SECURE II: Unlocking the Potential of Artificial Intelligence for Entrepreneurial Success

Abstract

This study investigates the potential of artificial intelligence (AI) techniques to aid novice entrepreneurs in evaluating their business models prior to launching new ventures. The proposed SECURE II framework integrates symbolic AI, neural AI and ensemble modeling to strengthen ex-ante assessment of business model designs and expected performance outcomes. Machine learning experiments demonstrate that AI modeling uncovers hidden patterns and relationships between pre-launch plans and post-launch results. This enables more informed entrepreneurial decision-making by providing data-driven evaluative feedback. Rather than relying solely on intuition, the interactive AI assessments offer entrepreneurs a simulation mechanism to systematically test assumptions and refine opportunities pre-launch. The ensemble approach combining complementary AI techniques outperforms individual models, underscoring the value of synthesized hybrid intelligence tailored to the entrepreneurial context. By compensating for limitations in human information processing, pattern recognition, and biases, the SECURE II framework augments entrepreneurial cognition during business model formulation. This study elucidates the mechanisms through which AI can expand mental capabilities for opportunity analysis and new venture creation. The proposed toolkit demonstrates strong predictiveness on real-world data, validating the utility of AI to minimize uncertainties and boost startup success.