🤖 Did you know that the computing power required for AI training doubles every 5.5 months? Since 2010, this growth rate has reached 4.6x annually. This is not just a temporary boom. Here's what's really happening in the semiconductor industry—a seismic transformation.
The Core of the "Bubble" Debate: Why AI Demand Is Real
Skepticism about generative AI persists. Many compare it to the real estate bubble of the 1990s or the dot-com bubble of the 2000s. However, the data tells a fundamentally different story about today's semiconductor demand.
According to the World Semiconductor Trade Statistics (WSTS), the global semiconductor market reached $772.2 billion in 2025, recording a remarkable 22.5% year-over-year growth. What's striking is that this growth is concentrated in memory and logic semiconductors. AI-focused GPUs and HBM (High Bandwidth Memory) are driving the market, while other segments remain largely flat—a clear "bifurcation" in the industry.
Unprecedented Computing Demand: The Numbers Tell the Truth
The reason AI semiconductor demand cannot be called a "bubble" lies in the continuous and predictable growth of computing requirements.
According to analysis by Preferred Networks (PFN), the computing power needed to create state-of-the-art AI models has been doubling every 5.5 months since 2010. This translates to approximately 4.6x annually, or about 1 million times over a decade. Even more striking is that AI inference demand exploded in late 2024, recording an 80x year-over-year increase.
Google's usage exemplifies this trend: their token consumption grew from 480 trillion in May 2025 to 980 trillion just two months later—nearly doubling. This demonstrates the rapid adoption of AI in software development.
NVIDIA's Dominance and the "Winners' Circle"
NVIDIA has benefited most from this transformation. Commanding approximately 90% of the AI semiconductor market, the company topped the global semiconductor rankings in Q2 2025. Their Data Center segment alone achieved an operating profit margin exceeding 75%—an extraordinary figure for any manufacturing business.
However, industry-wide, the "AI boom" benefits only a handful of companies. As Masahiko Todoroki, Managing Executive Officer at Shin-Etsu Chemical, noted: "Today's semiconductor industry cannot be described in a single phrase." The divide between "AI and everything else" is becoming increasingly stark.
Test equipment giant Advantest doubled its profits riding AI semiconductor demand, while many Japanese manufacturers focusing on MCUs and analog semiconductors continue to struggle.
Japan's Semiconductor Industry: Where the Real Strengths Lie
Japan's semiconductor industry, which once commanded over 50% global market share, has shrunk to below 10%. However, the country maintains overwhelming presence in manufacturing equipment and materials:
- Silicon Wafers: Over 50% global share
- Photoresist: Approximately 90% global share
- Cleaning and Inspection Equipment: 60-80% global share
Global semiconductor manufacturing equipment sales reached a record $33.66 billion in Q3 2025. The Semiconductor Equipment Association of Japan (SEAJ) forecasts Japanese equipment sales will reach ¥6 trillion ($40 billion) by fiscal year 2027.
Companies like Tokyo Electron, Advantest, Disco, and SCREEN Holdings are essential to AI semiconductor manufacturing. As AI proliferates, demand for their equipment will only intensify.
The Rapidus Challenge: Domestic 2nm Semiconductor Production
Rapidus, established in 2022, has become the symbol of Japan's semiconductor strategy. The company is building a state-of-the-art 2nm process semiconductor facility in Chitose, Hokkaido, targeting mass production by 2027.
This government-led project has attracted investment from eight major Japanese corporations including Toyota, Sony, NTT, and Denso. Total government support is estimated at ¥10 trillion ($67 billion) over ten years.
The 2nm generation that Rapidus will adopt employs a new technology called GAA (Gate-All-Around) structure. This evolution from the conventional FinFET structure surrounds transistors with nanosheets from all directions, achieving both performance and power efficiency.
Notably, Rapidus is developing an AI-assisted design tool called "Raads." Leveraging large language models (LLMs), it aims to reduce design time by 50% and design costs by 30%.
TSMC Kumamoto: Revival of "Silicon Island Kyushu"
The other pillar of Japan's strategy is the entry of TSMC, the world's largest foundry, into Kumamoto Prefecture. Following the first factory that began operations in 2024, construction of a second factory with an investment of approximately $14 billion (¥2.1 trillion) began in October 2025.
The second factory initially planned to manufacture at 6nm and 4nm processes, but reports suggest it may shift to cutting-edge 2nm process technology in response to surging AI semiconductor demand. If realized, this would also serve as a competitive response to Rapidus.
TSMC's entry has attracted over ¥6 trillion ($40 billion) in semiconductor-related capital investment to Kyushu, with more than 40 companies from Kanto and Chubu regions and 11 from overseas announcing expansion plans. The revival of Kyushu's "Silicon Island" semiconductor industry is becoming increasingly tangible.
The Coming "Inference Economy"
Current AI demand centers on the "training" phase, but a shift toward the "inference" phase is underway. This involves deploying models trained in data centers to edge devices like PCs, smartphones, and automobiles.
This shift could fundamentally restructure the semiconductor market. Inference doesn't necessarily require NVIDIA's GPUs, opening opportunities for more power-efficient and affordable processors. This could present new opportunities for Japanese companies specializing in MCUs and analog semiconductors.
For OpenAI's GPT-4, training costs were estimated at approximately $150 million, while annual inference service costs reach roughly $2.3 billion—over 15 times higher. The expansion of the inference market is certain to become the center of future semiconductor demand.
Energy: The New Constraint
The biggest constraint on AI growth is no longer semiconductor supply—it's energy. Next-generation AI data centers consume power on the scale of several gigawatts. One gigawatt is equivalent to a large nuclear power plant, roughly the electricity consumption of one million people.
Microsoft CFO Amy Hood has noted that the biggest constraint on AI infrastructure is no longer semiconductors. Securing power and transitioning to green energy is becoming the new battleground in AI competition.
Conclusion: Can Japan Forge a "Third Path"?
AI is not a bubble. The continuous growth in computing demand proves this. The question is how to ride this massive wave.
Japan leads the world in manufacturing equipment and materials while lagging significantly in cutting-edge logic semiconductor manufacturing. The country is attempting to fill this gap with two pillars: Rapidus and TSMC Kumamoto.
Challenges remain substantial. Talent shortages are severe, and competition with TSMC and Samsung for skilled workers is fierce. Rapidus's 2027 mass production target faces significant technical hurdles.
Still, amid rising geopolitical risks, Japan's semiconductor revival holds significant meaning for a world seeking alternatives to Taiwan concentration. Japan is being called upon to pursue a "third path"—leveraging strengths in equipment and materials while securing a meaningful presence in advanced manufacturing.
In Japan, discussions like these are unfolding around AI and semiconductors. What initiatives are progressing in your country regarding AI industry and semiconductor policy? We'd love to hear about government support measures, industry trends, and the level of public interest in your region.
References
- https://www.jeri.or.jp/survey/202512-202601_10/
- https://eetimes.itmedia.co.jp/ee/articles/2601/20/news040.html
- https://eetimes.itmedia.co.jp/ee/articles/2507/14/news046.html
- https://news.mynavi.jp/techplus/article/20251226-3875940/
- https://ainow.jp/rapidus-japan-semiconductor/
- https://daily-gadget.net/pickup/103526/
- https://www.nikkei.com/article/DGXZQOJC123HQ0S5A111C2000000/
Reactions in Japan
I feel the '5.5 month doubling of computing' firsthand on the job. Delivery inquiries are incomparable to last year. AI semiconductor demand is at abnormal levels. But traditional products have excess inventory. The bifurcation is intense.
The point about energy becoming the bottleneck over semiconductors is spot-on. An era where AI data centers consume the power of one nuclear plant. We need a national discussion on whether to prioritize renewable energy or nuclear restart.
So buying NVIDIA is the winning move? Japanese equipment makers aren't bad, but the winner-takes-all structure is becoming clear and tough. Advantest stock is up, but how long will it last?
80x increase in inference demand—is it because we're using ChatGPT daily? Can't let go of GitHub Copilot, and yes, work methods have changed. But honestly, this dependency is scary.
I can feel the excitement in Chitose from Rapidus. But can they really start mass production in 2027? Technical hurdles seem high, and I hear they're short on talent. Half hopeful, half anxious.
Land prices might jump again with TSMC's second factory groundbreaking. Honestly smells like a bubble. Even with the factory, who knows what things will look like in 30 years. Residents are mixed between hope and confusion.
More than whether AI is a bubble, it's a valuation issue. NVIDIA's PER remains elevated. Even if demand is real, investors get burned if stocks are overvalued. We should watch the spillover to the real economy more closely.
Rapidus succeeding with 2nm is an uphill battle. Even with IBM tech transfer, mass production is different. Some see TSMC considering 2nm in Kumamoto as a check on Rapidus. Competition is welcome though.
Is the government's ¥10 trillion support appropriate as industrial policy? It could distort market principles. The 'Japan Inc.' semiconductor era of the 80s succeeded but later declined. Hoping for different results this time.
Getting tons of questions from viewers about AI semiconductors. People are interested. But it's too technical to explain easily. Many don't get what '2nm' means, right? Wish there was more accessible coverage.
Thought this was irrelevant to small factories like ours, but our clients are increasing semiconductor-related work. Precision parts demand is growing, which helps. But price pass-through remains tough.
Semiconductor job postings are exploding on job sites. Salaries are good too. But it looks like hard work, and who knows what the industry will look like in 10 years. My current company isn't bad either.
The power consumption issue of AI semiconductors should be discussed more. They say they aim to run on green energy, but can Japan realistically secure that much renewable energy? Oppose industrial policy that ignores environmental impact.
Watched this industry for 40 years, seen many booms and busts. This AI boom won't last forever either. However, the computing demand growth trend itself is real. There will be temporary corrections, but...
Using AI constantly in the lab. Efficiency has skyrocketed for literature surveys and coding. Never thought about the massive infrastructure behind it. Educational.
Semiconductor-related loan applications are increasing. As reviewers, our industry knowledge isn't keeping up. Honestly don't understand AI semiconductors well. But management says handle it. Studying now.
Want to see more Japanese AI semiconductor startups. There's room for design-focused companies targeting niche areas. But the funding environment is still lacking. Less than 1/10 the scale of US VCs.
From a Silicon Valley VC perspective, opinions differ on whether AI is a bubble. But computing demand growth is proven by numbers. Japan's strength in equipment and materials is real, but design capability and software talent remain challenges.
Working at a German semiconductor research institute, we always watch Japanese equipment makers. Their cleaning and inspection equipment precision is world-class. But talent drain is also a European problem—people being poached by TSMC and Samsung.
NVIDIA's dominance won't last forever. AMD and Intel are strengthening AI chips, and AWS and Google are developing their own. The power map in 5 years might look completely different from today.
As a Korean memory maker, we feel the HBM demand explosion. Competition between Samsung and SK Hynix is fierce, but our dependence on NVIDIA is more concerning. Japan's moves are noteworthy from a supply chain health perspective.
As a Taiwanese, TSMC's Kumamoto expansion brings mixed feelings. There are technology leakage concerns, but geopolitical risk diversification makes sense. I'm honestly skeptical if Rapidus can really mass-produce 2nm. TSMC has over 30 years of accumulation.
On the receiving end of US CHIPS Act subsidies, but honestly Japan's industrial policy seems faster. Our congressional approval process takes too long. National projects like Rapidus are somewhat enviable.
For Indian startups, AI semiconductor costs remain a barrier. If inference chips become cheaper, AI adoption in developing countries will advance. Japan can contribute significantly in power-efficient chips. Looking forward to the edge AI market.
France is also strengthening semiconductor policy, but the scale is smaller compared to Japan and the US. Whether EU can coordinate is the challenge. I think STMicroelectronics and Infineon need stronger collaboration.
From China's perspective, Japan-US semiconductor policies look like part of a containment strategy. But realistically, we understand the need to produce advanced semiconductors domestically. The localization movement won't stop.
Australia has no presence as an AI semiconductor production hub, but this trend matters as consumers. Data center power issues might be a business opportunity for Australia with its high renewable energy ratio.
From Brazil's tech industry, Japan and the US seem like distant worlds. But we're already using AI tools daily. This article made me think about the importance of semiconductors supporting that infrastructure.
As a Swedish energy company, we're watching AI data center power demand closely. Power consumption equivalent to one nuclear plant is shocking. Nordic cheap hydro and wind power might give us an advantage in attracting data centers.
Vietnam's semiconductor industry is still assembly-focused, but we welcome Japanese company expansion. If back-end processing advances, there's opportunity for us too. Talent development is the biggest challenge.
As a Swiss financial analyst, AI stock valuations concern me. But as the article points out, the computing demand growth trend is real. Despite short-term corrections, I'm bullish medium to long term.
AI is a hot topic in Nigeria's tech community too. But we weren't conscious of the semiconductor supply structure. Now I realize we're part of the global supply chain. Hope data centers come to Africa too.