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The Era of AI Hegemony Competition: A Proposal for a Liberal Bloc Compute Alliance and Strategies for Securing South Korea's Strategic Autonomy
Executive Summary
Executive Summary
The AI hegemony competition is evolving beyond a mere contest for technological superiority into a complex geopolitical conflict intersecting global supply chains, security alliances, and data sovereignty. With the United States occupying approximately 75% of global AI computing capacity, a 'Compute Alliance' among liberal bloc allies is taking shape. South Korea, Taiwan, and Japan effectively dominate the AI core hardware value chain, including HBM, granting them significant leverage as strategic suppliers for a US-led alliance. However, they are simultaneously exposed to dual pressures: the US's technology control policies and their economic ties with China. As exemplified by the restriction of Anthropic's overseas access, the current structure involves simultaneous cooperation and control. In this context, allies are called upon not for simple bloc alignment, but for the acquisition of sophisticated strategic autonomy, comprising three pillars: leveraging their core supply chain positions, building multi-layered AI cooperation networks, and deepening domestic AI technological self-reliance. South Korea, in particular, must utilize its leadership in HBM through Samsung Electronics and SK Hynix, along with its large-scale semiconductor investment plans, to establish an active partner status within the compute alliance. Concurrently, it must pursue independent cooperation channels with the EU, Japan, and the Global South to diversify geopolitical risks arising from dependence on a single bloc.
Phase 1: Issue Situation Analysis
AI Hegemony Competition and the Liberal Bloc's Compute Alliance Proposal: Reshaping the Technological and Industrial Landscape
Issue Situation Analysis
1. Background and Progress of the Issue
The AI hegemony competition has evolved beyond a simple contest for technological superiority into a geopolitical conflict that is reshaping national security and economic order. Its starting point was the US's systematic efforts to block China's acquisition of advanced AI capabilities by strengthening export controls on core AI technologies and semiconductor supply chains. In this process, the control over AI computing infrastructure—namely GPUs, HBM, and data centers—has emerged as a key variable in technological hegemony.
From a historical perspective, the US has progressively blocked China's access to AI chips through Export Administration Regulations (EAR) and the expansion of its Entity List. In response, China has accelerated the development of its own AI semiconductors, such as the Huawei Ascend chip, while simultaneously pursuing a strategy of expanding its AI infrastructure exports to Global South countries. This trend of technological decoupling between the US and China has naturally provided the backdrop for liberal bloc allies to seek the establishment of joint AI computing infrastructure, leading to the concept of a 'Compute Coalition'.
Structural changes have also been underway in the supply chain dimension. The core hardware value chain for AI infrastructure—including memory semiconductors, substrates, and optical components—is effectively dominated by South Korea, Taiwan, and Japan [14]. These nations have thus ascended to a strategic supplier position that neither side in the US-China AI hegemony competition can easily afford to alienate. Notably, South Korea's Samsung Electronics and SK Hynix securing leadership in High Bandwidth Memory (HBM), which resolves the memory bottleneck issue in AI computing [5], has significantly enhanced these countries' negotiating power.
2. Current Situation (Latest Trends)
Currently, the proposal for an AI Compute Alliance is materializing simultaneously in multiple regions. The US-led strategy for expanding AI infrastructure is rapidly becoming a reality through cooperation with allies, with NVIDIA at its center. NVIDIA CEO Jensen Huang recently visited South Korea, signing broad cooperation agreements to build an integrated AI ecosystem encompassing memory, data centers, robotics, and smart factories [13]. SK Telecom and NVIDIA have also announced a partnership to build a gigawatt-scale AI cloud in South Korea [1].
The South Korean government is also elevating AI infrastructure investment to the level of national strategy. Samsung Electronics is reportedly planning an unprecedented investment of 1,000 trillion KRW in the domestic AI semiconductor sector [15], and the government is pursuing plans to establish new semiconductor clusters to address the capacity shortage driven by the AI boom [8]. South Korea's 'Physical AI Alliance' is transitioning from a policy-making body to an operational platform, deepening its cooperation with NVIDIA [2].
In Europe, a sense of crisis regarding AI infrastructure self-reliance is also growing. The EU currently possesses only about 5% of the world's AI computing capacity, while the US holds approximately 75% [3]. McKinsey forecasts that Europe's data center demand will more than triple from 10 GW in 2024 to 35 GW in 2030 [3], which, coupled with the political will to move away from reliance on US AI, is fueling discussions for building independent AI infrastructure [14]. Meanwhile, Japan is pursuing an independent path by establishing AI cooperation dialogue frameworks with countries like France and India, aiming to reduce excessive dependence on both US and Chinese technologies [11].
Tensions are also escalating on the export control front. The White House has ordered Anthropic to cease all overseas access to its cutting-edge AI models [1], a case that is drawing attention as it demonstrates that even allied nations can be excluded from US AI technology access. The Dutch Minister of Trade expressed opposition to the MATCH Act, which would block Chinese semiconductor companies' access to Western equipment, during a visit to the US Congress [16], suggesting that allied nations are beginning to create fissures in unilateral US technology controls.
3. Key Actors and Their Positions/Interests
United Statesis pursuing the establishment of a compute coalition utilizing an alliance network to maintain AI hegemony, while simultaneously strengthening export controls to block technology leakage to China. The US's core interest lies in setting global standards for AI computing infrastructure centered around itself and making allied AI ecosystems dependent on the US technology stack. However, this process creates a paradoxical tension of restricting technology access for its allies [1].
NVIDIAis the de facto standard setter in AI computing infrastructure and is the most direct beneficiary of the AI infrastructure boom among allied nations. NVIDIA is expanding its 'AI Factory' ecosystem through partnerships with allies, including South Korea [13], aiming to strengthen its platform dominance across the entire AI infrastructure, beyond mere chip sales.
South Koreaoccupies an irreplaceable position in the core AI hardware supply chain, including HBM, and is receiving strong requests for cooperation from the US [5][13]. However, it faces the dilemma of its companies facing restrictions in accessing the Chinese market due to strengthened US export controls [1]. The South Korean government seeks to enhance its strategic standing in the global AI supply chain through large-scale semiconductor investments and AI infrastructure development [8][15].
European Unionis navigating a complex balance between deepening dependence on US AI technology and regulatory sovereignty, as exemplified by the EU AI Act. Europe is concerned about becoming subservient to American values through reliance on US AI [14], and voices of opposition to unilateral US technology controls are growing, as seen with the Netherlands, which possesses ASML [16]. Europe is pursuing the development of independent AI infrastructure but faces practical barriers of cost and technological gaps [3].
Japanis pursuing strategic autonomy that does not excessively rely on either the US or China by participating in the US-led compute alliance while simultaneously engaging in multilateral cooperation with countries like France and India [11]. This aligns with the trend of Global South countries being concerned about becoming 'digital colonies' of AI superpowers [11].
Global South Countriesare seeking a 'non-aligned' path in the US-China AI hegemony competition, aiming not to be subservient to either side [9][10]. Southeast Asian countries are increasing their strategic bargaining power by emerging as new hubs in the AI server supply chain [12], but they are simultaneously facing pressure to take sides from both the US and China.
4. Summary of Key Issues
First, the issue of geopolitical fragmentation of AI computing infrastructureis critical. If the liberal bloc's compute alliance materializes, AI infrastructure is likely to be physically and technologically divided into a US-led bloc and a China-led bloc. This could lead to the fragmentation of the entire AI ecosystem, including AI model training data, algorithm standards, and cloud service access.
Second, the paradox of restricted technology access for alliesis evident. While the US seeks to unite allies in a compute coalition, it paradoxically restricts their access to US AI technology through strengthened export controls [1]. This can undermine allied trust and have the counterproductive effect of promoting the development of independent AI capabilities.
Third, the conflict between data sovereignty and AI regulatory standardsis intensifying. The clash between Europe's regulatory approach, exemplified by the EU AI Act, and the US's innovation-first approach is fueling conflict within the liberal bloc over AI governance standards. Which country's regulatory standards become the de facto global standard for the AI industry is a matter directly linked to technological sovereignty.
Fourth, the issue of power and physical infrastructure bottlenecksis significant. The surge in AI data center demand is making power infrastructure a new supply chain constraint [4], which is becoming a key factor determining the geographical distribution of AI computing power. The imbalance between AI infrastructure expansion and power supply is particularly acute in the Asian region [4].
Fifth, the pressure on strategic choices for South Korea, Taiwan, and Japanis notable. These countries, controlling critical links in the AI hardware supply chain, face intense pressure to align with the US [14]. However, completely severing economic ties with China is practically impossible. Therefore, they are required to engage in delicate balancing diplomacy to maintain strategic autonomy while integrating into the Western alliance system [9][10].
Phase 2: In-depth Issue Analysis
AI Hegemony Competition and the Liberal Bloc's Compute Alliance Proposal: Reshaping the Technological and Industrial Landscape
In-depth Issue Analysis
1. Analysis of the Root Causes of the Issue
The fundamental cause of the AI hegemony competition lies in the paradigm shift recognizing artificial intelligence not merely as a domain of technological innovation, but as a 'General Purpose Technology' that determines national competitiveness, military power, and economic order. As with nuclear or space technology in the past, both the US and China share the strategic judgment that AI can provide an overwhelming and asymmetric advantage to the nation that pioneers it. This perception is the fundamental driver transforming technological competition into a zero-sum geopolitical conflict.
More specifically, the extreme concentration of AI computing infrastructure can be cited as a cause. Currently, the US accounts for approximately 75% of global AI computing capacity, while the EU holds a mere 5% [3]. When the computing infrastructure, the physical foundation of AI capabilities, is concentrated in a specific country, access to that infrastructure itself becomes a key variable defining power relations between nations. This is because control over each layer of the AI stack—cloud services, AI models, semiconductor chips—determines the boundary between technological dependence and autonomy.
The geographical concentration of the semiconductor supply chain also acts as a root cause. The core hardware value chain for AI infrastructure—High Bandwidth Memory (HBM), substrates, optical components, and advanced logic semiconductors—is effectively dominated by South Korea, Taiwan, and Japan [14]. This structure makes close supply chain cooperation with these allies indispensable for the US to maintain its AI hegemony. Simultaneously, given that these countries find it difficult to completely sever economic ties with China, the supply chain issue transforms from a simple economic problem into a complex geopolitical equation.
Concerns about data sovereignty and digital colonialism are also emerging as significant causes. In Europe, there is a growing sense of crisis that reliance on US AI technology could lead to the erosion of national values and cultural identity by AI models trained with American biases [14]. Japan is also pursuing multiple AI cooperation dialogue frameworks with countries like France and India to reduce excessive dependence on US and Chinese technologies [11], demonstrating that securing AI sovereignty is perceived not just as an economic interest but as a matter of national identity and autonomy.
2. Structural Context
Political Structure
At the political level, the AI hegemony competition is embedded within the larger framework of systemic competition between the liberal democratic bloc and the authoritarian bloc. The United States, defining the potential military applications of AI technology as a security threat, is employing a strategy of systematically blocking China's acquisition of advanced AI capabilities through export controls and alliances. The core of this strategy is not merely to exclude China but to preemptively secure technological standards and governance norms by integrating free-world nations into a US-led AI ecosystem.
However, this political framework harbors internal rifts among allies. This is because US export control measures are directly impacting allied companies. It was only five days after Anthropic received a White House order to completely halt foreign access to its most advanced AI models that SK Telecom and NVIDIA announced a partnership to build a gigawatt-class AI cloud in South Korea [1]. This serves as a symbolic example demonstrating that US AI security logic can conflict with the AI industry strategies of its allies. Similarly, the Netherlands strongly opposed the MATCH Act, which restricts ASML's lithography equipment exports, leading the Minister of Trade to make an unprecedented diplomatic trip to Washington to persuade Congress and the Department of Commerce [16]. Thus, the US-led technological alliance initiative contains political tensions at points where it clashes with the economic interests of allied nations.
Economic Structure
At the economic level, the concept of an AI compute alliance is creating immense demand for infrastructure investment and a competitive landscape surrounding it. McKinsey projects that Europe's data center demand will more than triple from 10 GW in 2024 to 35 GW in 2030 [3], and in Asia, the boom in AI data center construction is making power infrastructure a new supply chain constraint [4]. This massive investment demand is attracting global venture capital and private equity firms to East Asia, with AI startups and infrastructure companies in South Korea, Japan, and Taiwan emerging as new investment destinations [6].
From the perspective of supply chain economics, supply bottlenecks for critical components required for AI infrastructure construction are creating economic leverage. Bottlenecks are spreading beyond GPUs to encompass the entire supply chain, including memory, substrates, and optical components [14], increasing the bargaining power of South Korean, Taiwanese, and Japanese companies that dominate the supply of these parts. Samsung Electronics' plan for a 1,000 trillion KRW domestic investment [15] and the South Korean government's initiative to create new semiconductor clusters [8] can be interpreted as attempts to capture this economic opportunity at the national strategic level. Furthermore, the acceleration of cloud service providers' development of their own AI chips (ASICs) is reshaping the cooperative structure of the entire semiconductor supply chain [7].
Security Structure
At the security level, the AI compute alliance is being formed under the recognition that control over technology equates to security capability. As the military applications of AI—autonomous weapons, cyber warfare, and information warfare—become a reality, access to AI computing infrastructure is being incorporated as a core agenda item for security cooperation in a manner similar to traditional military alliances. The US concept of a 'Compute Alliance,' aiming to jointly build AI infrastructure with allies, can be seen as an attempt to redefine the technology supply chain as an extension of security alliances.
Data sovereignty is another key pillar of the security structure. The question of where the data used to train AI models and the models themselves are stored, and which companies control them, is directly linked to security issues such as the protection of state secrets and citizens' personal information. The strengthening of regulatory frameworks, such as the EU AI Act, is an institutional expression of this desire to secure data sovereignty, forming a structure that legally supports the geopolitical alignment of the AI technology supply chain.
3. Comparison with Historical Precedents and Similar Cases
Cold War Technology Control Regime (COCOM)
The most direct historical precedent comparable to the current AI compute alliance initiative is the Coordinating Committee for Multilateral Export Controls (COCOM) established by the Western bloc during the Cold War. Founded in 1949, COCOM was a multilateral system under US leadership where Western allies jointly controlled the export of strategic materials and technologies to the Soviet Union and Eastern Bloc countries. While the controlled items at that time were military equipment and dual-use technologies, today AI chips and computing infrastructure have taken their place. The US's restriction on the export of NVIDIA A100/H100 chips to China and its demand for allied participation can be seen as a modern rendition of COCOM.
However, crucial differences also exist. During the COCOM era, the Soviet Union was not deeply integrated into the Western economy. In contrast, China today is a key participant in the global supply chain and has formed extensive economic interdependence with allied nations. For this reason, as seen in the case of ASML in the Netherlands [16], allied nations are required to strike a much more complex balance between security logic and economic interests.
Internet Governance Fragmentation (Splinternet)
Another similar case is the fragmentation of internet governance, the so-called 'Splinternet' phenomenon. China's Great Firewall and Russia's Runet have demonstrated that a single global internet can be divided along geopolitical lines. The AI compute alliance initiative can be understood as a process where this fragmentation is further deepened at the infrastructure layer. This is because it is not merely content or platforms, but the very physical computing infrastructure that trains and operates AI models, that is being separated by bloc.
Semiconductor Supply Chain Realignment (US-Japan Semiconductor Agreement)
The US-Japan Semiconductor Agreement (1986, 1991) of the 1980s also serves as an important historical reference point. At that time, the US, feeling threatened by the rapid growth of the Japanese semiconductor industry, signed an agreement that enforced market access and price regulations. This agreement led to the decline of the Japanese semiconductor industry and served as an opportunity for supply chain realignment, with South Korea and Taiwan filling the void. Today, the US's export controls on semiconductors to China are having a similar supply chain realignment effect, with South Korea, Taiwan, and Japan emerging as beneficiaries [6][14]. However, unlike in the past, there is a structural difference in that the US is now pursuing a strategy of integration rather than exclusion of these countries.
Energy Security and the IEA Framework
The strategic importance of AI computing infrastructure can also be compared to the energy security framework established after the oil crisis of the 1970s. Following the oil shock, Western countries established the International Energy Agency (IEA) and pursued joint management of strategic oil reserves and diversification of energy supply chains. Today, AI computing infrastructure corresponds to 'digital energy,' and the 'Compute Alliance' concept, which jointly secures and manages it, can be seen as a digital version of the IEA framework. The fact that the boom in AI data center construction in Asia is making power infrastructure a new supply chain constraint [4] demonstrates that AI computing and energy security are indeed converging.
4. Key Variables in Issue Development
First, the scope of US export controls and their application to allied nations. If the US strictly applies AI technology export controls to its allies, internal divisions within the alliance may deepen. The case of Anthropic blocking foreign access [1] and the US-Netherlands conflict over the MATCH Act targeting ASML [16] illustrate the practical risks of this variable. The broader the scope of export controls, the greater the incentive for allied nations to defect, potentially weakening the cohesion of the compute alliance.
Second, the speed of China's indigenous AI capability development. The speed at which China achieves success in developing its own AI semiconductors, such as Huawei's Ascend chips, is a key variable determining the effectiveness of US-led export controls. If China succeeds in building competitive AI infrastructure without Western technology, the strategic logic of export controls will weaken, and the incentive for allied nations to cooperate may diminish.
Third, the choice of bloc by Global South countries. Japan's efforts to build AI cooperation frameworks with Global South countries [11] reflect the recognition that which bloc's AI infrastructure these nations adopt could determine the trajectory of medium- to long-term technological hegemony competition. If the Global South leans towards adopting China's AI infrastructure exports, the geographical influence of the free world's compute alliance will inevitably be limited.
Fourth, the constraints of electricity and physical resources required for AI infrastructure construction. The explosive increase in demand for AI data centers is creating power infrastructure as a new bottleneck [4], and how this constraint is resolved will determine the feasibility of the compute alliance. In particular, for European and Asian countries pursuing both renewable energy transition and AI infrastructure expansion simultaneously, the issue of power supply can lead to conflicting policy priorities.
Fifth, the convergence or divergence of AI regulatory frameworks. If the regulatory environment, exemplified by the EU AI Act, converges into common standards within the free world, the institutional foundation of the compute alliance will be strengthened. However, if the differences in regulatory philosophy between the US and the EU persist, the friction costs of technological cooperation within the alliance may increase. In particular, regulatory divergence concerning data sovereignty and AI model transparency requirements could lead to further fragmentation of the AI supply chain.
Sixth, the strategic positioning of South Korea, Taiwan, and Japan. The extent to which these countries, which dominate the core hardware supply chain for AI, integrate into the US-led compute alliance, or choose to maintain strategic autonomy, is a variable that determines the alliance's actual capabilities. Japan's pursuit of multilateral cooperation [11] to reduce excessive dependence on US and Chinese technology is interpreted as a signal that these countries are acting as proactive agents, not mere suppliers, seeking to assert their own interests.
Phase 5: Final Recommended Response Measures
AI Hegemony Competition and the Free World's AI Compute Alliance Initiative: Reshaping the Technological and Industrial Landscape
Final Recommended Response Measures
1. Overall Assessment and Recommended Response Measures
The current AI hegemony competition has evolved beyond mere technological competition into a complex geopolitical conflict intersecting global supply chains, security alliances, and data sovereignty. US allies, including South Korea, find themselves in a dual position within this dynamic: strategic suppliers on one hand, and targets of alignment pressure on the other. The case where the White House ordered Anthropic to cease all foreign access to its AI models just five days after SK Telecom and NVIDIA announced their gigawatt-class AI cloud partnership [1] symbolically illustrates that even allied companies are not immune to US technology control policies. In this structure where cooperation and control operate simultaneously, what is required of US allies is not a simple choice of alignment but the acquisition of precisely designed strategic autonomy.
Based on this overall assessment, the core response directions recommended for US allies—particularly South Korea—consist of three pillars. First, Strategic Utilization of a Key Position in the Supply Chainis crucial. The fact that South Korea, Taiwan, and Japan hold a virtually monopolistic position in the AI core hardware value chain, including HBM [14], provides a structural basis for these countries to participate not merely as affiliates of the US-led compute alliance but as partners with bargaining power. Samsung Electronics' plan for a 1,000 trillion KRW domestic investment [15] and the establishment of new semiconductor clusters [8] should be pursued in a direction that further solidifies this position, thereby developing the capability to proactively set the terms and scope of technological cooperation.
Second, Building a Multi-layered AI Cooperation Networkis essential. Japan's strategy of establishing multiple AI cooperation dialogue channels with countries like France and India [11] to reduce excessive dependence on US and Chinese technology serves as a noteworthy precedent. South Korea, while participating in the US-led compute alliance, should also maintain independent AI cooperation channels with the EU, Japan, and Global South countries to diversify its reliance on any single bloc. This serves to hedge geopolitical risks and also contributes to securing a voice in the future formation of AI governance norms.
Third, Deepening Domestic AI Technology Self-Reliance Capabilitiesis vital. As the Anthropic case demonstrated, reliance on foreign AI models harbors a vulnerability that can be severed at any time by external policy changes [1]. Therefore, it is indispensable in the medium to long term to strengthen research capabilities in bottleneck AI technologies—such as computational compression, liquid cooling, and on-device AI—centered around science and engineering universities like KAIST and UNIST [5], and to foster an ecosystem of AI semiconductor startups like Rebellions [6] to secure the ability to build an indigenous AI stack.
2. Short-Term/Mid-Term/Long-Term Action Plans
Short-Term Action Plan (0-12 months): Risk Defense and Positioning Establishment
In the short term, the most urgent tasks are to manage the immediate risks arising from changes in US AI export control policies and to secure a favorable initial position within the compute alliance initiative. As the case of Anthropic's suspension of foreign AI model access illustrates [1], US AI control policies can be applied unexpectedly to companies in allied nations. Therefore, domestic companies must immediately assess their dependency on US AI models and cloud services and establish emergency plans to secure alternative technological options in advance.
Concurrently, diplomatic efforts are needed to elevate the broad cooperation agreements, such as those for AI factories and physical AI, materialized during NVIDIA CEO Jensen Huang's visit to South Korea [13], from mere supply contracts to strategic partnerships. Specifically, the content of cooperation should be substantivized by including provisions for technology transfer, joint research and development, and exceptions to export controls. Furthermore, based on the experience of transforming the Physical AI Alliance into an operating platform [2], an AI infrastructure cooperation governance system linking government, corporations, and research institutions should be established early on.
The case of the EU's ASML activating independent diplomatic channels against the US MATCH Act [16] suggests that allied companies must also proactively respond politically to protect their national interests. The South Korean government and companies should also strengthen their policy lobbying capabilities targeting the US Congress and administration, and establish channels to continuously raise concerns about the negative impact of export control policies on allied companies.
Mid-Term Action Plan (1-3 years): Expanding Strategic Autonomy and Building Ecosystems
In the medium term, efforts should focus on substantially expanding strategic autonomy based on the position secured in the short term. The most critical task is the domestic expansion of AI computing infrastructure. While the large-scale investment plans of Samsung Electronics [15] and the establishment of new semiconductor clusters [8] should be pursued without delay, they should evolve beyond mere production capacity expansion into integrated AI infrastructure hubs incorporating the concept of AI factories. In this process, to preemptively address the power infrastructure constraints arising from the Asian AI data center boom [4], a power supply system based on renewable energy should be concurrently established.
In terms of supply chain diversification, a strategy for South Korean companies to secure production bases in Thailand, Malaysia, and Vietnam, leveraging the trend of expanding AI server supply chains in Southeast Asia [12], is effective. This serves the dual purpose of diversifying supply chain risks concentrated in specific regions amidst escalating US-China tensions and expanding cooperation networks with Global South countries. Japan's strategy of building cooperation frameworks with Global South countries, acknowledging concerns about 'digital colonization' [11], is a model applicable to South Korea as well.
Fostering the AI startup ecosystem is also a key pillar of the mid-term action plan. To actively leverage the trend of global VCs and private equity firms such as Andreessen Horowitz, New Mountain, and PGIM concentrating investments in AI companies in Korea, Japan, and Taiwan [6], government-level deregulation, tax incentives, and linked public procurement support should be strengthened to enable AI semiconductor startups like Rebellions to achieve global competitiveness. In particular, industry-academia linkage platforms must be reorganized to facilitate the industrialization of AI bottleneck-breaking technologies such as computational compression and liquid cooling pursued by institutions like KAIST and UNIST [5].
Long-term Action Plan (3-5+ years): Establishing AI Sovereignty and Participating in Global Norm Formation
In the long term, the goal should be to substantially establish AI technological sovereignty and play an active role in the formation of global AI governance norms. To this end, the capacity to develop proprietary AI models must be fostered at the national strategic level. Just as Europe is pursuing independent AI development out of concern over dependence on AI models trained with American values [14], Korea must secure data sovereignty by developing large language models and AI systems optimized for the Korean language and culture. While deepening cooperation with Nvidia in the Physical AI Alliance, as Naver is doing [2], is effective in the short term, it is essential to concurrently cultivate the capacity to build an independent AI stack in the long run.
In terms of global AI governance, efforts are needed to actively participate in the formation process of major regulatory frameworks such as the EU AI Act [3] to reflect Korea's interests. Diplomatic capabilities should be concentrated to position Korea not as a norm-taker but as a norm-creator, particularly in areas such as interoperability standards for AI computing infrastructure, data sovereignty protection norms, and multilateral cooperation frameworks for AI export controls. To this end, a multi-layered diplomatic strategy is required, involving institutionalizing a trilateral AI cooperation framework with Japan and Taiwan, and expanding solidarity with the EU, India, and Global South countries based on this foundation.
3. Monitoring Indicators and Trigger Points
For effective response, it is crucial to establish key indicators for continuously tracking the unfolding landscape of the AI hegemony competition and to pre-define critical points that necessitate strategic adjustments.
Supply Chain and Technology IndicatorsThe most critical monitoring target is whether the United States imposes additional export control measures on HBM and advanced semiconductors. If the US strengthens regulations on Chinese semiconductor exports by its allied companies beyond the current level, this will serve as a trigger that directly impacts the revenue structure of Korean semiconductor companies. Furthermore, changes in Nvidia GPU allocation, the degree of bottleneck intensification in AI data center power infrastructure [4], and supply constraints for AI infrastructure components such as optical interconnects [18] should also be continuously tracked.
Geopolitical IndicatorsIn terms of geopolitical indicators, the speed at which the US expands its AI export controls on China and whether these controls are applied to allies are key variables. If restrictions on AI model access for allied nations are repeated or expanded, as in the case of Anthropic [1], this should act as a trigger to renegotiate the terms of participation in US-led compute alliances. How the semiconductor policy conflict between the US and Europe over ASML is resolved [16] also serves as an important leading indicator. If Europe successfully resists unilateral US export control policies, it sets a favorable precedent for Korea to adopt a similar negotiation strategy.
Market and Investment IndicatorsIn terms of market and investment indicators, the flow of global VC investments into East Asian AI startups [6] and the speed of the AI server supply chain's relocation to Southeast Asia [12] should be regularly assessed. If investment flows show a pattern of concentration in specific countries or technological domains, this should be interpreted as a leading signal indicating the direction of global AI industry landscape restructuring. The projection that European data center demand will triple by 2030 [3] is an important market indicator that can be utilized in formulating an AI infrastructure export strategy targeting the European market.
Key Trigger PointsThree scenarios should be established as key trigger points. First, if the US issues an executive order further restricting AI technology access for companies from allied nations, immediate diplomatic channels should be activated, and investment in building proprietary AI stacks should be accelerated. Second, if China retaliates by restricting the export of rare earths or materials to Korean semiconductor companies, the supply chain diversification plan should be switched to emergency mode. Third, if major regulatory frameworks such as the EU AI Act begin to pose substantial barriers to European market access for Korean companies, a dedicated regulatory response team should be formed, and efforts to conclude a technology cooperation agreement with the EU should be pursued.
4. Summary Conclusion
The AI hegemony competition has already moved beyond the stage of technological competition and is solidifying into a complex geopolitical structure where supply chains, security, and data sovereignty intersect. Among the US allies, South Korea, in particular, is a strategic partner possessing irreplaceable supply chain status [14] within this structure, while simultaneously being a vulnerable beneficiary within the direct influence of technology control policies [1]. This dual position presents both a crisis and an opportunity.
The recommended core strategy is neither unconditional integration into the US-led compute alliance nor maintaining strategic ambiguity and observing passively. Instead, it involves simultaneously pursuing a three-pronged strategy: leveraging its core supply chain status as negotiation leverage, building a multi-layered AI cooperation network, and deepening its capacity for independent AI technology self-reliance. Samsung Electronics' large-scale investment [15], the creation of new semiconductor clusters [8], the operationalization of the Physical AI Alliance as a platform [2], and the research on AI bottleneck technologies by science and engineering universities like KAIST [5] are all components of this strategy. By pursuing these cohesively within the framework of a consistent national AI strategy, Korea can position itself not as a passive subject but as an active shaper of the AI hegemony competition.
References
[2] [DigiTimes Asia] South Korea takes physical AI push from policy to practice
[3] [DigiTimes Asia] Europe's AI infrastructure: the cost gap that policy cannot paper over
[4] [DigiTimes Asia] Asia's AI data center boom turns green power into supply chain stress test
[7] [DigiTimes Asia] MediaTek-Global Unichip tie-up talk puts TSMC's AI ASIC ecosystem on watch
[8] [Nikkei Asia] South Korea plans new chip cluster as AI boom strains capacity
[9] [Nikkei Asia] The AI cold war needs a nonaligned movement
[10] [Nikkei Asia] The AI cold war needs a nonalignment movement
[11] [Nikkei Asia] Japan seeks AI alliances with France, India to curb US-China dominance
[12] [DigiTimes Asia] AI server supply chain expansion accelerates across Southeast Asia
[14] [Wired] Europe Is Fed Up and Wants Its Own AI
[15] [Daily Sabah] Samsung eyes record $650B bet on South Korea’s AI chip sector
[16] [TechCrunch] Europe is pushing back on Washington’s chip war
*This text is an AI translation of an original written in Korean. Some translations or nuances may be inaccurate.