AI-Driven Policy Mapping for Regional Entrepreneurial Ecosystems: A Mixed-Methods Framework

Background: Regional entrepreneurial ecosystems are key drivers of innovation, economic growth, and inclusion. However, fragmented policies and data silos hinder effective governance. Artificial Intelligence (AI) offers a new pathway to understand and optimize these ecosystems through data-driven policy mapping. Objectives: This study aims to design and evaluate an AI-powered framework that models the structure, dynamics, and disparities within regional entrepreneurial ecosystems. It focuses on enhancing policy effectiveness, predicting startup outcomes, and promoting equity through advanced computational techniques. Methods: A mixed-methods, computational-exploratory approach was used. Over 100,000 policy documents, financial flows, and social network data from 20,000+ ecosystem actors were analyzed. Techniques included transformer-based NLP models (e.g., BERT, RoBERTa), graph neural networks, and reinforcement learning. Quantitative and qualitative data were integrated to assess startup density, innovation output, funding allocation, and inclusion metrics. Predictive modeling and scenario simulations were conducted to evaluate policy impacts. Results: The AI framework achieved high classification accuracy (F1-score 0.91) in semantic policy categorization. Predictive models forecasted startup survival and innovation outputs with up to 88% accuracy. Network analysis revealed centralized control over capital and mentorship, with inclusion gaps along gender, geographic, and socio-economic lines. Scenario simulations indicated that integrated, equity-focused policies improved startup survival by 12–19% and reduced funding disparities by 25%. Conclusions: AI-driven policy mapping provides a powerful lens to understand and shape entrepreneurial ecosystems. By combining large-scale data, ethical AI design, and stakeholder engagement, the framework supports adaptive, inclusive governance. These findings underscore the potential of AI to enable smarter, fairer entrepreneurship policy in dynamic regional contexts.