AI-driven Industrial Revolution

The rapid development of artificial intelligence (AI) models is driving a qualitatively new stage of industrial transformation. AI is becoming the core of cyber-physical systems, digital twins, and self-learning production loops, fundamentally reshaping business trajectories. This process can be described as an AI-driven Industrial Revolution, which is transforming production models, business processes, market structures, and approaches to management. The use of AI extends beyond individual sectors, creating cross-industry effects, including productivity growth, enhanced resilience of supply chains, reduced environmental footprint, and industrial adaptation to evolving global challenges. At the same time, the industrial context imposes specific requirements for the reliability, interpretability, and scalability of AI-based solutions. In parallel, issues of policy, regulation, and ethics related to the integration of AI into industrial systems are becoming increasingly important.



The aim of this Research Topic is to establish an expert platform for analyzing and discussing how AI transforms industry, to identify key mechanisms and barriers to implementation, and to outline strategic directions for policy, corporate strategies, and international cooperation in this domain. Special attention is given to the practical outcomes of AI deployment, scenario modeling of industrial development, and the analysis of how digital technologies contribute to the formation of a new industrial paradigm.



This Research Topic seeks to consolidate interdisciplinary research that translates AI achievements into reproducible technological, organizational, and managerial solutions for the industry of the future. Its mission is to integrate theoretical approaches and applied developments that foster the creation of sustainable industrial ecosystems. Particular emphasis is placed on the synthesis of knowledge from economics, engineering, computer science, management, and the social sciences, enabling a holistic vision of the trajectories of the AI-driven Industrial Revolution.



Original research, review articles, and applied case studies are welcome, addressing but not limited to the following areas:

• Applications of AI in industry and their impact on production processes;

• Cross-industry potential and technology markets for industrial AI;

• Digitalization of business processes and optimization of value chains through AI;

• Adaptation of industrial enterprises to AI technologies and the formation of new organizational models;

• AI in strategic management and scenario modeling;

• Industrial policy and AI strategies of countries and regions;

• Social, environmental, and ethical aspects of the AI-driven Industrial Revolution.



It is expected that the contributions to this Research Topic will provide a comprehensive understanding of the mechanisms, effects, and strategies of the AI-driven Industrial Revolution, forming a foundation for scientific and applied dialogue between academia, industry, and government.

Article types and fees

This Research Topic accepts the following article types, unless otherwise specified in the Research Topic description:

• Brief Research Report
• Conceptual Analysis
• Data Report
• Editorial
• FAIR² Data
• FAIR² DATA Direct Submission
• General Commentary
• Hypothesis and Theory
• Methods
• ... View all formats

Articles that are accepted for publication by our external editors following rigorous peer review incur a publishing fee charged to Authors, institutions, or funders.

Article types

This Research Topic accepts the following article types, unless otherwise specified in the Research Topic description:

• Brief Research Report
• Conceptual Analysis
• Data Report
• Editorial
• FAIR² Data
• FAIR² DATA Direct Submission
• General Commentary
• Hypothesis and Theory
• Methods
• Mini Review
• Opinion
• Original Research
• Perspective
• Policy and Practice Reviews
• Review
• Systematic Review
• Technology and Code

Keywords: Industrial AI; digital twin; predictive analytics; sustainable manufacturing; autonomous systems

Important note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.