The integration of technological innovations from Silicon Valley into conventional business operations has emerged as a transformative trend, especially as traditional industries face increasing pressure to modernize and remain competitive. However, the mechanisms, success factors, and challenges of this innovation transfer remain underexplored. This study aims to examine how technological innovations, particularly artificial intelligence, cloud computing, and Internet of Things (IoT), are adopted by non-tech, traditional businesses and assess their impact on operational performance. Employing a qualitative case study approach, data were collected from five traditional enterprises across various sectors that implemented Silicon Valleyborn technologies. The data collection involved semi-structured interviews, document analysis, and comparisons of performance metrics before and after implementation. Findings reveal that successful technology transfer is facilitated by organizational readiness, strategic alignment, and continuous employee training. In contrast, barriers include cultural resistance, lack of digital literacy, and resource constraints. The study also uncovers that innovation adoption leads to measurable improvements in efficiency, customer satisfaction, and market agility. By comparing these findings to existing literature, the study highlights a gap in contextual adaptation strategies and the need for tailored implementation frameworks. The research contributes to the theoretical discourse on innovation diffusion and offers practical implications for managers aiming to bridge the digital divide. Future research is suggested to focus on cross-cultural and longitudinal studies to explore further the sustainability and scalability of tech innovation in traditional industries.