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Artificial Intelligence Integration Into Dbms: Performance Optimization, Benefits, And Associated Challenges

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  • BABUCEA ANA-GABRIELA

    (CONSTANTIN BRANCUSI UNIVERSITY OF TARGU JIU)

Abstract

The current digital economy requires database management systems (DBMS) capable of adaptation and autonomy. Increased data volumes and rapid analysis current requirements are not support by the traditional DBMS. The right solution for these limitations is integration of artificial intelligence (AI). Due to AI algorithms, queries can be optimized and anomalies can be automatically identified for increased data security, natural language-based interfaces can be developed, and data management activities, such as archiving, indexing, or data migration, can be improved, too. However, the success of the process of AI integration into organizational DBMS depends on economic and technological factors that influence the final result, and some of them can be initial costs, difficulties during the integration, and the level of data quality. The paper aims to analyze the economic and technological context that forced organizations to decide on the integration of AI into database management. The main technologies as well as common implementation methodologies are presented. Operational and economic benefits are highlighted alongside with organizational, technical, and ethical challenges associated with AI integration into DBMS.

Suggested Citation

  • Babucea Ana-Gabriela, 2026. "Artificial Intelligence Integration Into Dbms: Performance Optimization, Benefits, And Associated Challenges," Annals - Economy Series, Constantin Brancusi University, Faculty of Economics, vol. 1, pages 144-153, February.
    • Handle: RePEc:cbu:jrnlec:y:2026:v:1:p:144-153
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