The Semiconductor Industry Redefined by AI

As AI moves from experimentation to large-scale deployment, semiconductors have become more strategically important than ever as the foundation of AI computing.

This optimism is underpinned by the explosive growth in AI computing workloads, driven by the rapid expansion of token consumption. Annual token processing volume is estimated to have increased fifteenfold within a year, with some forecasts suggesting that AI-related semiconductor demand could grow by nearly 90% in 2026.

At the same time, the sustainability of this growth remains a subject of debate. Skeptics argue that the current investment cycle resembles previous semiconductor booms and warn of overcapacity, geopolitical risks, and the eventual return of the traditional silicon cycle. Optimists, however, believe that AI's transformative nature, combined with a paradigm shift in semiconductor technologies, is creating the foundation for a new semiconductor Supercycle.

Meanwhile, advances in AI—including multimodal models and AI agents—are reshaping semiconductor demand beyond GPUs and high-bandwidth memory (HBM) to a broader computing architecture encompassing CPUs, NPUs, and specialized accelerators. At the same time, sovereign technology initiatives, export controls, and economic security policies are fundamentally redefining the industry's competitive landscape.

This paper examines these structural shifts through three strategic lenses: demand, supply, and sovereign risk. By analyzing how these forces are reshaping the semiconductor ecosystem, it aims to provide strategic implications for business leaders navigating the AI era.

Demand is also becoming increasingly diversified. In AI servers, the widening gap between processor performance and memory bandwidth has created the "memory wall," making high-bandwidth memory (HBM) a critical bottleneck for AI infrastructure (4) . HBM capacity is already largely sold out through 2026, accelerating the transition toward new computing architectures built around tightly integrated GPUs and HBM. At the same time, AI workloads are expanding beyond cloud data centers to edge devices, driving demand for dedicated AI chips in smartphones, vehicles, and industrial equipment. Looking ahead, Physical AI—including autonomous vehicles and humanoid robots—is expected to become another major source of semiconductor demand.

Many industry observers therefore view today's AI-driven demand as a structural transformation rather than a temporary cycle, marking the beginning of a new semiconductor Supercycle (5) .
Nevertheless, important uncertainties remain. AI monetization is still in its early stages, and hyperscale’s and AI startups have yet to fully justify their massive infrastructure investments through sustainable revenue generation (6) .
In addition, power infrastructure constraints (7) , geopolitical tensions and export controls could all influence the pace and sustainability of future semiconductor demand (8) .

This technological transition is also being accelerated by supply constraints in leading-edge AI chips. With advanced GPUs remaining in limited supply, maximizing computing performance increasingly depends on packaging, memory integration, and high-speed interconnect technologies rather than processor performance alone.

As a result, competition is expanding beyond computational capability to include thermal management, packaging, and advanced materials. Silicon interposers, glass substrates, and next-generation thermal materials are emerging as critical enablers of AI infrastructure. Competitive advantage is therefore no longer determined solely by transistor scaling, but by the ability to integrate chips more densely and manage heat more efficiently.

Ultimately, competitive advantage in the AI era will depend less on the performance of individual chips than on the ability to design and optimize the entire computing ecosystem by integrating diverse processors with advanced packaging technologies. Alongside these technological shifts, governments are becoming increasingly involved in the semiconductor industry through industrial policy and economic security initiatives. The next chapter examines how technological sovereignty and public policy are reshaping global competition and semiconductor supply chains.