Iffa Jayyana
The relentless acceleration of artificial intelligence (AI) is encountering a formidable physical barrier: the global electricity grid. As technology giants forge ever more sophisticated AI models and deploy vast, power-hungry computing infrastructures, the digital revolution is imposing an unprecedented strain on physical energy resources. At the nexus of this escalating challenge sits East Asia, the indispensable industrial heartland of the global hardware supply chain.
Mainland China boasts the world’s second-largest data center market and stands as the foremost global hub for electronics manufacturing, responsible for approximately 36% of worldwide electronics output. Taiwan, a tiny island nation with immense geopolitical and technological significance, dominates the production of the most advanced semiconductors, the foundational building blocks of modern AI. Furthermore, Taiwan serves as the leading manufacturing base for AI servers, the specialized hardware that powers these complex models. Meanwhile, South Korea reigns supreme in the memory chip industry, with domestic giants Samsung Electronics and SK Hynix holding commanding positions in DRAM and NAND flash memory. Together, these three East Asian economies occupy critical, interconnected roles across the data center, semiconductor, server manufacturing, and memory chip sectors that collectively underpin the entire modern AI ecosystem.
However, this booming digital economy carries a significant environmental cost. In 2024, data centers worldwide consumed an estimated 415 terawatt-hours (TWh) of electricity, a figure representing roughly 1.5% of total global electricity consumption. According to the International Energy Agency (IEA), this demand has been growing at an accelerated pace, increasing by approximately 12% annually over the preceding five years. The implications for the future are stark: Greenpeace East Asia estimates that global electricity demand specifically for AI chipmaking could surge by an astonishing 170-fold between 2023 and 2030. Given that the production of the logic and memory chips essential for AI hardware is heavily concentrated in East Asia, a substantial portion of this exponential increase in manufacturing burden will fall upon Taiwan, South Korea, and Japan.
Recognizing the urgent need to address this escalating challenge and chart a more sustainable path forward, Greenpeace East Asia convened a global webinar on August 6th. The virtual forum brought together leading experts in energy policy and climate technology from the United States, Taiwan, and South Korea. The primary objective was to pivot the prevailing discourse from merely acknowledging the necessity of decarbonizing AI to actively exploring actionable strategies for building a clean, resilient, and sustainable AI supply chain.
Dr. Junyan Liu, Deputy Program Director at Greenpeace East Asia, articulated the organization’s vision in her opening remarks. "We would love to build shared momentum for a clearer and more sustainable AI and technology industry," she stated. "We strongly believe that by partnering directly with industry leaders, we can transform complex environmental hurdles into viable, high-impact business models for the long haul." This sentiment underscored a commitment to collaborative solutions, emphasizing that environmental sustainability and economic prosperity in the technology sector are not mutually exclusive but rather intrinsically linked.
Scaling Clean Technology: Lessons from China’s Industrial Policy
Bridging the widening gap between AI’s burgeoning energy requirements and the capacity of existing power grids necessitates a deep understanding of how clean technologies can be scaled effectively at an industrial level. China’s remarkable ascent in sectors such as solar energy, electric vehicles (EVs), battery manufacturing, and grid infrastructure offers a compelling case study and valuable lessons for the rapid deployment of clean technologies amidst surging demand.
Dr. Kyle Chan, a Fellow at the Brookings Institution’s John L. Thornton China Center, highlighted China’s strategic approach to building end-to-end dominance across various industrial sectors. This strategy involved a multi-pronged effort: absorbing foreign technology, adapting it with remarkable speed, and co-developing robust local supply chains. Crucially, proactive engagement from local governments played a pivotal role by providing essential infrastructure, land access, and supportive policy frameworks, thereby accelerating the transition.
"China’s cleantech policy wasn’t a single linear path toward becoming a powerhouse," Dr. Chan explained. "It involved constant pivots, strategic shifts, and adaptation along the way. China made a broad bet across multiple technologies, and it paid off." This approach eschewed a singular focus on one technology, instead supporting a diverse portfolio of battery chemistries and clean energy solutions simultaneously. This diversification allowed Chinese manufacturers to cater to different market needs while leveraging economies of scale and supply chain flexibility to drive down costs. Furthermore, China’s established heavy industrial base created synergistic opportunities for its newer clean-energy sectors. For instance, its shipbuilding capabilities were leveraged to construct specialized vessels for offshore wind farm installation.
China is now extending these integrated principles to its burgeoning data center sector. The "East-West Computing Resources Transmission Project" (EWCRT Project) is a prime example of this strategy in action. This national initiative encourages companies to relocate energy-intensive and less latency-sensitive computing workloads to the country’s resource-rich western provinces. These regions are favored for their abundant land resources and significant wind and solar power potential. The processed data and services generated in these western hubs can then be efficiently delivered to users in the more densely populated coastal cities through the national computing network. This innovative approach optimizes resource utilization and energy sourcing, aligning with both economic and environmental objectives.
As Chinese cleantech companies increasingly expand their global footprint, Dr. Chan suggested that this integrated, multi-faceted approach could provide invaluable lessons for powering the AI era more sustainably worldwide.
The Economics of AI Power: Why Renewables Will Lead in South Korea
In South Korea, the escalating demand from AI infrastructure presents a significant opportunity to accelerate the nation’s transition to clean energy. Jongkyu Kim, founder and chief executive officer of 60Hz and chair of the Korea Climate Tech Association, emphasized this point, framing AI not as a burden but as a catalyst for green growth.
South Korea has recently unveiled ambitious mega-projects with a combined investment of approximately 1,500 trillion won (roughly US$1 trillion). This package includes the construction of four new semiconductor fabrication facilities by industry leaders Samsung Electronics and SK Hynix, alongside regional robotics initiatives. A key component of this initiative is a target to establish 18.4 gigawatts (GW) of AI data center capacity by 2035. This projected capacity alone would represent roughly 18-19% of South Korea’s recent peak electricity demand, underscoring the scale of the energy challenge.
"AI has become an electricity story," Kim stated, echoing sentiments from industry leaders. "Sam Altman said last year: ‘The cost of intelligence should eventually converge to near the cost of electricity.’ If true, AI competition becomes a race for the cheapest electricity, and future-proof sources will win." This perspective highlights a fundamental economic truth: as AI’s computational demands grow, the cost of energy will become a primary determinant of its affordability and widespread adoption.
Kim further argued that, from an economic standpoint, renewable energy sources offer the most compelling and cost-competitive option compared to fossil fuels or nuclear power. Data from Lazard’s 2026 Levelized Cost of Energy (LCOE)+ Report consistently shows that unsubsidized renewable energy, on a dollar-per-megawatt-hour basis, remains the most cost-effective form of new-build electricity generation. This economic advantage is expected to become even more pronounced as AI demand drives up overall electricity consumption.
"AI is not a burden on the energy transition; it is a catalyst," Kim asserted. "Korea has anchored its AI build-out to renewables by location, law, and policy. Industry leaders have signed on to RE100, and the underlying economics close the loop. If the cost of AI is the cost of power, zero-marginal-cost renewables will win." This optimistic outlook suggests that the economic imperatives of AI development could, in fact, accelerate the adoption of renewable energy, creating a virtuous cycle of technological advancement and environmental progress.
Overcoming Bottlenecks in Taiwan’s Chip Industry
As a pivotal global producer of advanced semiconductor chips and AI servers, Taiwan stands as a critical engine of the worldwide computing revolution. Allissa Tai, the RE100 representative in Taiwan at the Chung-Hua Institution for Economic Research (CIER), outlined the structural obstacles and emerging opportunities that manufacturers face in securing a reliable supply of renewable electricity.
Taiwan’s Ministry of Economic Affairs projects an annual electricity demand growth of approximately 2.5% from 2026 to 2035, a significant portion of which will be driven by the expansion of semiconductor fabrication plants, AI data centers, and the increased cooling requirements associated with these energy-intensive operations. CIER estimates that AI and semiconductor-related projects alone could necessitate an additional 4.32 GW of power capacity by 2030, a substantial figure for the island’s energy infrastructure.
In response to this projected surge, Taiwan’s Ministry of Economic Affairs plans to augment its power generation capacity by approximately 26 GW through new natural-gas-fired plants by 2035. However, this strategy carries inherent risks. Taiwan currently imports over 94% of its energy, making it highly vulnerable to international price volatility, potential shipping disruptions, and broader geopolitical instabilities. A greater reliance on imported fossil fuels would exacerbate these existing vulnerabilities, potentially impacting the island’s energy security and economic stability.
While major global technology corporations like Google and Apple are actively pursuing 100% renewable electricity for their operations and supply chains, their corporate procurement currently accounts for only about 5% of Taiwan’s total renewable energy generation, according to data from CIER and The Climate Group’s 2024-2025 Taiwan Renewable Electricity Market Briefing. This indicates a significant gap between corporate sustainability goals and the actual availability of renewable energy on the island.
Several key structural obstacles hinder a more rapid transition to renewables for Taiwan’s crucial industries. These include limitations in grid infrastructure that impede the integration of large-scale renewable energy projects, the absence of a sufficiently developed market for corporate power purchase agreements (PPAs), and challenges in the permitting and regulatory processes that can delay project development. Furthermore, the availability of land for renewable energy installations is a significant constraint on the island.
"To power the AI boom cleanly, we need energy infrastructure built at scale," Tai emphasized. "That requires policy stability, social consensus, and cross-party alignment. Transitioning to renewables is not just about climate; it is the bedrock of Taiwan’s economic security and global competitiveness." Her statement underscores the multifaceted importance of a robust renewable energy strategy, linking environmental stewardship directly to national resilience and economic prosperity.
An Action Plan for a Clean AI Ecosystem
To effectively align the rapid growth of the AI sector with global climate objectives, the webinar panelists collectively proposed three targeted reforms aimed at fostering a clean and sustainable AI ecosystem:
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Establishing Robust Renewable Energy Procurement Mechanisms: This involves developing more accessible and scalable pathways for corporations to secure renewable electricity, including expanding options for long-term Power Purchase Agreements (PPAs), facilitating direct investment in renewable energy projects, and simplifying regulatory frameworks to accelerate project development. This reform is critical for enabling companies, especially those in energy-intensive sectors like semiconductor manufacturing and data centers, to meet their sustainability targets and reduce their carbon footprint.
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Incentivizing Energy Efficiency and Demand-Side Management: Beyond increasing renewable energy supply, reducing overall energy consumption is paramount. This reform calls for implementing policies that incentivize energy-efficient data center design and operation, promoting the adoption of advanced cooling technologies, and encouraging AI workload optimization to minimize energy waste. Furthermore, exploring demand-side management strategies, where energy consumption can be shifted to periods of high renewable energy availability, will be crucial for grid stability.
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Fostering Cross-Sectoral Collaboration and Policy Alignment: Addressing the energy challenges posed by the AI boom requires coordinated efforts among governments, industry stakeholders, research institutions, and civil society. This reform emphasizes the need for clear, long-term policy signals that support renewable energy development, predictable regulatory environments that encourage investment, and platforms for knowledge sharing and best practice dissemination. Collaboration between policymakers and industry leaders is essential to ensure that technological advancements in AI are accompanied by corresponding progress in environmental sustainability.
The confluence of surging AI demand and the physical limitations of the global electricity grid presents a critical juncture. As East Asia continues to be the engine of AI hardware innovation and production, its ability to transition to clean energy will be a determining factor in the sustainability of the digital revolution. The insights shared during the Greenpeace East Asia webinar underscore the urgent need for strategic policy interventions, innovative technological solutions, and collaborative action to ensure that the AI boom powers a greener, more resilient future.
Ali Ikhwan
Layla Zulfa
