AI Semiconductor Market Set to Reach $753B by 2030
Morgan Stanley forecasts the global AI semiconductor market will reach $753 billion by 2030, with a 30% compound annual growth rate and a value equal to about half of the global semiconductor market. The AI semiconductor market could exceed $485 billion this year under an optimistic scenario.
The report names 23 Taiwanese companies that may benefit, including TSMC, MediaTek, United Microelectronics, ASE Technology, King Yuan Electronics, WinWay, Alchip, Global Unichip and others across foundry, memory, testing, equipment and chip design. Morgan Stanley also expects Nvidia’s revenue to grow 70% in 2027, driven by demand for GPUs and customised ASICs.
Cloud service providers’ capital spending is expected to keep rising but grow more slowly. Spending by the 14 largest listed providers could approach $1.6 trillion by 2028, while annual growth may slow from 99% this year to 60% next year and 12% in 2028. The report says this reflects a higher spending base rather than the end of AI demand.
HBM supply remains a major constraint. Even including China’s CXMT capacity, global HBM supply could fall short of demand by 17% in 2026 and 15% in 2027. Rising costs may pressure chip designers’ margins, while non-AI and smaller semiconductor companies risk being crowded out.
Neutral
The direct impact on cryptocurrency markets is likely neutral because the report covers semiconductor demand, Taiwanese equities and cloud infrastructure rather than crypto assets. It may still influence crypto indirectly. Strong AI chip demand supports the infrastructure narrative behind AI-related tokens and could improve sentiment toward technology-linked digital assets. However, the expected slowdown in cloud capital-spending growth may limit near-term enthusiasm if traders interpret it as a sign that AI infrastructure investment is approaching a peak.
The persistent HBM shortage and supply-chain constraints could support semiconductor prices and selected technology stocks, but they also raise production costs and execution risks. Historically, AI-related equity rallies have sometimes lifted AI tokens through sector-wide risk appetite, while disappointing capital-expenditure guidance has triggered sharp rotations away from speculative assets. For crypto traders, the main indicators to monitor are Nvidia’s outlook, major cloud providers’ capital-spending announcements, Taiwan semiconductor equities, AI-token trading volume and broader liquidity conditions.
In the short term, the news is more likely to create selective optimism than a broad crypto rally. Over the long term, continued AI infrastructure expansion could support AI-focused crypto projects, but the report does not provide a direct catalyst for Bitcoin, Ethereum or other major tokens. Therefore, the overall market classification is neutral.