AI Drives Semiconductor Market to $2.3 Trillion Horizon

McKinsey & Company reported on September 18, 2026, that artificial intelligence (AI) is reshaping the semiconductor market. The firm stated that AI is driving semiconductor growth, with leading-edge chips and High Bandwidth Memory (HBM) influencing data center capital expenditures. This growth is projected to push the semiconductor market to a $2.3 trillion horizon.

The details

AI is identified as a primary engine of economic activity. The AI ecosystem spans multiple levels, from foundational research to application development. This expansion leads to increased demand for specialized semiconductors. The semiconductor market forecast indicates a potential value of $2.3 trillion, representing the horizon for AI's impact on the industry. Specific components like leading-edge chips and HBM are central to this development, as they are essential for processing the complex algorithms and vast datasets required by AI systems. These advanced components are shaping capital expenditures within data centers, which serve as the physical infrastructure for AI operations.

Data center buildouts are attracting capital, even in an environment where interest rates are climbing and cash is earning returns elsewhere. AI spending continues to pull capital like a magnet, indicating its priority in investment strategies. This sustained investment is driven by the fundamental need for computational power to develop and deploy AI models. ON Semiconductor Corporation anticipates its AI data center business will more than double in 2026, indicating specific company growth within this sector. This growth is a direct consequence of the increasing demand for power management and sensing solutions critical for AI data centers. The iShares Semiconductor ETF (SMH) and VanEck Semiconductor ETF (SOXX) are considered 'Buys' by some analysts. This assessment is due to AI-driven capital expenditure fueling demand for semiconductors, suggesting a positive outlook for the sector's financial performance. Semiconductors are positioned to benefit directly and early from this spending cycle.

Why it matters

AI infrastructure is moving capital, reshaping U.S. power, investment, and technology markets. The construction and operation of AI data centers require substantial investment in physical infrastructure, including land, buildings, and specialized cooling systems, in addition to the semiconductors themselves. Investment in AI data centers could reach $50 trillion by 2050, according to Al Majalla, highlighting the scale of this infrastructure race. The location of these new economic 'factories' will be determined by factors such as the availability of electricity, access to advanced semiconductors, and data laws. For instance, the Senate blocked the Ratepayer Protection Act, a bill that could have impacted the expansion of U.S. data centers. This legislative action suggests that regulatory frameworks are adapting, or struggling to adapt, to the rapid growth and energy demands of AI infrastructure. The blocking of such legislation can influence the operational costs and expansion capabilities of data centers, thereby affecting the broader AI ecosystem.

Semiconductors are integral to this expansion, serving as the foundational technology for AI. They are 'paid first' in the AI spending cycle, meaning that investment in AI capabilities directly translates into demand for semiconductor products. This foundational role means that the performance and availability of semiconductors directly impact the pace of AI development and deployment. The rising demand for semiconductors is a direct consequence of AI's economic impact, creating a feedback loop where AI advancements drive semiconductor innovation and production. This demand influences market valuations and investment strategies across the technology sector, as companies vie for access to critical components and investors seek to capitalize on the growth. The capital expenditure on AI infrastructure, particularly in data centers, is a significant driver of this demand. The need for high-performance computing, enabled by leading-edge chips and HBM, necessitates substantial upfront investment in hardware. This investment, in turn, stimulates further innovation in semiconductor design and manufacturing, creating a virtuous cycle of technological advancement and economic growth. The increasing energy consumption of AI data centers also presents a second-order effect, impacting power grids and potentially influencing energy policy and infrastructure development.

What to watch

Future reports from McKinsey & Company and other market intelligence firms will detail the ongoing impact of AI on semiconductor market valuations and data center capital expenditure trends. Monitoring legislative developments, such as those related to data center regulation and energy policy, will be crucial for understanding the operational environment for AI infrastructure. The performance of semiconductor-focused exchange-traded funds (ETFs) and individual semiconductor companies will serve as indicators of sustained investment and growth in the sector. Additionally, observing trends in the development and adoption of leading-edge chips and HBM will provide insight into the technological advancements driving the AI market. The interplay between technological innovation, capital investment, and regulatory frameworks will continue to shape the trajectory of the AI-driven semiconductor market.