Entrepreneurial decision-making in the age of AI: Sector knowledge at the balance of intuition and analysis

Artificial intelligence (AI) is shaping entrepreneurial decision making today, increasingly informing opportunities recognition, assessment, and exploitation. Yet prior sector knowledge of entrepreneurs remains a fundamental pillar in these cognitive activities, providing the experiential schemas and contextual understanding that anchor entrepreneurial judgment. This study examines the interaction between two forces – AI-driven analysis and sector knowledge – and their influence on entrepreneurial outcomes, encompassing the recognition, assessment, and exploitation of opportunities. Using a controlled laboratory experiment with 124 entrepreneurs, we manipulate AI usage and measure prior sector knowledge to identify the independent and joint effects of these factors on entrepreneurial decision outcomes. Results show that AI increases the number of opportunities recognized and enhances the depth of opportunity assessment, exploitation, and contextual understanding. At the same time, AI reduces novelty in recognition and innovation in exploitation. Sector knowledge restores this creative dimension, enabling entrepreneurs to integrate intuitive insights with AI-supported deliberation. Entrepreneurs who combine AI and expertise achieve the most balanced outcomes, excelling simultaneously in novelty, depth, contextual understanding, and innovation. These results extend dual-process theories of cognition by demonstrating that prior knowledge conditions how AI reshapes the balance between intuitive and deliberative processes. Practically, the study highlights that the strategic value of AI in entrepreneurship lies not in substituting for human judgment but in complementing it with sector-specific expertise that anchors both originality and analytical rigor.