Data Valuation, AI Ecosystem Restructuring and Enterprise Digital Intelligence Transformation

Abstract

This paper aims to explore how data valorization drives enterprise digital intelligence by reconstructing the AI ecosystem (covering three dimensions: AI talent, technology, and collaboration). Based on technological economics and innovation theory, this study constructs a theoretical analytical framework of “data valorization—AI ecosystem reconstruction—enterprise digital intelligence” and conducts empirical testing using data from China’s Shanghai and Shenzhen A-share manufacturing listed companies from 2014 to 2023. In terms of research design, the core dependent variable “enterprise digital intelligence” is measured using text mining methods based on the BERT large language model, effectively overcoming the limitations of traditional lexical methods in semantic understanding and motivation identification. The findings reveal: First, data valorization has a significant positive driving effect on enterprise digital intelligence, and this conclusion remains valid after a series of robustness tests. Second, mechanism analysis indicates that data valorization empowers transformation through three pathways: first, fostering and optimizing AI talent structures to strengthen human capital foundations; second, systematically enhancing AI technological innovation and engineering applications; and third, deepening AI collaboration by promoting cooperation at the levels of resource utilization, assetization, and capitalization. Third, the transformational effects of data valorization exhibit heterogeneity, being more pronounced in enterprises with strong absorptive capacity, optimal talent structures, and rich governance experience.