Generative AI-Driven Technological Entrepreneurship: Theoretical Analysis of Opportunity ,Recognition, Resource Allocation and New Venture Growth Logic

Abstract

Generative artificial intelligence (GenAI) is transforming how we access information, create knowledge, and organize resources in the field of technology entrepreneurship. Based on a review of the related literature and theoretical analysis, this study constructs an analytical framework covering three key aspects: opportunity identification, resource allocation, and venture growth. Our analysis suggests that GenAI broadens the opportunity space for technology entrepreneurs by combining heterogeneous information across various sources and recombination of scattered knowledge; improves the efficiency of resource allocation via AI-enabled decision support, resource orchestration, and network connectivity; and promotes new venture growth by accelerating opportunity conversion, fostering dynamic capabilities, and enabling iterative business model adaptation. Instead of simply replacing human labor, the entrepreneurial value of GenAI stems primarily from its ability to reconfigure entrepreneurial capabilities via human–AI collaboration.