Analysis of the economic efficiency of implementing intelligent analytics systems in small business

The article examines the mechanisms underlying the economic efficiency of implementing intelligent analytics systems in small businesses under conditions of accelerating digital transformation and resource constraints typical of small and medium-sized enterprises (SMEs). The analysis is based on a theoretical-analytical synthesis of contemporary empirical and review studies addressing the adoption of artificial intelligence, big data analytics, and decision support systems in SMEs. The study demonstrates that the use of intelligent analytics influences firms’ economic performance by reducing uncertainty in managerial decision-making, improving process coordination, and enhancing demand forecasting and resource utilization. It is substantiated that the economic effect manifests not primarily through direct increases in average performance indicators but through the redistribution of probabilities of economic outcomes and improved business resilience. The statistical strength of the impact of analytics systems is confirmed through structural modeling results identifying a significant relationship between analytics adoption and firm performance. The findings indicate that the return on implementation depends on the level of organizational and technological maturity of companies, including technological readiness, employee competencies, managerial support, and the integration of analytics into decision-making processes. Intelligent analytics is interpreted as a mechanism of structural managerial transformation enabling the transition toward data-driven management and the formation of stable economic performance parameters. The article is relevant for researchers in digital business transformation, SME economics, and analytics management, as well as for practitioners involved in the implementation of intelligent data analytics systems.