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This study explores how artificial intelligence (AI) can mitigate cognitive biases in entrepreneurial decision making, such as affect, availability, and representativeness heuristics, overconfidence, escalation of commitment, planning fallacy, and illusion of control. These biases often impair judgment, especially in uncertain environments. By leveraging AI tools that provide data-driven insights, predictive analytics, and real-time feedback, the research highlights AI’s potential to improve decision quality and foster rational risk assessment. Using self-regulation theory, the study examines how shared beliefs within entrepreneurial setups influence AI adoption. It identifies a research gap in understanding the long-term effects of AI on bias reduction and the role of social contexts in shaping its acceptance. Our suggestions highlight that AI can challenge entrenched mental models and emotional heuristics, enhancing decision outcomes. Last, this study offers conceptual understandings and practical implications for entrepreneurs, advocating a balanced integration of AI with human judgment to support sustainable and informed business practices.
Khakwani et al. (Thu,) studied this question.