The impact of artificial intelligence as a disruptive and closing technologies on industrial economics: a set of tasks for scientific comprehension and resolution

This article investigates the impact of Artificial Intelligence (AI) on the industrial economy, analyzing it from the perspective of two competing theories: disruptive and closing innovation. The research is highly relevant due to the significant growth in investments (Nvidia's capitalization surpassed $5 trillion in October 2025) and AI's influence on global industrial production. This is particularly crucial for Ukraine, given the prospects for the transfer of military-oriented AI into the civilian economy. The literature review identifies two main groups of academics: proponents (AI as the core of Industry 4.0) and critics (AI primarily automates existing tasks, potentially leading to "over-automation" and a decrease in GDP). This contradiction forms the basis for two competing hypotheses: AI is a Disruptive Innovation, which changes markets and creates new players. AI is a Closing Innovation, which merely improves existing products and strengthens the position of current market leaders. A comparative analysis of AI was conducted based on criteria such as the impact on the product, the customer, market dominance, and the institutional space. The study demonstrates that AI represents a complex innovative phenomenon that simultaneously exhibits characteristics of both types of technologies: - Closing Role: AI improves existing platforms and products of market giants (Microsoft Copilot, Google AI Overviews, Siri), thereby strengthening their dominance. - Disruptive Role: AI creates fundamentally new products (ChatGPT, Grok), attracts new customers, and shapes new specialized legislation. The dual nature of AI presents several challenges, notably the lack of economic theory and tools for quantitative assessment of its effects at the micro-, meso-, and macro-levels. A list of key scientific challenges requiring resolution is formulated: Defining the theoretical foundations of AI's micro-, meso-, and macro-level impact as both disruptive and closing technologies. Substantiating the assessment methodology and testing the hypothesis regarding AI's statistically significant impact. Identifying economic constraints, minimizing risks, and systemizing directions for stimulating AI adoption. Substantiating recommendations for updating Ukraine's national industrial policy, institutional regulation (including taxation), and ensuring the economic efficiency of AI utilization. Understanding the dual nature of AI is crucial for economic forecasting and strategizing. Although AI possesses powerful disruptive potential, its implementation is currently dominated by incumbent large companies, which does not lead to the "disruption" of their positions. Addressing the outlined challenges is necessary for the urgent actualization of Ukraine's industrial policy.