The New Paradigm in the Global Tech Ecosystem of 2026: Restructuring of Computing Power and Infrastructure
Editor
As of early 2026, the global tech industry stands at an unprecedented inflection point. The explosive growth of generative AI has led to a surge in demand for computing power, while geopolitical tensions are driving a restructuring of tech supply chains. This is accelerating structural changes across the tech ecosystem, from semiconductors to cloud infrastructure. According to market research firm Gartner, the global AI-related semiconductor market is expected to reach $124 billion in 2026, a 28% increase from the previous year, significantly outpacing the overall semiconductor market growth rate of 12%. The demand for high-performance GPUs and AI-specific chips is particularly skyrocketing, fundamentally reshaping the value chain and competitive structure of the existing semiconductor industry.
At the heart of these changes is the tech supremacy competition between the United States and China. The U.S. Department of Commerce’s new semiconductor export control measures, announced in December 2025, further restricted China’s access to AI semiconductors. In response, the Chinese government announced an additional support package of 200 billion yuan (approximately $28 billion) in January 2026 to foster its domestic semiconductor industry. This geopolitical separation is accelerating the bifurcation of the global tech supply chain, forcing major semiconductor companies like Samsung Electronics (Suwon, Gyeonggi-do) and SK Hynix (Icheon, Gyeonggi-do) to make complex strategic choices between the two camps. Samsung Electronics reported that its memory semiconductor division’s sales increased by 42% year-on-year to 24.3 trillion won in Q4 2025, driven primarily by the surge in demand for high-bandwidth memory (HBM) for AI data centers.
In the semiconductor manufacturing equipment sector, ASML (Veldhoven, Netherlands) still dominates the extreme ultraviolet (EUV) lithography equipment market, but the impact of restricted access to the Chinese market is becoming evident. ASML announced in its January 2026 earnings guidance that its revenue is expected to decrease by 5-8% year-on-year, primarily due to export restrictions to China. Meanwhile, Japanese companies like Tokyo Electron (Tokyo) and Shin-Etsu Chemical (Tokyo) are continuing to grow by expanding their market share in China, indicating a shift in the competitive landscape of the semiconductor equipment market.
Rapid Expansion of AI Computing Infrastructure and New Competitive Dynamics
As the complexity and scale of AI models increase exponentially, the demand for computing infrastructure is surging to unprecedented levels. The computing power required to train OpenAI’s (San Francisco, California) GPT-5 model is estimated to be about 10 times that of GPT-4, and Google’s (Mountain View, California) Gemini 2.0 model is also known to require similar computing resources. This surge in demand is leading to explosive growth in the GPU market, with NVIDIA (Santa Clara, California) reporting a 89% year-on-year increase in Q4 2025 data center revenue to $47.3 billion. Orders for next-generation H200 and B200 GPUs are already sold out through Q3 2026, indicating a severe supply shortage.
This GPU supply shortage is intensifying competition among cloud service providers. Amazon Web Services (AWS, Seattle, Washington) announced an $80 billion investment in AI infrastructure for 2026, a 45% increase from the previous year. Microsoft (Redmond, Washington) also plans to allocate $65 billion annually to expand Azure AI services. Google Cloud is pursuing a differentiated strategy using TPU (Tensor Processing Unit) v5 to expand its market share with AI workload-specialized services. According to Synergy Research Group, AWS held a 31% share, Microsoft Azure 25%, and Google Cloud 11% in the global cloud infrastructure market in Q4 2025, with competition in AI-specialized services becoming even fiercer.
Meanwhile, Chinese companies are accelerating the development of their own AI chips in response to U.S. GPU export restrictions. Baidu (Beijing) unveiled its self-developed AI chip ‘Kunlun 3’ in December 2025, which is evaluated to achieve 80% of the performance of NVIDIA’s A100 GPU. Alibaba (Hangzhou) also launched the ‘Heigang N1’ AI inference chip through its subsidiary Pingtouge Semiconductor, and Tencent (Shenzhen) and Huawei (Shenzhen) are also pursuing their own AI chip development projects. With strong support from the Chinese government, these companies are progressing faster than expected in AI chip development, potentially altering the competitive landscape of the global AI chip market.
In the memory semiconductor market, demand for high-bandwidth memory (HBM) and DDR5 memory optimized for AI workloads is surging. Samsung Electronics announced plans to triple its monthly production capacity of HBM3E products compared to 2025, and SK Hynix is accelerating the development of HBM4 with a target for mass production in the second half of 2026. According to market research firm Omdia, the HBM market is expected to grow 73% year-on-year to $31.4 billion in 2026, with AI data center applications accounting for 85% of the total. As major AI accelerators like NVIDIA’s next-generation GPUs, AMD’s (Santa Clara, California) MI300 series, and Intel’s (Santa Clara, California) Gaudi 3 all require HBM3E or higher memory, the technological competition among memory manufacturers is intensifying.
Data Center Innovation and New Challenges in Energy Efficiency
The surge in AI workloads is bringing fundamental changes to the data center industry. As the transition from traditional CPU-centric data center architecture to GPU and AI accelerator-centric structures accelerates, power consumption and cooling requirements are increasing rapidly. According to the latest report from the International Energy Agency (IEA), global data center power consumption is expected to reach 460 TWh in 2026, an 18% increase from the previous year, with AI workloads accounting for 35% of this total. This represents about 1.8% of global power consumption, putting pressure on data center operators to improve energy efficiency and expand the use of renewable energy.
To address these challenges, major companies are adopting innovative cooling technologies and energy efficiency improvement solutions. Meta (Menlo Park, California) announced in January 2026 that it would fully implement liquid cooling systems in its next-generation data centers, expecting to achieve over 40% improvement in energy efficiency compared to existing systems. Google also applied its machine learning-based cooling optimization system ‘DeepMind for Data Centers v3.0’ to AI-specific data centers, improving power usage effectiveness (PUE) to 1.08. Amazon is continuously improving the energy efficiency of its AWS infrastructure using its self-designed Graviton processors and Inferentia AI chips, and has pledged to achieve 100% renewable energy use in all AWS data centers by 2026.
The data center real estate investment trust (REIT) market is also directly benefiting from the surge in AI demand. Digital Realty Trust (San Francisco, California) reported a 97.2% occupancy rate in Q4 2025, with AI customers’ average power density being 3-4 times higher than traditional customers, resulting in significant rental premiums. Equinix (Redwood City, California) also announced that over 85% of its AI-specialized data center ‘xScale’ capacity had been secured by 2026. In Korea, companies like LG CNS (Seoul) and Naver (Seongnam, Gyeonggi-do) are actively building AI-specific data centers, with Naver planning to complete the second phase expansion of its Chuncheon data center ‘GAK’ in the first half of 2026.
New challenges are also emerging in terms of security and regulatory compliance. With the full implementation of the EU’s AI Act in August 2025, technical requirements for risk classification and regulatory compliance of AI systems are being specified. AI services in high-risk areas such as healthcare, finance, and transportation must meet strict data protection and algorithm transparency requirements, creating new demand for related infrastructure and security solutions. Security specialists like CyberArk (Petah Tikva, Israel) and Palo Alto Networks (Santa Clara, California) are increasing investments in AI workload-specific security solutions, with the convergence of zero-trust security models and AI-based threat detection technologies emerging as new growth drivers.
In the field of quantum computing, commercial applications are becoming more concrete in 2026. IBM (Armonk, New York) unveiled its ‘Flamingo’ processor with 1,121 qubits in December 2025, claiming it outperformed traditional supercomputers in specific optimization problems. Google also announced breakthroughs in quantum error correction with its ‘Willow’ chip and aims to launch commercial quantum computing cloud services in the second half of 2026. China’s Origin Quantum (Hefei, Anhui Province) also claimed to demonstrate quantum supremacy with its 72-qubit ‘Wukong’ system, intensifying international competition in the quantum computing field. According to market research firm BCG, the quantum computing market is expected to grow rapidly from $1.3 billion in 2026 to $85 billion by 2030, with commercialization expected to accelerate in areas such as financial optimization, new drug development, and encryption.
The current restructuring of the tech ecosystem is having a fundamental impact on the global economy and geopolitical order, beyond mere market changes. As countries and companies with AI computing power are expected to determine future competitiveness, major countries, including Korea, are focusing on securing their technological sovereignty and strengthening supply chain stability. The pace of these changes is expected to accelerate further throughout 2026, and it is a critical time for investors and companies to seize new opportunities while paying close attention to risk management during this technological paradigm shift. Companies in the semiconductor, cloud, and data center infrastructure sectors are likely to be the biggest beneficiaries of these megatrends, but their ability to respond to geopolitical risks and regulatory changes will determine their long-term success.
*This analysis is provided for informational purposes only and is not intended as investment advice or a recommendation of specific stocks. Investment decisions should be made based on individual judgment and responsibility.*
