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RESEARCH CENTER FOR INDUSTRIAL DEVELOPMENT PROBLEMS of NAS of Ukraine (KHARKIV, UKRAINE)

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Liburkina L. M.

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A Multilevel Model of Artificial Intelligence Adoption in Enterprise Marketing: An Econometric Analysis of the Effect Under Ukrainian Market Conditions
Koberniuk S. O.

Koberniuk, Serhii O. (2026) “A Multilevel Model of Artificial Intelligence Adoption in Enterprise Marketing: An Econometric Analysis of the Effect Under Ukrainian Market Conditions.” Business Inform 8:692–701.
https://doi.org/10.32983/2222-4459-2026-8-692-701

Section: Management and Marketing

Article is written in English
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UDC 658.8:004.8

Abstract:
The aim of the study is to develop a multilevel model of artificial intelligence adoption in enterprise marketing that combines an original typology of maturity levels, an econometric substantiation of the dependence of the economic effect on the level of implementation, and a forecast of the Ukrainian market structure through 2030. The methodological basis comprises systemic and comparative analysis, econometric modeling, and multi-source triangulation of empirical data drawn from the AI Focus 2026 study (216 Ukrainian enterprises), the Boston Consulting Group (1.250 executives) and PwC (4.454 executives) reports, and statistics from Stanford HAI and Eurostat. A four-level maturity scale is proposed – fragmentary, functional, integrated, and transformational – aligned with leading international frameworks and adapted to marketing specifics. The integrated economic effect index rises from 0.148 at the fragmentary level to 0.684 at the integrated level, while the decay of the marginal increment reveals the logistic rather than exponential nature of the process. The gap between the extreme levels in the share of enterprises reporting a significant positive effect reaches 10.6 times. Triangulation across a combined sample of about 5.920 enterprises confirms the robustness of the maturity–outcome relationship, with an advantage coefficient from 1.4 to 10.6, interpreted as a self-reinforcing cycle of capability accumulation. The calibrated logistic model forecasts the global share of mature enterprises approaching 78% by 2030, with the Ukrainian market following the same trajectory at a lag of about one year. The barrier transition coefficient (0.662) quantifies a high threshold of movement between levels dominated by technological and economic obstacles. The practical value consists in providing enterprises with a measurable self-assessment apparatus and in substantiating the priority of investment in tool integration over their mere accumulation. It makes sense to focus further research on industry verification of the model and refining the parameters of the transformational level.

Keywords: artificial intelligence; marketing; adoption maturity; econometric modeling; logistic curve; economic effect; implementation barriers; digital transformation.

Fig.: 4. Tabl.: 4. Formulae: 4. Bibl.: 20.

Koberniuk Serhii O. – Candidate of Sciences (Economics), Associate Professor, Associate Professor, Department of Marketing, Dnipro State Agrarian and Economic University (25 Academician Serhiy Yefremov Str., Dnipro, 49027, Ukraine)
Email: [email protected]

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