ARTIFICIAL INTELLIGENCE INTEGRATION INTO DBMS: PERFORMANCE OPTIMIZATION, BENEFITS, AND ASSOCIATED CHALLENGES

Babucea Ana-Gabriela
Additional contact information
Babucea Ana-Gabriela: CONSTANTIN BRANCUSI UNIVERSITY OF TARGU JIU

Annals - Economy Series, 2026, vol. 1, 144-153

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.

Keywords: Database Management Systems (DBMS); Artificial intelligence (AI); Optimization (search for similar items in EconPapers)
Date: 2026
References: Add references at CitEc
Citations:

Downloads: (external link)
https://www.utgjiu.ro/revista/ec/pdf/2026-01/14_Babucea.pdf (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:cbu:jrnlec:y:2026:v:1:p:144-153

Access Statistics for this article

More articles in Annals - Economy Series from Constantin Brancusi University, Faculty of Economics Contact information at EDIRC.
Bibliographic data for series maintained by Ecobici Nicolae ().