Towards an Intelligent Industry

AI-Driven Transformation and Managerial Innovation
Erscheinungsjahr 2026
ISBN: 978-3-032-29240-7
Verlag: Springer

Buch, Englisch, 519 Seiten, Format (B × H): 155 mm x 235 mm

Reihe: Lecture Notes in Information Systems and Organisation

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.

Zielgruppe

Research

Autoren/Hrsg.

Leng, Jiewu

Kuzmin, Evgeny

Gadekallu, Thippa Reddy

Akberdina, Victoria

Kumar, Vikas

Fachgebiete

• Wirtschaftswissenschaften Wirtschaftssektoren & Branchen Non-Profit-Organisationen, Verbände
• Mathematik | Informatik EDV | Informatik Professionelle Anwendung
• Wirtschaftswissenschaften Volkswirtschaftslehre Volkswirtschaftslehre Allgemein Industrielle Organisation
• Mathematik | Informatik EDV | Informatik Angewandte Informatik
• Wirtschaftswissenschaften Betriebswirtschaft Wirtschaftsmathematik und -statistik

Inhaltsverzeichnis

Chapter 1: The AI Pilot Trap: From Proof of Concept to Industrialization.-  Chapter 2: Artificial Intelligence in Digital Transformation of Industry: A Comparative Analysis of Global Trends and Russian Practices.- Chapter 3: Analysing the Awareness of SME Managers in Türkiye Regarding National Industry 4.0 Policies and Artificial Intelligence Strategies.- Chapter 4: Dynamic Capabilities for Agentic AI in Service Organizations.- Chapter 5 : Cross-Industry Transferability of AI Technology: Evidence from Russian Metallurgical and Chemical Industries.- Chapter 6 : A Framework for the Early Integration of Energy and Sustainability in Industrialized Building Design.- Chapter 7 : Management in Distributed Energy Using Explainable Artificial Intelligence.- Chapter 8: Analysis of the Development of Digital Technologies and Artificial Intelligence in the Agricultural Sector.- Chapter 9: Assessing Human–Autonomic Computing Interaction at the Shopfloor Level in Process Industries.- Chapter 10: Data Management at Industrial Enterprises: The Data Value Dilemma.- Chapter 11: Change Management in the Process of Digital Transformation of Manufacturing Enterprises.- Chapter 12: On the Assessment of the Impact of Concomitant Processes on the Activities of Large Mechanical Engineering Enterprises in the Context of Industry 4.0.- Chapter 13: Personal Branding and Digital Business Models: The Case of Rhode Skin.- Chapter 14: Architecture of an Agent-Based Model of an Industrial Digital Ecosystem.- Chapter 15: A New Method for Optimizing Adaptive Identification and Selection of a Model of the Dynamics of a Digital Industrial Ecosystem Object.- Chapter 16: Digital Platform of a Cross-Border Innovation Ecosystem: Principles of Design and a Conceptual Model.- Chapter 17: Analysis of Design Methods and Performance Improvement Techniques for Intelligent Systems' Hardware Platform Emulation Tools.- Chapter 18: Regional Scientific Potential and Industrial Digital Transformation: An Analysis of Transregional Smart Specialization Centers in Russia.- Chapter 19: A Review and Research Avenues on AI for Human-Centered Manufacturing.- Chapter 20: Key Discourses on the Impact of Artificial Intelligence on Education and Industry.- Chapter 21: Towards Human-AI Complementarity in Higher Education Institutions (HEIs): Evidence from an Italian University.- Chapter 22: AI-Powered Workforce Equilibrium and Sustainable Employment in the Digital Economy.- Chapter 23: Digital Skills, AI Competences, and Wages: The Moderating Role of Social Resilience.- Chapter 24: Neural Network Solutions for Managing Human Capital Formation and Labor Demand in Digital Megacities.- Chapter 25: AI-driven Energy Transition and Industry 5.0: Redefining Human Capital and Industrial Strategy.- Chapter 26: Digital Transformation and Human Capital Among Farmers During the COVID-19 Pandemic: The Case of Samsun, Türkiye.- Chapter 27: Empowering Financial NLP with DeepSeek: Applications of Large Language Models.- Chapter 28: A Hybrid LSTM and Isolation Forest Framework for Proactive Zero-Day Attack Detection.

Über Autor(innen)

Jiewu Leng is Professor and Deputy Director of the of Guangdong Provincial Key Laboratory of Computer Integrated Manufacturing at Guangdong University of Technology, Guangzhou, China. His current research interests include smart manufacturing system design and digital twins. He has published more than 130 SCI papers and was selected as a Clarivate Highly Cited Researcher in 2025 and an Elsevier Highly Cited Chinese Researcher since 2021. 

Evgeny Kuzmin is an Academic Researcher in the Department of Regional Economic Policy and Economic Security at the Institute of Economics of the Ural Branch of the Russian Academy of Sciences, Russia. His research interests include risk and uncertainty, economic crises, sustainability, public-private partnerships, industrial policy, economic growth, and entrepreneurship. He has authored more than 150 scientific publications and has served as a peer review on various international journals. 

Thippa Reddy Gadekallu is Chief Engineer at Zhongda Group, Jiaxing City, China. Currently his areas of research include machine learning, internet of things, deep neural networks, blockchain and computer vision. He has more than 15 years’ experience in teaching and research and has more than 350 international/national publications in reputed journals and conferences. He was recently recognized among the top 2% scientists in the world by Elsevier in 2021, 2022, 2023, and 2024. He is also recognized as a highly cited researcher, young scientist category, by Clarivate (web of Science) for the period 2017-2022 in the year 2023.  

Victoria Akberdina is Deputy Director of the Institute of Economics and Head of the Department of Regional Industrial Policy and Economic Security at the Ural Branch of the Russian Academy of Sciences, Russia. She conducts fundamental and applied research on problems concerning industrial policy formation, forecasting methodologies, and modeling the evolution of the economic and technological development of industrial complexes, as well as the structural dimensions of economic development.

Vikas Kumar is a Deputy Vice Chancellor for Research and Innovation at the University of Portsmouth, UK. He is a distinguished academic and researcher with over 15 years of experience in the operations and supply chain management domain. Professor Kumar has significantly contributed to areas of sustainable supply chains, circular economy, operational excellence, and supply chain 4.0. He has published over 350 papers in top-tier international journals and international conferences. He was featured among the top 1% of the Highly Cited Researchers 2024 list and in the World’s Top 2% Scientists list in 2024. He is also featured in the World’s Top 2% Scientists list in 2024/2025 and in the Talent 100 Business & Economics 2026 ranking.