Europe's secret superpower ASML in the chip war: How a single company holds the future of EU chip AI in its hands

How is the market for AI chips developing? Opportunities for the EU market – Can the 43 billion euro plan end our dependence on Asia's AI chips?

Are we on the cusp of the greatest technological revolution of the 21st century? The development of the AI ​​chip market clearly demonstrates that we are at a turning point in the semiconductor industry. While Chinese companies like Huawei are presenting ambitious plans to double their AI chip production, and American giants like Nvidia are grappling with geopolitical challenges, the crucial question arises: What position can and will Europe occupy in this race for the technological future?

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How big is the global AI chip market really?

The global AI chip market is undergoing a period of explosive growth, exceeding even the most optimistic forecasts of the past. Current figures speak for themselves: worldwide revenue in the AI ​​chip segment is projected to reach approximately US$92.74 billion by 2025. This impressive sum, however, is just the beginning of an even more dramatic development.

Experts predict an annual growth rate of 29.11 percent between 2025 and 2030, which would result in a projected market volume of US$332.77 billion by 2030. These figures illustrate not only the enormous potential of the market but also the rapid pace at which the technology is gaining traction.

The distribution of market shares becomes particularly interesting when considering geographical differences. The USA dominates the market with expected revenue of US$13.84 billion in 2025. Germany, as Europe's largest economy, only achieves revenue of approximately US$2.86 billion, highlighting the challenge for Europe.

The growth momentum is also reflected in the monthly figures: Global semiconductor sales rose by 22.7 percent year-on-year in April 2025 to US$57.0 billion. This acceleration of growth compared to previous months underscores the continued strength of the market.

What role does Nvidia play in the AI ​​chip market today?

Nvidia has become a true giant in the AI ​​chip business in recent years, dominating the market with a near-monopoly. The company controls an estimated 80 to 85 percent of the market for AI data center chips, a position underpinned by impressive financial figures.

The financial results speak for themselves: In the first quarter of fiscal year 2026, Nvidia recorded record revenue of $44.1 billion, representing year-over-year growth of 69 percent. The data center segment alone contributed $39.1 billion to this success. For the second quarter, the company projected revenue of $45 billion, which would correspond to year-over-year growth of 50 percent.

This dominant market position is based on several factors. First, Nvidia possesses the most advanced chip architecture, specifically optimized for AI applications. Second, the company benefits from its comprehensive software ecosystem, particularly the CUDA platform, which has fostered a broad developer community. Third, Nvidia recognized the strategic importance of AI chips early on and invested accordingly.

However, the first cracks are appearing in Nvidia's seemingly indestructible position. US export restrictions have significantly impacted its business in China. The company estimates it will lose eight billion dollars in revenue this quarter alone. This development opens doors for competitors, particularly from China and other regions.

How is China reacting to American dominance?

China has recognized the strategic importance of the semiconductor industry and is making every effort to build its own competitive AI chip industry. At the heart of these efforts is Huawei, China's largest technology company, which has made remarkable progress despite years of US sanctions.

Huawei's ambitious plans are impressive: The company plans to produce approximately 600,000 of its flagship 910C Ascend chips next year, doubling this year's output. Overall, production of the Ascend product line is slated to increase to up to 1.6 million dies by 2026. These figures suggest that Huawei and its main partner, Semiconductor Manufacturing International Corp. (SMIC), have found ways to overcome the bottlenecks caused by US sanctions.

Huawei's technological strategy is certainly innovative. While the company openly admits that its individual chips cannot yet compete with Nvidia in terms of computing power, it is pursuing a different approach. Analysts at Bernstein estimate that a single next-generation Ascend 950 offers only six percent of the performance of Nvidia's upcoming VR200 superchip. However, Huawei compensates for this weakness with innovative networking solutions.

The company unveiled its UnifiedBus technology, which enables the interconnection of up to 15,488 Ascend chips. Huawei claims that this technology allows for data transfer between the chips up to 62 times faster than Nvidia's upcoming NVLink144 technology. By pooling this computing power, Huawei hopes to close the performance gap with Nvidia.

The Chinese government is strongly supporting these efforts. Beijing is urging domestic companies to switch to locally developed and manufactured semiconductors and reduce their dependence on foreign suppliers. The authorities want to replace foreign chips, especially in state-owned data centers, and large internet companies like ByteDance and Tencent are also expected to stop using US-made products.

What challenges do Chinese chip manufacturers face?

Despite impressive progress, Chinese chip manufacturers face significant technological and economic hurdles. The biggest challenge lies in manufacturing technology. While Nvidia has access to TSMC's state-of-the-art 4nm nodes, Huawei has to rely on SMIC's outdated 7nm technology.

This technological gap has concrete implications for production efficiency. The chips for the 910 product line are manufactured using an improved version of SMIC's 7nm technology, but this still lags about two generations behind TSMC's technology. Experts therefore doubt whether Huawei can achieve its ambitious production targets with acceptable yields.

The US sanctions are exacerbating these problems. US suppliers of Semiconductor Manufacturing International Corp. (SMIC) are no longer permitted to deliver products to the company's most advanced plant. These restrictions could disrupt production at the "SMIC South" plant, which experts believe is currently the only facility capable of manufacturing state-of-the-art smartphone chips, for up to nine months.

Another problem is acceptance among major customers. So far, Huawei's key clients have largely used the company's best semiconductors only for inference purposes or to run AI models after training them. Whether they are ready to switch completely to Huawei's solutions remains to be seen.

Nevertheless, initial successes of alternative Chinese suppliers are already becoming apparent. Chip designer Cambricon recorded a revenue increase of more than 4000 percent in the first half of 2025. While this dramatic increase is partly due to the US export bans on Nvidia chips, it also demonstrates the potential of domestic solutions.

How is Europe positioning itself in the global AI chip race?

Europe finds itself in an ambivalent position in the global race for AI chips. On the one hand, the continent boasts some of the world's leading technology companies, but on the other hand, it lags significantly behind in actual chip production. Current market shares speak volumes: Europe currently holds only about nine to ten percent of the global semiconductor market.

The EU has recognized this strategic weakness and launched an ambitious counter-program with the Chips Act. This package of measures aims to mobilize €43 billion in public and private investment to increase Europe's share of the global semiconductor market from its current level of around ten percent to 20 percent by 2030. In 15 member states, 68 concrete and strategically important funding projects totaling €22 billion have already been announced.

A key component of this strategy is attracting international chip giants to Europe. TSMC, the world's largest contract manufacturer, has begun construction of a ten-billion-euro semiconductor plant in Dresden. Approximately half of the financing is covered by government subsidies, and production is scheduled to begin at the end of 2027. TSMC is already considering further chip factories in Europe, focusing on the AI ​​chip market.

What strengths does Europe have in the semiconductor industry?

Despite lags in mass production, Europe possesses impressive strengths in the semiconductor industry. The Dutch company ASML exemplifies these strengths. ASML is the world's only manufacturer of lithography systems using extreme ultraviolet (EUV) technology, which is essential for the production of state-of-the-art chips under 7 nanometers.

With a global market share of 80 to 90 percent for lithography equipment and a company value of approximately €270 billion, ASML is the most valuable technology company in Europe. The company's highly complex machines are roughly the size of a bus, require three Boeing 747s for delivery, and cost between €185 and €360 million. This technology is so specialized that even the world's largest chip manufacturers rely on ASML.

Germany is home to Infineon, one of the world's leading manufacturers of power semiconductors. In 2023, Infineon invested around five billion euros in the construction of a semiconductor manufacturing facility for analog/mixed-signal and power semiconductors. In chip manufacturing, European manufacturers such as Infineon, STMicroelectronics, and NXP currently hold a market share of approximately eight to nine percent of the global market.

Europe is also a world leader in the production of machines that print tiny semiconductor tracks onto silicon circuit boards, as well as in the production of key chemicals and gases for semiconductor manufacturing. These strengths in the supply industry form an important foundation for the expansion of the European chip industry.

What challenges must Europe overcome?

Europe's ambitions in the AI ​​chip sector face significant challenges. The European Court of Auditors has already expressed doubts as to whether the 20 percent target can be achieved by 2030. Because more new semiconductor plants are being built in Asia and the USA, the European share could even decline further.

A particularly serious setback was the indefinite postponement of the Intel plants in Magdeburg. These plants were the largest European semiconductor project, with planned investments of more than 30 billion euros. Because the largest subsidies are concentrated on a few companies, individual delays or cancellations have a significant impact on the overall goal.

The complexity of the semiconductor value chain presents a further challenge. Without a comprehensive strategy that includes holistic production in Europe, the goal remains only half-heartedly achieved. The complex and labor-intensive testing, assembly, and packaging of the chips continues to take place almost exclusively in low-wage Asian countries.

Europe is currently heavily dependent on Asian semiconductor supplies. 62 percent of the semiconductors used in Germany come from just five Asian countries, with Taiwan being the largest supplier (23 percent). This dependence makes European industry vulnerable to geopolitical tensions and supply chain disruptions.

What role will AI inference chips play in future developments?

AI inference chips represent a particularly dynamic and high-growth segment of the AI ​​chip market. These specialized processors are optimized to execute pre-trained AI models and make real-time decisions. The global AI inference chip market is estimated to reach approximately US$15 to US$18 billion by 2025 and is projected to grow at a compound annual growth rate (CAGR) of 35 to 40 percent until 2032.

The applications for inference chips are diverse and growing rapidly. Image and speech recognition dominate the market with approximately 45 percent market share, followed by Natural Language Processing (NLP), which benefits from the increasing integration of AI-powered chatbots, virtual assistants, and language translation services.

Edge computing is further driving demand for inference chips. Processing AI models directly on end devices such as smartphones, surveillance cameras, or autonomous vehicles requires specialized, energy-efficient chips. This development enables real-time decisions without reliance on cloud servers, while simultaneously improving data privacy and reliability.

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How are the market shares developing among the major chip manufacturers?

Market dynamics among the major chip manufacturers are showing clear shifts. AMD is continuously gaining market share from Intel, particularly in the lucrative server segment. According to recent data from Mercury Research, AMD has steadily increased its market share of Epyc server processors, and a 40 percent market share is expected by 2027.

Particularly noteworthy is AMD's success in the cloud business, where the company already holds over 50 percent market share. In the desktop segment, AMD achieved a market share of 32.2 percent in the second quarter of 2025, the highest figure in recent times.

Intel, on the other hand, is in a difficult situation. The once largest chipmaker in the world still achieved a market share of 99 percent in server processors in 2017. Today, experts estimate that it only holds around 55 percent, and the trend is continuing downward.

The financial figures reflect this market development. AMD boasts a gross margin of around 51 percent, while Intel struggles with margins that have shrunk to 33 percent. While Intel had to record a net loss of $20.5 billion last year, AMD remained profitable with a profit of $2.73 billion.

TSMC, the world's largest contract manufacturer, benefits from this development, as both AMD and Nvidia have their most advanced chips manufactured by the Taiwanese company. In January 2025, TSMC became the third company worldwide to achieve a revenue exceeding US$200 billion.

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What significance do proprietary AI chips have for technology companies?

Developing their own AI chips is increasingly becoming a strategic imperative for large technology companies. Apple's M series impressively demonstrates how successful this strategy can be. Since the introduction of the M1 chip in 2020, Apple has not only revolutionized the performance of its Mac computers but also ushered in a new era of chip integration.

The success of Apple Silicon is based on the combined encapsulation of GPU, CPU, and memory, as well as the maximum number of in-house designed cores. This highly integrated architecture offers both low power consumption and high performance, making the M1 Mac products significantly more powerful than their predecessors with Intel processors.

Apple is already working on the next generation of its own chips. The M6 ​​processors, codenamed "Komodo," and the M7 chips, codenamed "Borneo," are currently under development. Both are expected to represent a significant leap forward, particularly in the area of ​​AI capabilities. In parallel, Apple is developing "Sotra," a chip that could set new performance standards.

Apple's work on specialized AI chips for smart glasses is particularly interesting. For the first time, the company is developing its own chips specifically for augmented reality applications, based on the energy-optimized architecture of the Apple Watch. These chips are designed to control multiple cameras simultaneously and are optimized for smart glasses, which are expected to launch in 2026 or 2027.

Apple is also pursuing an independence strategy with its mobile chips. Since 2019, the company has been working on its own 5G modems and acquired Intel's modem division for one billion dollars. The goal is to create a single component that combines cellular, Wi-Fi, and Bluetooth and can later be fully integrated into Apple's M-series system-on-a-chip.

How are the requirements for AI chips changing?

The requirements for AI chips are evolving rapidly and becoming increasingly specific. While early AI applications relied primarily on general GPU power, modern applications require highly specialized solutions for different areas of use.

Training large AI models still requires extremely powerful chips capable of performing massive parallel calculations. Nvidia's H100 and upcoming H200 chips continue to dominate the market in this area. These processors are designed to train complex neural networks with trillions of parameters.

For inference applications, however, other properties take precedence. Here, energy efficiency, low latency, and the ability to execute pre-trained models quickly and cost-effectively are paramount. Edge computing applications additionally require compact form factors and the ability to function without a permanent internet connection.

The automotive industry is pushing ahead with the development of specialized automotive AI chips. These chips must withstand extreme temperature fluctuations, operate with high reliability, and be able to make safety-critical decisions in real time. Companies like Tesla, as well as traditional automakers, are investing heavily in the development of their own AI chips for autonomous vehicles.

What geopolitical factors influence the AI ​​chip market?

The AI ​​chip market is heavily influenced by geopolitical tensions, which significantly impact market dynamics. The US has continuously tightened its export controls on semiconductor technology to China, enacting its most comprehensive restrictions to date in December 2024.

The new US regulations prohibit access to 24 different types of chip manufacturing equipment and three software programs. Of particular significance is the removal of the previous 25 percent threshold for US components in foreign chip manufacturing facilities. Going forward, all equipment containing US technology will be subject to export restrictions.

These measures have far-reaching consequences. Experts believe the new regulations could have devastating effects on Chinese chip factories and immediately halt further expansion of Chinese production capacity. Existing manufacturing facilities could be severely restricted or rendered inoperable within six months.

China is responding with its own countermeasures. The Chinese government has launched an investigation into Nvidia for possible violations of the anti-monopoly law. At the same time, Beijing is urging domestic companies to switch to locally developed and manufactured semiconductors.

Europe is attempting to develop an independent position within this complex situation. The EU Chips Act aims to reduce strategic dependence on other regions. However, key European allies of the US, such as the Netherlands and Japan, are hesitant to support new US sanctions. They have shown little interest in further measures so far, even though both countries partially supported previous sanctions.

What does this development mean for consumers and businesses?

The rapid development of the AI ​​chip market has a direct impact on consumers and businesses. Smartphones are increasingly being equipped with specialized AI chips that enable local AI functions such as image recognition, speech processing, and intelligent camera features. These so-called NPUs (Neural Processing Units) are becoming standard in devices from Apple, Google, Qualcomm, and other manufacturers.

New opportunities are opening up for companies, but also new challenges. The increasing availability of powerful and energy-efficient AI chips makes it possible to implement AI applications directly in production facilities, monitoring systems, or autonomous vehicles. This can lead to significant efficiency gains and new business models.

At the same time, new dependencies and risks are emerging. Companies must choose between different chip architectures and ecosystems, with each choice having long-term strategic consequences. Geopolitical tensions can disrupt supply chains and lead to shortages.

The cost of AI hardware remains a significant factor. While chip performance is increasing exponentially, prices for the most advanced solutions are still very high. This can exclude smaller companies from accessing cutting-edge AI technology and exacerbate market concentration.

What future scenarios are conceivable for the EU market?

Several future scenarios are conceivable for the European AI chip market, depending on political decisions made in the coming years. In the most optimistic scenario, Europe succeeds in building an independent, competitive AI chip industry through the Chips Act and targeted investments.

In this scenario, European strengths in the supplier industry, particularly at companies like ASML, would be leveraged as the basis for vertical integration. TSMC and other Asian chip giants would significantly expand their production capacities in Europe and establish local supply chains. Simultaneously, European companies such as Infineon, STMicroelectronics, and NXP would intensify their activities in the AI ​​chip sector and develop new, specialized solutions.

A more realistic scenario envisions Europe as an important, but not dominant, player in the global AI chip ecosystem. In this case, Europe would expand its strengths in niche areas, such as energy-efficient edge computing chips or specialized automotive AI processors. The region would benefit from its strong automotive industry and leading industrial companies that have specific requirements for AI hardware.

The most pessimistic scenario would see Europe as a dependent importer of AI chips from Asia and the US. In this case, the ambitious goals of the Chips Act would be missed, and Europe would remain reliant on external suppliers. This would undermine strategic sovereignty and make Europe vulnerable in future technological conflicts.

What strategic recommendations can be made for Europe?

The analysis of global AI chip development yields several strategic recommendations for Europe. First, Europe should consistently build on its existing strengths. ASML, as an indispensable supplier to the global chip industry, should be further strengthened and protected from foreign takeovers. Its technological leadership in EUV lithography is a tremendous strategic advantage.

Secondly, Europe should focus on specialization rather than direct competition with the US or China. Instead of trying to surpass Nvidia in high-end training chips, Europe should concentrate on niche areas such as automotive AI, industrial IoT chips, or energy-efficient edge computing solutions. Here, Europe can leverage its industrial strengths.

Thirdly, closer coordination between EU member states is essential. The success of the Chips Act depends on national interests taking a back seat to common European goals. Germany, France, the Netherlands, and other key technology hubs must better coordinate their activities.

Fourth, Europe should invest in research and education. The shortage of qualified specialists in the semiconductor industry is a critical bottleneck. Universities and research institutions must be strengthened and more closely integrated with industry.

Fifth, a pragmatic approach to international partnerships is important. Europe should selectively cooperate with trusted partners such as Japan, South Korea, or Taiwan, without completely isolating itself from other regions. Technological sovereignty does not mean technological isolation.

What are Europe's chances in the global AI chip race?

The development of the AI ​​chip market presents Europe with one of the greatest industrial policy challenges of the coming decade. With a projected market volume of over US$330 billion by 2030, the stakes are high. Europe has both significant strengths and considerable weaknesses in this race.

The strengths are undeniable: ASML as a technological gatekeeper, a strong automotive industry as a customer for specialized AI chips, leading industrial companies with specific requirements, and the political will to invest 43 billion euros in the semiconductor industry. These factors provide a solid foundation for building a European AI chip industry.

At the same time, the challenges are considerable. The existing market dominance of Nvidia, TSMC, and other Asian players cannot be overcome in the short term. Geopolitical tensions between the US and China create additional uncertainties, and complex global supply chains cannot simply be relocated to Europe.

Europe's success will ultimately depend on its ability to set realistic goals and pursue them consistently. Instead of trying to become a leader in every area, Europe should focus on specialization and leveraging existing strengths. The automotive industry, industrial automation, and energy-efficient edge computing solutions offer promising niche markets.

The coming years will show whether Europe can make the leap from importer to major producer of AI chips. The foundations are in place, but implementation requires political will, industrial coordination, and strategic patience. In a world where AI chips determine technological sovereignty, Europe cannot afford to play a secondary role.

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