Author: Ilham Perdana LazuardhiEditor: Achmed Faiz Yudha Siregar
The adoption of AI in Indonesia represents a form of modernization in society and the digital technology industry. According to the Indonesia AI Report 2025, 97% of 1,000 Indonesians surveyed use AI for academic, entertainment, and business purposes. Meanwhile, 69% of users engage with AI at least three times a week, indicating a relatively high level of productive use.[1] This fact indicates the growing operational requirements of AI infrastructure for expanding building, processing resources, and ensuring the availability of energy supplies.
As one of the countries with a large number of AI users, Indonesia is projecting the development of domestic data centers to store, process, and distribute data through computing infrastructure so that it can operate securely, rapidly, and efficiently.[2] Through greater independence in data center infrastructure, Indonesia is laying the foundation for sovereign AI, namely the capacity of a country to independently develop, operate, and manage its AI ecosystem, while simultaneously promoting digital sovereignty, or the capacity of a country to control strategic digital assets without becoming fully dependent on foreign actors. This approach is intended to strengthen economic competitiveness, national resilience, and digital sovereignty in the future.[3]
The Neglect of the Environment in AI Strategy
The AI ecosystem affects not only the development, digital, and economic dimension, but also the environment. From an ecological perspective, AI can serve as a reliable tool for supporting climate action, improving energy-grid efficiency, modeling and predicting climate change, and monitoring climate-related threats which contribute to scientific discoveries and industrial development aimed at environmental sustainability.[4][5] On the other hand, AI infrastructure requires intensive amounts of energy and resources.[6] AI consumes substantial amounts of energy, thereby contributing significantly to increasing carbon emissions. The training of GPT-5 alone reportedly generates 42,000 tons of CO₂ emissions.[7] Indirectly, the AI industry affects the environment through increasing demand for data-storage units, digital services, cloud computing, and data centers. In this context, AI-related economic and technological activities contribute to resource degradation and increased energy consumption.[8]
The UNU-INWEH report identifies the land footprint, water supply, and electricity required for AI operations.[9] In 2025, the land footprint of AI data centers reached 6,900 km² and is projected to exceed 14,500 km² by 2030, equivalent to approximately twice the area of Jakarta. Developments in the United States provide an illustration of what may occur when demand for AI building exceeds the availability of land in industrial areas, prompting construction to shift toward areas near residential communities, where it can generate noise and opposition from surrounding residents.[10]
AI building also consumes freshwater for machine cooling, electricity generation, and semiconductor manufacturing.[11] The amount of water used for AI training reaches at least 1.6 billion liters, while water associated with electricity generation reaches 4.5 trillion liters and is projected to reach 9.3 trillion liters by 2030, equivalent to the minimum annual domestic water requirements of 1.3 billion people in Sub-Saharan Africa. In 2025, global data center electricity consumption reached 448 TW. By 2030, data center electricity consumption could reach 945 TWh, equivalent to the electricity consumption of the world’s sixth-largest electricity-consuming country.[12]
At the same time, demand for critical minerals is increasing to meet the needs of construction on data center infrastructure and electronic devices used in AI technologies.[13] For example, semiconductors and microelectronics require boron and silicon, data-storage units such as HDDs, SSDs, and memory chips require lithium and silicon, while connectivity networks and circuit boards require nickel and cobalt.[14] Increased demands for providing such infrastructure and technologies can contribute to land subsidence, water contamination, and deforestation, which in turn contribute to biodiversity and habitat loss as well as air pollution affecting local communities.[15] These considerations require international attention, particularly from Indonesia as a developing country with a large population of AI users seeking to position itself within the global AI industry.
In Indonesia, Cikarang and Batam have emerged as industrial areas designated for data center development. Cikarang’s accessibility to the Greater Jakarta metropolitan area, which represents the largest and most mature data center market, provides advantages in terms of goods distribution, internet connectivity, and adequate electricity infrastructure. Meanwhile, Batam has become a location for the development of international connectivity and data center facilities because it functions as a hub for several hyperscalers and telecommunications companies.[16]
In reality, Indonesia’s AI ecosystem continues to face challenges related to the equitable distribution of digital infrastructure, electricity supply, and adequate internet connectivity. Komdigi has indicated the need to develop a more adequate AI ecosystem through completing the formulation of a Presidential Regulation on an AI roadmap.[17][18] In response to this urgency, the Ministry of National Development Planning/BAPPENAS released the Rencana Induk Pemerintah Digital Nasional 2025-2045 as a guideline for the development of national data centers. The government has also established a development framework through the Peta Jalan Infrastruktur Digital Indonesia Tahun 2026-2030. The report estimates that domestic data center energy capacity stood at approximately 290 MW as of June 2025, while projected demand over the following two years is approximately 1.5–2 GW.[19] If Indonesia intends to enter a new phase of AI ecosystem development, connectivity, storage capacity, processing capabilities, security, and data resilience need to be supported by the equitable distribution of infrastructure, electricity, and internet access. However, this framework does not sufficiently incorporate the ecological dimensions of AI ecosystem development.
The Powering the Future: Advancing Green Data Centers in Indonesia report by CSIS offers a green data centers framework for developing AI ecosystem networks through an ecological approach.[20] Renewable Energy Certificates (RECs) constitute an energy-transition scenario for the data center network projected for the 2025–2035 period by combining renewable energy resources to optimize the potential of data centers in Batam and Cikarang.[21] This energy-efficiency strategy could meet 43% of electricity demand in Batam and 90% of electricity demand in Cikarang. As a result, carbon emissions could be significantly reduced by 0.56 Mt CO₂ in Batam and 5.08 Mt CO₂ in Cikarang. The required investment is also relatively low because it does not require the construction of new power plants and could instead be fulfilled through the purchase of renewable energy certificates valued at US$500 million for Batam and US$316 million for Cikarang. However, electricity costs would differ between the two regions. Batam could reduce its electricity costs to as low as 7.28 US cents/kWh, while Cikarang could experience an increase to as much as 8.77 US cents/kWh. These costs can be considered in relation to their long-term implications through the utilization of renewable energy sources for power generation.
Nevertheless, the provision of green data centers alone is insufficient. As a consumer of AI services, the next step is to ensure that the land, water, electricity, and pollution footprints of digital infrastructure are managed in ways through Presidential Regulations and the other legal instruments that can help address disparities in population welfare while strengthening the bargaining position of national products within global industrial supply chains. By simultaneously ensuring access to suitable land, maintaining a commitment to renewable energy transitions, and distributing digital infrastructure more equitably, the AI ecosystem can promote investment and technological advancement while supporting environmental sustainability.
[1] Indonesia AI Report 2025, Kumparan, viewed 21 September 2026, (https://blue.kumparan.com/document/kumparan-Indonesia-AI-Report-2025.pdf).
[2] Microsoft 2025, Why Indonesia Needs Datacenters for an AI-Powered Future, Microsoft, viewed 18 September 2026. (https://news.microsoft.com/source/asia/2025/01/22/why-indonesia-needs-datacenters-for-an-ai-powered-future/).
[3] Telkom Indonesia 2026, Sovereign AI: Mengapa Negara Mulai Membangun AI Sendiri, PT Telkom Indonesia, viewed 18 September 2026. (https://www.telkom.co.id/sites/berita/id_ID/article/sovereign-ai-mengapa-negara-mulai-membangun-ai-sendiri-425).
[4] Amanta, F., 2024. AI is supposed to make us more efficient – but it could mean we waste more energy. The Conversation. URL: https://theconversation.com/ai-is-supposed-to-make-us-more-efficient-but-it-could-mean-we-waste-more-energy-220990 (Accessed: 19 September 2026).
[5] Chouksey, A., Rajan, A.K., Gurjar, V., Tiwari, R., Mishra, P.K., 2026. The green paradox: The climate, environmental, and sustainability implications of artificial intelligence. Global Environmental Change Advances 6, 100029. https://doi.org/10.1016/j.gecadv.2025.100029.
[6] Allain, T., 2023. Dampak lingkungan ‘data center’ tak bisa diremehkan, solusinya tak cukup dengan efisiensi energi. The Conversation. URL: https://theconversation.com/dampak-lingkungan-data-center-tak-bisa-diremehkan-solusinya-tak-cukup-dengan-efisiensi-energi-203168 (Accessed: 11 September 2026).
[7] UNU-INWEH Report: Aczel, M., Chamanara, S., Matin, M., Farsi, A., Marwala, T., Madani, K. (2026). Environmental Cost of AI’s Energy Use: Carbon, Water and Land Footprints. United Nations University Institute for Water, Environment and Health (UNU-INWEH), Richmond Hill, Ontario, Canada. 10.53328/INR26RMA002.
[8] Alnafrah, I., 2025. The Two Tales of AI: A Global assessment of the environmental impacts of artificial intelligence from a multidimensional policy perspective. Journal of Environmental Management 392, 126813. https://doi.org/10.1016/j.jenvman.2025.126813.
[9] UNU-INWEH. (2026). Rising Emissions, Depleting Water and Vanishing Land–UN Scientists: AI is Threatening Natural Resources for Billions. United Nations University. Viewed 14 September 2026. https://unu.edu/inweh/news/environmental-cost-of-AIs-Enrgy-use-carbon-water-and-land-footprints
[10] Mediana, C., 2026. Fasilitas Pusat Data Semakin Banyak Membutuhkan Lahan Industri. Kompas.id. URL: https://www.kompas.id/artikel/fasilitas-pusat-data-semakin-banyak-meminta-lahan-industri?open_from=Search_Result_Page (Accessed: 14 September 2026).
[11] Barnett-Itzhaki, Z., 2026. The water footprint of artificial intelligence: Emerging solutions and governance imperatives. Water Research 299, 125866. https://doi.org/10.1016/j.watres.2026.125866.
[12] Ibid.
[13] Okolo, C.T., 2026. Global majority countries must embed critical minerals into AI governance. Science 391. https://doi.org/10.1126/science.aef6678.
[14] Critical Minerals in AI and Digital Technologis, SFA Oxford, viewed 22 September 2026. https://www.sfa-oxford.com/knowledge-and-insights/critical-minerals-in-low-carbon-and-future-technologies/critical-minerals-in-artificial-intelligence/.
[15] Reitmeier, L & Lutz, S. (2025) What direct risks does AI pose to the climate and environment [Online]. Available at: https://www.lse.ac.uk/granthaminstitute/explainers/what-direct-risks-does-ai-pose-to-the-climate-and-environment/ (Accessed: 19 September 2026).
[16] Mediana, C., 2026b. Pusat Data Terus Dibangun, Batam Jadi Koridor Baru Digital. Kompas.id. URL: https://www.kompas.id/artikel/skkl-dan-pusat-data-terus-bertumbuh-batam-jadi-koridor-baru-digital-setelah-jabodetabek?open_from=Search_Result_Page (Accessed: 13 September 2026).
[17] Komdigi 2024, Membangun Ekosistem AI di Indonesia untuk 2030, Potensi dan Tantangan, Kementerian Komunikasi dan Digital RI, viewed 18 September 2026. (https://www.komdigi.go.id/berita/infrastruktur-digital/detail/membangun-ekosistem-ai-di-indonesia-untuk-2030-potensi-dan-tantangan).
[18] Komdigi 2026, Komdigi Jadikan Perpres AI sebagai Langkah Awal Menuju Undang-Undang AI, Kementerian Komunikasi dan Digital RI, viewed 23 September 2026. (https://portal.komdigi.go.id/kanal-publik/berita-kini/10425).
[19] Kementerian PPN/BAPPENAS. 2026. Peta Jalan Infrastruktur Digital Indonesia Tahun 2026-2030. Kementerian Perencanaan Pembangunan Nasional/Bappenas.
[20] Powering the Future: Advancing Green Data Centers in Indonesia 2026, CSIS Indonesia, Tenggara Strategics, Prasetiya Mulya University, UMBRA Strategic Legal Solutions, and the Indonesian Solar Energy Association (AESI), viewed 15 September 2026. (https://csis.or.id/publication/powering-the-future-advancing-green-data-centers-in-indonesia/).
[21] Ibid.