An Application Model of Data Disaster Preparedness Strategy Incorporating Artificial Intelligence in Data Element Governance

Data security and business continuity are facing serious challenges in the era of digital economy. This paper proposes a data disaster recovery application model integrating artificial intelligence, which contains three core parts: overall architecture design, risk intelligent sensing mechanism, and data element intelligent grading and disaster recovery strategy matching. The model achieves accurate early warning of data risk through deep learning algorithms, intelligent grading of data value based on multi-dimensional assessment, and generates the optimal disaster recovery strategy. Experimental validation shows that the model outperforms traditional disaster recovery methods in terms of warning accuracy, resource utilisation efficiency and system adaptability, providing an efficient and reliable disaster recovery solution for the data element industry.