves data processing and decision support, mitigating issues such as inherent bias, misinformation, and transparency deficits requires careful attention. The integration of multi-agent frameworks and human oversight is critical for ensuring ethical and reliable outcomes. Ultimately, this synthesis highlights the transformative potential of GenAI as a decision-making tool by presenting a cross-disciplinary framework that reveals its impact and uncovers gaps across various domains. The study also advocates the development of robust regulatory and technological strategies to harness the benefits and address the limitations of GenAI.

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