Rifan Muazin
The relentless ascent of artificial intelligence, a transformative force reshaping industries worldwide, is confronting an unexpected and formidable physical limitation: the global electricity grid. As technology giants forge ever more sophisticated AI models and deploy colossal computing infrastructures, the digital revolution is precipitating an unprecedented surge in energy consumption. At the epicenter of this critical challenge lies East Asia, the indispensable industrial powerhouse driving the global hardware supply chain. The region’s pivotal role in semiconductor fabrication, data center development, and electronics manufacturing places it at the nexus of both the AI boom and its burgeoning energy demands.
Mainland China, already boasting the world’s second-largest data center market, also stands as the foremost electronics-manufacturing hub, responsible for approximately 36% of global output. Taiwan, a linchpin in the global tech ecosystem, dominates the production of the most advanced semiconductors, including the cutting-edge processors essential for AI, and serves as the primary manufacturing base for AI servers. South Korea, a leader in the memory-chip industry, is home to giants like Samsung Electronics and SK Hynix, which command dominant positions in DRAM and NAND flash memory – crucial components for high-performance computing. Collectively, these three East Asian economies form the bedrock of the modern AI infrastructure, occupying critical positions across the data center, semiconductor, server manufacturing, and memory chip sectors.
However, this exponential growth in computing power carries a significant environmental toll. In 2024, global data centers are estimated to have consumed approximately 415 terawatt-hours (TWh) of electricity, accounting for roughly 1.5% of total global electricity consumption. According to the International Energy Agency (IEA), this demand has been escalating at an annual rate of approximately 12% over the preceding five years. The environmental impact is projected to intensify dramatically, with Greenpeace East Asia forecasting a staggering 170-fold increase in global electricity demand for AI chipmaking between 2023 and 2030. Given the concentration of logic and memory chip production for AI hardware in East Asia, the bulk of this immense additional manufacturing burden will likely fall upon Taiwan, South Korea, and Japan, intensifying their energy challenges.
Recognizing the urgent need to address this burgeoning energy demand and chart a cleaner course for the AI industry, Greenpeace East Asia convened a global webinar on August 6. 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 discourse from the necessity of decarbonizing AI to the practicalities of constructing a clean and resilient AI supply chain.
"We would love 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." The webinar served as a crucial platform for interdisciplinary dialogue, aiming to foster collaboration and innovation in the face of a shared global challenge.
Scaling Clean Tech: Lessons from China’s Industrial Policy
Addressing the escalating power demands of the AI revolution necessitates a deep understanding of how clean technologies can be effectively scaled at an industrial level. China’s remarkable ascent in the fields of solar energy, electric vehicles (EVs), battery manufacturing, and grid infrastructure offers invaluable insights and potential blueprints for rapidly deploying clean technologies amidst surging demand.
Dr. Kyle Chan, a Fellow at the Brookings Institution’s John L. Thornton China Center, highlighted China’s strategy of building end-to-end dominance across its clean technology sectors. This was achieved through a multifaceted approach that involved absorbing foreign technology, adapting it with remarkable speed, and strategically co-developing robust local supply chains. Crucially, proactive support from local governments, in the form of infrastructure development, land allocation, and tailored policy frameworks, significantly accelerated this industrial expansion.
"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 diversified approach, rather than relying on a single technological winner, allowed Chinese manufacturers to explore and support a wide array of battery chemistries and clean energy solutions simultaneously. This strategy not only enabled them to cater to diverse market needs but also leveraged economies of scale and supply chain flexibility to drive down costs. Furthermore, China’s established heavy industries created synergistic opportunities for its burgeoning clean energy sectors. For instance, its sophisticated shipbuilding capabilities have been instrumental in constructing the specialized vessels required for offshore wind farm installations.
The principles underpinning China’s cleantech success are now being applied 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 country’s resource-rich western provinces. These regions offer abundant land and substantial wind and solar resources, enabling the establishment of large-scale, renewable-powered data centers. The processed data and services generated in these western hubs can then be efficiently transmitted to users in the more densely populated coastal cities via national computing networks. This strategic redistribution aims to optimize energy utilization and leverage renewable energy potential across the vast country. As Chinese clean technology companies increasingly expand their global footprint, this integrated, adaptive, and multi-pronged approach could offer significant lessons for powering the AI era more sustainably on a worldwide scale.
The Economics of AI Power: Why Renewables Will Win in South Korea
In South Korea, the escalating demand for electricity driven by the expansion of 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 dynamic at the webinar.
South Korea has recently announced ambitious mega-projects with a combined investment exceeding approximately 1,500 trillion won (roughly US$1 trillion). This substantial package includes the development of four new semiconductor fabrication plants by industry leaders Samsung Electronics and SK Hynix, alongside regional robotics initiatives. A key component of these plans is a target to establish 18.4 gigawatts (GW) of AI data center capacity by 2035. This projected capacity is equivalent to approximately 18-19% of South Korea’s recent peak electricity demand, underscoring the magnitude of the energy challenge and the opportunity for clean energy solutions.
"AI has become an electricity story," Kim stated. "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 positions the pursuit of affordable, reliable, and sustainable energy as a core competitive advantage in the AI race.
Kim further argued that renewable energy sources present the most compelling economic case when compared to fossil fuels, particularly natural gas, and nuclear power. Data from Lazard’s 2026 Levelized Cost of Energy (LCOE+) report consistently shows that unsubsidized renewable energy, such as solar and wind, remains the most cost-competitive form of new-build electricity generation on a per-megawatt-hour basis. This economic advantage is expected to grow as renewable energy technologies mature and deployment scales up.
"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 statement underscores a paradigm shift where the exponential growth of AI is not viewed as an impediment to decarbonization but as a powerful driver for accelerating the adoption of clean energy technologies, particularly in economies like South Korea that are heavily invested in advanced manufacturing and technology. The integration of AI development with renewable energy targets is thus seen as a mutually beneficial strategy, fostering both technological advancement and environmental sustainability.
Overcoming Bottlenecks in Taiwan’s Chip Industry
As a preeminent global producer of advanced semiconductors and AI servers, Taiwan stands as a critical engine powering the world’s computing infrastructure. Allissa Tai, RE100 representative in Taiwan at the Chung-Hua Institution for Economic Research (CIER), detailed the structural obstacles and emerging opportunities facing manufacturers as they strive to secure a reliable supply of renewable electricity.
Taiwan’s Ministry of Economic Affairs projects a significant increase in electricity demand, anticipating an average annual growth of 2.5% from 2026 to 2035. This surge is largely attributed to the expansion of semiconductor fabrication plants, the proliferation of AI data centers, and the heightened demand for cooling infrastructure to support 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, presenting a substantial challenge to the island’s existing energy grid.
In response to these projected needs, Taiwan’s Ministry of Economic Affairs has outlined plans to add approximately 26 GW of new natural-gas-fired power generation capacity by 2035. However, this strategy raises concerns about Taiwan’s continued reliance on imported fossil fuels. In 2024, the island imported over 94% of its energy, making it highly vulnerable to international price volatility, potential shipping disruptions, and broader geopolitical risks.
While major global technology corporations, including Google and Apple, are actively pursuing 100% renewable electricity for their operations and supply chains, the impact of their corporate procurement initiatives on Taiwan’s overall renewable energy landscape remains limited. According to a 2024-2025 Taiwan Renewable Electricity Market Briefing by CIER and the Climate Group, RE100 members’ corporate procurement currently accounts for only about 5% of Taiwan’s total renewable generation. This highlights a significant gap between corporate commitments and the actual supply of accessible renewable energy in the Taiwanese market.
Key structural obstacles impeding the widespread adoption of renewable electricity for Taiwan’s tech industry include:
- Limited Renewable Energy Supply: The current installed capacity of renewable energy sources is insufficient to meet the rapidly growing demand from energy-intensive industries like semiconductors.
- Grid Integration Challenges: Integrating intermittent renewable sources like solar and wind into a grid designed for baseload power presents technical and infrastructural challenges.
- Procurement Barriers: Despite strong corporate demand, the mechanisms for corporate procurement of renewable energy are not yet fully developed or sufficiently scaled to meet the needs of major industrial players. This includes issues related to contract availability, pricing, and long-term supply security.
- Policy and Regulatory Frameworks: While policies are evolving, there is a need for more robust and stable regulatory frameworks that incentivize and facilitate large-scale renewable energy investments and procurement by industries.
"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 critical need for a cohesive national strategy that aligns energy policy with the imperatives of economic stability and technological leadership.
An Action Plan for a Clean AI Ecosystem
To effectively align the rapid expansion of artificial intelligence with pressing global climate objectives, the distinguished panelists at the Greenpeace East Asia webinar proposed a series of targeted reforms aimed at fostering a clean and sustainable AI ecosystem. These recommendations focus on policy, investment, and technological innovation.
Firstly, there is a critical need to accelerate the deployment of renewable energy sources and enhance grid resilience. This involves not only increasing the installed capacity of solar, wind, and other renewable generation but also investing in grid modernization, energy storage solutions, and smart grid technologies. Such enhancements are crucial to ensure a stable and reliable supply of electricity, particularly for the energy-intensive operations of data centers and AI chip manufacturing facilities. Policy frameworks should be designed to incentivize private investment in renewable energy projects and facilitate their integration into the national grid.
Secondly, the panelists called for enhanced transparency and accountability throughout the AI supply chain. This includes developing robust methodologies for measuring and reporting the energy consumption and carbon footprint of AI models and their underlying infrastructure. Greater transparency would empower consumers, investors, and policymakers to make informed decisions and hold companies accountable for their environmental impact. Standardized reporting mechanisms and third-party verification could significantly bolster trust and drive responsible innovation within the AI industry.
Thirdly, the initiative advocates for fostering collaborative partnerships between governments, industry, and research institutions. Such collaborations are essential for driving innovation in energy-efficient AI hardware and software, developing sustainable data center designs, and exploring novel energy solutions. Public-private partnerships can leverage diverse expertise and resources to overcome technical hurdles and accelerate the adoption of clean technologies. Furthermore, international cooperation is vital to address the global nature of the AI supply chain and ensure that decarbonization efforts are coordinated across different regions. The webinar itself served as a testament to this collaborative spirit, bringing together diverse stakeholders to share insights and forge common ground. By implementing these interconnected strategies, the global community can work towards harnessing the transformative power of AI while mitigating its environmental impact and building a more sustainable future.
Suro Senen
