Abstract: The studyʼs relevance is driven by the profound transformative processes occurring in the global economy under the influence of artificial intelligence. Modern businesses face challenges that require rethinking traditional business models and shaping new approaches to ensure competitiveness. While the global trend for AI adoption is evident, Ukraineʼs experience is significantly different: the penetration of AI solutions into the domestic business sector is much lower than in EU countries. This creates an urgent problem, as insufficient use of innovative technologies can lead to businesses losing their market positions in the long run. The analysis of existing scientific publications has revealed an insufficient development of theoretical and methodological frameworks for evaluating the economic effectiveness and value of AI solutions. Although several studies focus on specific aspects of AIʼs impact on business processes, there is no comprehensive, multi-vector model that would account for a combination of factors: economic, organizational, technical, and temporal. The problem of adequately assessing the value of AI solutions, which goes beyond a simple cost analysis, also remains under-researched. The article aims to develop a theoretical and methodological approach to assessing the economic effectiveness and value of AI solutions for enterprises, as well as their impact on strategic competitiveness. To achieve this goal, a comprehensive approach was used, combining systems analysis, modeling, and comparative analysis methods. The study analyzed the current state of AI technology implementation in Ukraine and EU countries, revealing significant differences in its use by industry and business size. It is argued that a comprehensive assessment of AI solutions goes beyond traditional economic analysis and requires a multi-vector approach. A methodological approach to assessing the value and effectiveness of AI solutions is proposed, based on three dominants: cost-based, results-based, and comparative analysis. As a result, a basic linear model for assessing effectiveness was developed, which considers the influence of information and time on an enterpriseʼs resources and results. Implementing this model will allow businesses to make informed management decisions regarding the feasibility of investing in AI technologies.