Collaborative Mechanism and Value Co-creation Model of Enterprise Innovation Ecosystems Embedded with Artificial Intelligence

Abstract

Artificial intelligence is increasingly embedded in enterprise R&D, production, management, and platform operations. This process shifts collaboration in enterprise innovation ecosystems from experience driven interaction to data identification, algorithmic matching, and intelligent feedback. Focusing on core firms, partners, supply chain actors, and technological cooperation relationships, an analytical framework is developed to examine AI embeddedness, collaborative mechanisms, and value co creation performance. The sample includes 480 Chinese A share listed enterprises from 2020 to 2025. Annual reports, ESG reports, announcement texts, joint patents, and public patent data are used as data sources. Python based text mining, BERT semantic identification, NetworkX analysis, panel regression, XGBoost, and SHAP interpretation are applied. The results show that enterprises with higher AI embeddedness have higher network density, stronger degree centrality, and a higher joint patent ratio. Collaborative mechanisms play a key role in the effect of AI embeddedness on value co creation performance. The findings indicate that AI does not improve innovation output in isolation. It promotes value co creation by optimizing cooperation structures, knowledge connections, and resource allocation in enterprise innovation ecosystems.