The Construction Mechanism of Digital Resilience in Traditional Manufacturing Enterprises Driven by Artificial Intelligence—An Exploratory Case Study Based on Midea Group

How does artificial intelligence drive the construction of digital resilience in traditional manufacturing enterprises? This study adopts an exploratory case study method and finds that: the three stages of resource datafication, data assetization to asset servitization, with self-reinforcing closed-loop mechanisms, become important processes that promote the continuous enhancement and stable development of digital resilience in traditional manufacturing enterprises; in this process, enterprises need to deploy technologies such as machine learning, human-computer interaction learning, and transfer learning. The co-evolution and mutual enhancement of the absorptive and adaptive paths, forming a positive feedback system, are key mechanisms for building enterprise digital resilience. These findings contribute to the study of the process of building digital resilience in traditional manufacturing enterprises facing digital disruption and provide practical insights for the digital transformation of traditional home appliance manufacturing enterprises.