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Artificial intelligence as a driver of transformation of regional marketing strategies: advantages, limitations, and impact on business results

Aug 2026 · Russian journal of resources, conservation and recycling · 0 citations

TL;DR

The central theoretical result of this work is the systematization of five key areas of artificial intelligence application in regional marketing, which include developing a strategic vision with clear key performance indicators, phased pilot implementation in individual marketing areas, and practical recommendations for improving the effectiveness of intelligent technologies.

Abstract

This article explores the transformative potential of artificial intelligence technologies as applied to the marketing strategies of regional companies in the context of increasingly digital competitive environments. The relevance of this research topic is determined by two interrelated factors: the accelerated penetration of intelligent solutions into marketing activities, on the one hand, and the significant gap between the potential of new technologies and the degree of their adoption by regional businesses, on the other. Traditional marketing approaches are losing their effectiveness in the face of price volatility, increasing consumer selectivity, and talent shortages, while intelligent systems offer a qualitatively new level of personalization, forecasting accuracy, and cost optimization. The central theoretical result of this work is the systematization of five key areas of artificial intelligence application in regional marketing. Predictive analytics and demand modeling ensure increased sales planning accuracy and reduced inventory costs. Hyper-personalization of communications through generative models adapts content to the behavioral, cultural, and situational characteristics of local communities, strengthening audience loyalty. Real-time advertising budget optimization reduces customer acquisition costs by automatically reallocating funds between channels. Regionally tailored content generation accelerates product launches into new markets, reducing localization costs. Reputation management through automated review analysis and mention monitoring increases consumer trust in the brand. Based on the analysis, the authors developed practical recommendations for improving the effectiveness of intelligent technologies. The proposed model includes developing a strategic vision with clear key performance indicators, phased pilot implementation in individual marketing areas, investing in data management systems, developing internal staff competencies in data-driven marketing, and developing corporate ethical standards for the use of algorithmic solutions. The combined implementation of these strategies can provide regional companies with a sustainable competitive advantage, transforming artificial intelligence from an optional tool into a strategic development resource.

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