ARTIFICIAL INTELLIGENCE AS A TOOL FOR MANAGING THE INTELLECTUAL CAPITAL OF A TRADING ENTERPRISE

Abstract

Proved that in the context of the digital economy and the Fourth Industrial Revolution, the intellectual capital of a trading enterprise transforms into a key strategic asset determining its competitiveness, innovation potential, and capacity for sustainable development. Established that traditional approaches to intangible asset management are insufficient under current conditions, as they fail to account for the dynamic nature of intellectual capital and do not provide for the systematic integration of digital tools into the processes of its formation and assessment. Systematized the structure of intellectual capital of a trading enterprise, encompassing three interrelated components: human capital (knowledge, competencies, and digital skills of personnel), customer capital (brand, consumer loyalty, and depth of market behaviour understanding), and structural capital (business processes, organisational knowledge, and information systems). Substantiated the authors' definition of intellectual capital of a trading enterprise as a dynamic set of intangible assets that, through their interaction and under the influence of digital technologies, generate intellectual added value and form sustainable competitive advantages. Identified the directions of artificial intelligence technology influence on each component of intellectual capital: automation of routine tasks and development of digital competencies of personnel – for human capital; personalisation of customer experience, predictive analytics of consumer behaviour, and proactive customer retention – for customer capital; optimisation of supply chain management, dynamic pricing, and integration of information systems – for structural capital. Proposed a three-level model for forming information systems for intellectual capital assessment, comprising an operational level for primary data collection through enterprise resource planning, customer relationship management, and electronic commerce systems; an analytical level for transforming data into knowledge using machine learning and business intelligence technologies; and a strategic level for management decision-making based on integrated dashboards and key intellectual capital development indicators. Developed a system of quantitative and qualitative indicators for assessing each component. Revealed the specifics of implementing the proposed model under the conditions of wartime and post-war economic recovery of Ukraine, particularly regarding cloud-based solutions for small and medium-sized trading businesses and corporate programmes for restoring digital competencies of personnel.