Periodization of the development of artificial intelligence

Abstract

The relevance of this study is determined by the rapid development of artificial intelligence (AI) and its impact on global technological, economic, and social processes. In the process of integrating artificial intelligence technologies into strategic planning, modern enterprises and government institutions require a scientifically grounded understanding of its historical evolution and main developmental periods. The purpose of this article is to analyze the development of AI from its inception in 1940 to the current stage as of October 2025, as well as to identify the patterns of technological evolution and key achievements at each historical stage. Methods. The study applies historical and systemic analysis, comparative review of scientific publications, and analysis of regulatory acts and strategic documents in the field of AI development. Synthesis and classification methods were used to determine chronological boundaries, dominant technological paradigms, and key innovative achievements of each period. Results. The scientific novelty of the study lies in the creation of an integrated periodization of the development of artificial intelligence (1940-2040) that takes into account national contexts and modern forecasts of technological singularity. Twelve main stages of AI evolution are proposed, characterized by cyclical development alternating between periods of advancement and « expectation crises. The influence of historical stages on the development of Ukrainian entrepreneurship was analyzed in the context of the AI Development Strategy until 2030 and global innovation trends as of October 2025. A correlation was established between the patterns of AI development and forecasts of technological singularity in 2035–2040. Additionally, it was determined that periodizing AI development enables more effective alignment of scientific, technical, and investment strategies with current technological trends. Conclusions. The study's results provide a methodological basis for strategic planning for AI implementation at the enterprise and state policy levels. Identifying clear development periods and technological paradigms enables forecasting future trends, adapting innovative strategies, and effectively leveraging AI's potential across sectors of society and the economy.