Ai-Driven Distributed Intelligence and Semiconductor Market Growth: A Demand-Side Empirical Analysis of Edge Computing and Hardware Innovation

Abstract

The global semiconductor industry is undergoing a profound structural transformation driven by the convergence of artificial intelligence (AI), edge computing, and distributed intelligence ecosystems. Traditionally influenced by consumer electronics cycles and centralized computing architectures, semiconductor demand is increasingly shaped by intelligence-centric applications requiring real-time processing, energy efficiency, and decentralized computational capability. This study develops a demand-side analytical perspective by examining how AI-enabled technological ecosystems influence semiconductor market growth through structural changes in computing architecture. Drawing on secondary industry datasets and technology-driven indicators, the research adopts a quantitative explanatory approach to evaluate the influence of four major technological drivers: AI network intelligence expansion, edge computing adoption, cloud–edge distributed architecture, and AI hardware innovation. Using Pearson correlation and multiple regression analysis conducted in SPSS, the study provides empirical evidence demonstrating that emerging AI-edge ecosystems significantly explain variations in semiconductor demand expansion. The findings reveal strong positive relationships between distributed computational infrastructures and semiconductor market growth, with AI-driven network intelligence emerging as the most influential predictor. Edge computing adoption and hardware innovation further strengthen semiconductor intensity across digital infrastructures, supporting the shift from centralized processing toward distributed intelligence. The study contributes theoretically by repositioning semiconductor research toward demand-side technology economics, integrating AI infrastructure development with industrial demand theory. From an industry perspective, the results highlight the strategic importance of edge AI processors, energy-efficient architectures, and intelligent connectivity ecosystems as future growth engines for semiconductor firms. The study demonstrates that semiconductor market evolution is increasingly governed by computational decentralization and AI ecosystem expansion, offering a robust empirical framework for understanding technology-driven demand transformation in the next generation of digital economies.