OPERATIONAL AI MATURITY IN MARKETING: ECONOMETRICS OF DEPLOYMENT TIME AND COSTS

Rapid adoption of artificial intelligence (AI) is radically restructuring the architecture of marketing activities, and the cumulative volume of the global AI marketing market is projected to exceed 107,5 billion dollars by 2028. However, despite the pronounced growth of investments, most companies encounter difficulties in moving from declaring potential to generating measurable economic returns, remaining predominantly at the initial levels of operational maturity. The purpose of this study is to bridge the gap between qualitative assessment of maturity and quantitative project planning by proposing an original conceptual econometric model. The methodological foundation includes a systematized review of academic publications and a critical analysis of current industry studies by leading consulting firms (McKinsey, Deloitte, Gartner). On this basis, an integral five-level model of AI maturity is proposed, and a conceptual econometric construct is developed that formalizes the relationship between the organization’s maturity level and the expected time and cost parameters of deploying new marketing AI solutions. The model is based on the assumption that increasing maturity reduces the marginal costs of innovation activity. In conclusion, the quantitative feasibility of strategic investments in the development of organizational maturity in the field of AI is substantiated, which determines the practical significance of the study for top management and researchers specializing in technology management issues and the development of marketing strategies.