Behavioral economics, artificial intelligence and entrepreneurship: an updated framework for management

Abstract Behavioral Economics, artificial intelligence (AI), and Entrepreneurship have emerged as critical fields reshaping contemporary management practices. This article explores the connections between these disciplines to propose an updated framework for entrepreneurship management. To achieve this, a systematic literature review was conducted, complemented by a Latent Dirichlet Allocation (LDA) topic modeling algorithm developed in Python to identify thematic patterns across the selected corpus. The findings reveal eight key topics linked to these fields, including strategic management, decision-making, and innovation, highlighting their interrelations through AI integration. Specifically, positive correlations between innovation, market dynamics, and risk management emphasize AI’s potential to enhance entrepreneurial decision-making and market adaptability. Also, behavioral insights further underpin these themes, showcasing AI’s capacity to address cognitive biases and optimize management strategies. Additionally, this study proposes eight research propositions to guide future investigations in this field that align with the identified topics, offering novel theoretical perspectives and practical applications that set an updated framework for management practices. The findings provide entrepreneurs with strategic guidance for leveraging these areas to advance innovation, enhance adaptive decision-making, and promote sustainable management practices within dynamic ecosystems shaped by the growing influence of AI and behavioral economics on managerial frameworks, which capitalize on a deeper understanding of human behavior.