Thailand pauses 49 data center projects for new green rules
- Thailand has suspended 49 data center projects to draft new environmental regulations.
- The government is consolidating oversight across 16 agencies to manage resource consumption.
- Thailand approved $27 billion in AI and data center investments during the first half of 2026.
- Energy Minister Akanat Promphan suggested classifying data centers as a separate consumer group with higher tariffs.
Thailand has suspended construction on 49 data centre projects while the government develops its first industry-specific environmental regulations. The work has been paused for several months to allow for the drafting of these new standards.
Authorities stated that the pause is temporary and confirmed that they do not intend to ban foreign investment. The government now seeks to implement tighter oversight of site construction.
Government commission targets 16 agencies to unify site standards
A government commission found that data regarding energy use, water consumption, and environmental hazards was distributed among 16 different agencies. The commission is now working to develop common standards for site selection, safety, resource utilisation, and economic returns.
These new rules aim to preserve national water and electricity resources. Energy Minister Akanat Promphan suggested that data centres should be classified as a separate consumer group subject to higher tariffs. He noted that these facilities consume large amounts of power, including electricity produced with costly imported gas.
Thailand attracts $27 billion in AI and data center investments
Thailand approved 88 artificial intelligence and data centre projects in the first half of 2026, representing a combined investment of US$27 billion. The nation currently has 216 megawatts of installed compute capacity, with nearly one gigawatt under active construction.
This pipeline represents a four-fold increase in capacity. Analysts estimate that Thailand will require between three and five gigawatts of capacity by the end of the decade to satisfy domestic and global demand.
AI infrastructure risks a green squeeze on local power grids
Thailand is facing a balance between an AI investment boom and its green-energy objectives. Modern AI racks can consume up to 80 kilowatts of power, which is sixteen times the consumption of traditional data centre racks.
Dr Mueller warned of a "green squeeze" where data centres absorb most clean power, leaving the local population reliant on non-renewable fossil fuels.
The national power-grid infrastructure is concentrated around population centres rather than optimal data centre locations. This creates distribution challenges for utility providers.
Global tech giants shift investment to Southeast Asia amid Western moratoriums
This shift has prompted hyper-scalers to direct their investment toward Southeast Asia. Southeast Asia currently accounts for about 50% of data centre capacity under construction in the Asia-Pacific region.
However, Southeast Asian countries are also beginning to limit data centre construction because of rising electricity and water use. The Bangkok region has data centre capacity under construction or planned totaling 2,084 MW.
Regional peers in Indonesia and Malaysia tighten project oversight
Regional neighbours are responding to infrastructure pressures and community concerns by tightening project oversight. On 30 September, West Java Governor Dedi Mulyadi ordered a halt to the construction of Singapore’s BDx Data Centres 640 MW AI complex in Jatiluhur. This order was issued because permits and an environmental impact assessment had not yet been completed, rather than due to confirmed environmental violations. The Guardian reported that Indonesia also halted the build-out of a large AI-focused data centre complex.
In Malaysia, state government head Onn Hafiz Ghazi said investment in the data centre sector in Johor has reached about $40 billion. Company analyst Alvin Tan warned that the swift construction of data centres may overload local grids and will necessitate upgrades to transmission and distribution networks. Residents in Johor protested against a complex by China’s ZData Technologies in February 2026, fearing construction dust and the deterioration of water supply. Local officials in Johor have since tightened the evaluation of new projects, now considering electricity and water usage, environmental safety, and effects on nearby communities.
International regulatory trends emerge from the US to Europe
International regulatory scrutiny is increasing as nations implement moratoriums and stricter permitting processes for data centre construction. Amsterdam implemented a one-year moratorium on new developments in 2019 and extended the ban on new facilities or expansions within the municipality until at least 2030. The Dutch government also introduced a 2022 hyperscale ban restricting large facilities to two designated locations, although Microsoft received approval in January 2026 for a project divided into three towers that each fall below the size threshold.
In the United States, state-level authorities are enacting diverse restrictions on the sector. Texas Governor Greg Abbott ordered a pause on new approvals through the state's grid interconnection process on 10 November 2026, requiring developers to provide additional information on power demand, water usage, and tax incentives.
Residents of Monterey Park, California, voted to permanently ban data centres through a ballot measure in June 2026.
Industry experts urge efficiency and liquid cooling adoption
Industry experts are urging a transition toward higher efficiency and advanced cooling technologies to manage the rising electricity demands of artificial intelligence. Dr Etienne Mueller, an assistant professor at CMKL University, said at the Sustainability Expo 2026 that Thailand faces significant green energy challenges during its current AI boom.
Public enthusiasm for AI remains high in Thailand, which contrasts with growing scepticism in the United States and Europe. Academics and developers are advised to improve software efficiency, use model quantisation, and build Thai large-language models that deliver high performance with smaller computational footprints.
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