Artificial intelligence algorithms and professional brand scaling efficiency in international markets

Abstract

The purpose of the study is to determine the impact of the intensity, breadth and depth of integration of artificial intelligence algorithms on the effectiveness of international scaling of professional brands and to substantiate the methodological tools for assessing the systematicity of their use. Methodology. The effectiveness of international scaling of professional brands with different intensities of artificial intelligence algorithm integration is compared using five economic metrics: CAC, conversion rate, TTM, IRS and ROMI or ROAS. Results. The calculation model reveals a fundamental difference between the breadth of functional coverage of business processes by intelligent algorithms and the depth of their integration into the marketing processes of a professional brand. The use of eight functions with one point each forms an AIB of 100% for AID 1.0, while four functions of maximum depth provide an AIB of 50% for AID 4.0. Therefore, an increase in the number of intelligent tools in itself does not characterize the quality of algorithmic integration. The highest level of systematicity corresponds to a configuration of 6–8 integrated functions, for which the ratio G3 > G2 > G1 is provided. The synergistic potential of integrating smart algorithms emerges from various functional combinations, particularly advertising optimization with lead scoring and CRM, as well as predictive analytics with segmentation and personalization. Distinguishing between the breadth and depth of integration prevents the methodological error of equating technological saturation with economic efficiency. The model’s applicability is limited by the level of data maturity and the actual level of data integration into business processes. Conclusions. The proposed approach shifts the assessment of using artificial intelligence algorithms for international scaling of professional brands from assessing the availability of individual tools to measuring their integration across processes. The matrix allows professional brand owners and marketing managers to prioritize algorithmic configurations based on expected impacts on acquisition costs, conversion, speed to market, and marketing returns. With low data maturity, simpler localization and advertising optimization configurations remain appropriate.