Jiewu Leng – författare

This book brings together selected papers presented at the International Scientific Conference “Digital Transformation in Industry: Trends, Management, Strategies” (DTI), held in Ekaterinburg, Russia, on November 19–21, 2025, as part of the biennial DTI framework. Organized by the Institute of Economics of the Ural Branch of the Russian Academy of Sciences, the conference further developed the strategic research agenda initiated at DTI-2024, with particular emphasis on the theme ‘Artificial Intellect in Industry: Effects, Barriers, and the Directions of National Policy’. The book is structured around five interconnected thematic areas. First, it addresses applied cases of artificial intelligence and emerging trajectories of industrial development, including comparative national experiences, sectoral applications, human–machine interaction on the shopfloor, and AI-enabled energy and sustainability solutions. Second, it explores the optimization of business processes and business models through digitalization, focusing on data management, organizational change, and the transformation of enterprise decision-making. Third, it considers digital ecosystem architectures and platform-based solutions, highlighting agent-based modeling, adaptive identification methods, cross-border innovation platforms, hardware emulation tools, and regional dimensions of digital transformation. Fourth, the volume examines the human dimension of AI adoption, including human-centered manufacturing, education, employment, digital skills, wages, and human capital formation under Industry 5.0. Finally, the book explores the application of AI-driven tools in FinTech and cybersecurity, with chapters addressing large language models and proactive cyberattack detection. Taken together, the chapters offer theoretical, methodological, and empirical perspectives on the restructuring of industrial systems under the influence of AI. The book will be of interest to scholars, practitioners, and policymakers engaged in the study and implementation of AI-driven industrial transformation.