Artificial Intelligence and Innovation Ecosystem: Evolutionary Developments, Challenges, and Future Directions
2026-07-27 • Artificial Intelligence
Artificial Intelligence
AI summaryⓘ
The authors explore how Artificial Intelligence (AI) is changing the way innovative ecosystems (IE)—networks where different groups collaborate to develop new ideas—work and grow. They break down IE into physical, social, and thinking parts and introduce the idea of an AI-driven innovative ecosystem (AIIE) from this spatial view. By looking at how AI has influenced different stages of development and using real company examples, the authors assess how AI helps and what problems it might bring in the future. They aim to guide future research by pointing out challenges in combining AI with innovation networks.
Innovative EcosystemArtificial IntelligenceDigitizationInformatizationEvolutionary PerspectiveSpatial PerspectiveAIIEEconomic IntegrationCollaborative Advancement
Authors
Zhimin Zhang, Chengzhen Ma, Jia Chai, Rongxin Zhan, Huansheng Ning, Lingfeng Mao, Dan Zhang, Suiping Jiang
Abstract
The development of the Innovative Ecosystem (IE) presents a new paradigm for economic integration, collaborative advancement, and shared achievements. The rise of Artificial Intelligence (AI) has significantly accelerated the global processes of digitization, informatization, and intelligence. Exploring how AI can leverage inherent characteristics to influence the development trajectory of IE is a topic that warrants further investigation. Given AI's increasing prominence and role within IE, the paper analyzes this new form, examining both AI's unique contributions to IE and its potential challenges. Firstly, the paper synthesizes the conceptual frameworks surrounding IE, decomposing them into manifestations in physical, social, and thinking spaces. Furthermore, the concept of Artificial Intelligence IE (AIIE) is introduced from a spatial perspective, with an exploration of the characteristics AI contributes to IE. Subsequently, the paper employs an evolutionary perspective to analyze the roles provided by AI during different development periods of AIIE. The paper then verifies the feasibility, effectiveness, and rationality of the AIIE's definition and analyzes AIIE development from an evolutionary perspective using enterprise development examples. Finally, acknowledging AI's inherent limitations, the paper examines potential challenges facing AIIE in the future from four perspectives, aiming to identify new research avenues for the further development of AIIE.