Exploration Research on Intelligent Generation Application of VR Virtual Scenes Driven by Artificial Intelligence and Digitalization

The large-scale and efficient production of virtual reality (VR) content remains a critical bottleneck constraining industry development. Traditional scene construction methods relying on manual modeling and scripted programming exhibit prominent issues such as prolonged cycles, high costs, and limited customization. Recent breakthroughs in artificial intelligence technologies—including generative AI (AIGC), large language models, and neural rendering—have opened new pathways for intelligent VR scene generation. This study systematically examines the theoretical foundations and technical architectures of VR scene generation driven by AI technologies, delves into key technical approaches including geometric appearance generation, physical logic mapping, and ambient environment intelligence, conducts empirical analyses through domestic and international case studies, and explores cutting-edge directions such as edge intelligence, embodied intelligence, and world models. Research demonstrates that AI-driven technologies can enhance VR scene construction efficiency by over 80% while reducing costs by approximately 70%. Building on these findings, the paper proposes actionable recommendations across three dimensions: technological innovation, industrial applications, and ethical standards, aiming to provide theoretical references and practical guidance for developing next-generation VR content production paradigms characterized by high efficiency, fidelity, and strong interactivity.