Azzam Bilal Chamdy
The relentless surge in artificial intelligence (AI) development is encountering a formidable physical constraint: the global electricity grid. As technology giants push the boundaries of AI model complexity and deploy increasingly massive computing infrastructures, the digital revolution is precipitating an unprecedented demand for physical energy. At the epicenter of this mounting challenge lies East Asia, the undisputed industrial powerhouse driving the global hardware supply chain.
Mainland China boasts the world’s second-largest data center market and stands as the preeminent global hub for electronics manufacturing, responsible for approximately 36% of all electronics produced worldwide. Taiwan, meanwhile, dominates the production of the most advanced semiconductors, the critical components powering AI, and is also the leading manufacturing base for AI servers. Complementing this ecosystem, South Korea spearheads the memory-chip industry, with giants like Samsung Electronics and SK hynix holding commanding positions in DRAM and NAND flash memory. Collectively, these three East Asian economies occupy strategically vital roles across the data center, semiconductor, server manufacturing, and memory chip sectors, all of which form the bedrock of modern AI capabilities.
However, this accelerating computing boom comes with a significant environmental toll. In 2024, data centers globally consumed an estimated 415 terawatt-hours (TWh) of electricity, representing roughly 1.5% of total global electricity consumption. According to the International Energy Agency (IEA), this electricity usage has been escalating at an annual rate of approximately 12% over the preceding five years. The environmental organization Greenpeace East Asia projects an even more dramatic surge, estimating that global electricity demand for AI chipmaking could increase by a staggering 170-fold between 2023 and 2030. Given that the production of logic and memory chips essential for AI hardware is heavily concentrated in East Asia, a substantial portion of this increased manufacturing burden is poised to fall upon Taiwan, South Korea, and Japan.
Recognizing the urgency to address this escalating challenge and chart a more sustainable trajectory, Greenpeace East Asia convened a global webinar on August 6th. The event 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 discourse from debating whether AI must be decarbonized to actively exploring how a clean and resilient AI supply chain can be effectively constructed.
"We aim to build shared momentum for a clearer and more sustainable AI and technology industry," stated Dr. Junyan Liu, deputy program director at Greenpeace East Asia, in her opening remarks. "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."
Scaling Clean Technology: Lessons from China’s Industrial Policy
Addressing the burgeoning AI power gap necessitates a deep understanding of how clean technologies can be effectively scaled at an industrial level. China’s remarkable ascent in solar energy, electric vehicles (EVs), battery production, and grid infrastructure offers invaluable insights for the rapid deployment of clean technologies in the face of surging demand.
Dr. Kyle Chan, a Fellow at the Brookings Institution’s John L. Thornton China Center, elaborated on China’s strategy of building end-to-end dominance across its clean technology sectors. This was achieved by integrating raw material sourcing, component manufacturing, and finished product assembly. Key to this success was the absorption of foreign technology, rapid adaptation, and the co-development of robust local supply chains. Proactive local governments played a crucial role in accelerating this growth by providing essential infrastructure, land, and policy support.
"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."
Instead of concentrating on a single technological winner, China strategically supported a diverse array of battery chemistries and clean technologies concurrently. This multi-pronged approach enabled manufacturers to cater to various market segments while leveraging economies of scale and supply chain flexibility to drive down costs. Furthermore, China’s established heavy industries provided significant synergies with its nascent clean energy sectors. For instance, its shipbuilding expertise has been instrumental in constructing offshore-wind installation vessels.
China is now applying similar strategic principles to the development of its data center infrastructure. Through the "East-West Computing Resources Transmission Project" (EWCRT Project), national policies are actively encouraging companies to relocate energy-intensive and less latency-sensitive computing workloads to the resource-rich western provinces. These regions offer abundant land and significant wind and solar energy potential. The processed data and resulting services can then be efficiently delivered to users in coastal cities via a sophisticated national computing network. This initiative, supported by research published in Nature, highlights a forward-thinking approach to balancing digital infrastructure growth with resource availability and renewable energy potential.
As Chinese cleantech companies increasingly expand their global footprint, this integrated, multi-faceted approach could provide critical lessons for powering the AI era more sustainably worldwide, Dr. Chan concluded.
The Economics of AI Power: Why Renewables Will Prevail 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, according to Jongkyu Kim, founder and chief executive officer of 60Hz and chair of the Korea Climate Tech Association.
South Korea has recently unveiled ambitious mega-projects with a combined investment of approximately 1,500 trillion won, equivalent to roughly US$1 trillion. This substantial package includes the construction of four new semiconductor fabrication plants by Samsung Electronics and SK hynix, regional robotics initiatives, and a target to establish 18.4 gigawatts (GW) of AI data center capacity by 2035. This projected capacity would represent approximately 18-19% of South Korea’s recent peak electricity demand.
"AI has become an electricity story," Kim stated. "As Sam Altman famously noted last year, ‘The cost of intelligence should eventually converge to near the cost of electricity.’ If this holds true, then AI competition will inevitably transform into a race for the cheapest electricity, and future-proof, cost-effective sources will emerge as the clear winners."
Kim presented a compelling economic argument, asserting that renewable energy sources offer the most advantageous proposition when compared to fossil gas or nuclear power for meeting this burgeoning demand. His analysis, supported by Lazard’s 2026 LCOE+ Report, indicates that unsubsidized renewable energy remains the most cost-competitive form of new electricity generation on a levelized cost of energy (LCOE) basis, measured in dollars per megawatt-hour. This economic advantage is particularly pronounced for new-build generation projects.
"AI is not a burden on the energy transition; it is a catalyst," Kim emphasized. "Korea has strategically anchored its AI build-out to renewables through deliberate choices in location, legislation, and policy. Industry leaders are actively signing onto the RE100 initiative, and the underlying economics reinforce this direction. If the cost of AI is intrinsically linked to the cost of power, then zero-marginal-cost renewables are poised to dominate."
Overcoming Bottlenecks in Taiwan’s Chip Industry
As a leading global producer of advanced semiconductors and AI servers, Taiwan serves as a critical engine for the world’s computing power. Allissa Tai, 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 reliable renewable electricity.
Taiwan’s Ministry of Economic Affairs forecasts an average annual electricity demand growth of 2.5% from 2026 to 2035, a projection significantly influenced by the expansion of semiconductor fabrication plants, the proliferation of AI data centers, and the increased energy required for cooling these facilities. CIER estimates that AI and semiconductor-related projects alone could necessitate an additional 4.32 GW of power capacity by 2030.
To meet this projected increase, Taiwan’s Ministry of Economic Affairs plans to augment its power generation capacity by adding approximately 26 GW of new natural-gas-fired power plants by 2035. However, this strategy carries inherent risks. In 2024, Taiwan imported over 94% of its energy, making it highly susceptible to international price volatility, potential shipping disruptions, and broader geopolitical uncertainties associated with an increased reliance on imported fossil fuels.
While major global technology corporations such as Google and Apple are actively pursuing 100% renewable electricity for their operations and supply chains, the corporate procurement of renewable energy by RE100 members currently accounts for only about 5% of Taiwan’s total renewable generation, according to data from CIER and The Climate Group’s 2024-2025 Taiwan Renewable Electricity Market Briefing. Several key structural obstacles impede a faster transition. These include limitations in the availability of suitable land for renewable energy installations, insufficient transmission infrastructure to connect remote renewable energy sources to demand centers, and regulatory hurdles that complicate long-term power purchase agreements for corporate buyers.
"To power the AI boom cleanly, we need energy infrastructure built at scale," Tai asserted. "That requires policy stability, social consensus, and cross-party alignment. Transitioning to renewables is not just about climate action; it is the bedrock of Taiwan’s economic security and its global competitiveness."
An Action Plan for a Clean AI Ecosystem
To effectively align the rapid growth of artificial intelligence with pressing climate goals, the webinar’s distinguished panelists collaboratively outlined three critical and targeted reforms:
- Accelerate Renewable Energy Deployment and Grid Modernization: This involves streamlining permitting processes for renewable energy projects, investing in grid infrastructure upgrades to enhance flexibility and reliability, and implementing policies that facilitate direct corporate procurement of renewable electricity. This could include mechanisms like virtual power purchase agreements (VPPAs) and green tariffs.
- Incentivize Energy Efficiency and Demand-Side Management: Promoting energy-efficient data center design, optimizing cooling systems, and encouraging the adoption of smart grid technologies can significantly reduce overall electricity consumption. Governments and industry can collaborate on standards and incentives for energy-efficient hardware and operational practices.
- Foster International Collaboration and Supply Chain Transparency: Establishing clear reporting standards for the environmental impact of AI development, from chip manufacturing to data center operations, is crucial. International cooperation can help share best practices, develop innovative clean energy solutions, and ensure greater transparency throughout the AI supply chain. This includes promoting the use of recycled materials and designing for circularity in hardware production.
The collective call to action from the webinar underscored that the path forward for AI development must be intrinsically linked to a robust and sustainable energy future. By embracing renewable energy, optimizing energy consumption, and fostering collaborative solutions, East Asia and the global community can navigate the energy demands of the AI revolution while safeguarding the planet. The urgency of the situation, highlighted by escalating energy needs and climate targets, necessitates immediate and concerted action from policymakers, industry leaders, and technology developers alike.
Lina Irawan
Raul Delapena Setiawan
