Fractal Technology for Sustainable Growth in the AI Era: Fractal Principles for Industry 5.0

This study presents fractal technology as a foundational approach to sustainable growth in the artificial intelligence (AI) era and Industry 5.0. We explore how the principles of fractal geometry, including self-similarity and recursive properties, improve scalability, efficiency, and adaptability in AI-driven systems. Representative applications include neural networks, decentralized control, and intelligent manufacturing, where fractal-based design enables modularity, fault tolerance, and optimized resource use. Case studies and theoretical models demonstrate that a fractal frameworks provide a viable path toward long-term, self-organizing industrial innovation and sustainability-oriented vision of Industry 5.0. Theoretical perspectives are strengthened by connections to nonextensive Tsallis statistics and parallels with complex systems in quantum field theory, suggesting the universality of fractal laws across disciplines. Case studies confirm that fractal frameworks offer a viable path toward long-term, self-organizing industrial innovation, contributing to the emerging field of fractal engineering and providing a systems-level paradigm for sustainable technological evolution.