MODERN DATABASE MANAGEMENT SYSTEMS AS A FOUNDATION FOR AI-BASED ANALYTICS IMPLEMENTATION IN SMALL AND MEDIUM-SIZED ENTERPRISES: A LITERATURE REVIEW AND A CONCEPTUAL MODEL
DOI:
https://doi.org/10.17512/znpcz.2026.3.08Keywords:
artificial intelligence, cloud computing, data analytics, database management systems, small and medium-sized enterprisesAbstract
Small and medium-sized enterprises (SMEs) increasingly seek to leverage artificial intelligence (AI) for data-driven decision-making, yet the technical foundation enabling such capabilities – the architecture of the underlying database management system – remains underexplored in the management literature. This article aims to systematise knowledge on the role of database architecture (on-premise, cloud-based, and data warehouse solutions) in enabling AI-based analytics in SMEs, and to propose a conceptual model supporting the architectural choice. A targeted literature review of nine purposively selected sources published between 2019 and 2025, including three PRISMA-based systematic reviews, was conducted across four thematic areas: database and data warehouse impact on performance, cloud computing adoption in SMEs, antecedents of data analytics adoption, and the integration of AI with database architectures, including code-based (Python/SQL) versus low-code approaches. The review reveals that database architecture choice, cloud adoption, and AI analytics implementation are treated as separate research streams, without an integrative decision-support model. A three-layer conceptual model (data architecture, analytical integration, organisational competence) is proposed as a diagnostic tool for SME managers and a starting point for future empirical validation.
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Copyright (c) 2026 Marcelina Otręba, Danuta Rozpędowska-Matraszek (Autor)
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