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Why transparency matters for sustainable data centers and carbon-neutral artificial intelligence (AI)
Can Hankendi1, Ayse K Coskun1, Benjamin K Sovacool2
1Electrical and Computer Engineering Department, Boston University, Boston, MA, USA.
Iscience
|November 17, 2025
Summary
Artificial intelligence (AI) growth increases data center energy use and carbon footprints. Greater data sharing transparency is crucial for developing sustainable AI and reducing environmental impact.
Area of Science:
- Computer Science
- Environmental Science
- Sustainability
Background:
- Artificial intelligence (AI) applications require significant computational power, leading to escalating energy consumption in data centers.
- Data centers' electricity demand is projected to reach 9% of global demand by 2030, highlighting a critical environmental concern.
- The rapid expansion of the AI industry exacerbates the environmental challenges associated with data center operations.
Purpose of the Study:
- To underscore the urgent need for transparency in data sharing to address the environmental impact of AI and data centers.
- To highlight the limitations researchers face in developing sustainability solutions due to a lack of operational data.
- To advocate for actionable strategies to foster innovation and achieve carbon-neutral data centers.
Main Methods:
- This study is a conceptual analysis and review of the current challenges and future needs for sustainable AI and data center operations.
- It synthesizes information on energy consumption trends and the role of data transparency in environmental impact mitigation.
- The approach emphasizes the critical importance of data sharing for research and development in green computing.
Main Results:
- A significant barrier to sustainable AI and carbon-neutral data centers is the lack of transparency in operational data sharing.
- Limited data access hinders the development of effective solutions for minimizing the carbon footprint of AI.
- Increased transparency is essential for innovation and the creation of practical strategies to reduce environmental impact.
Conclusions:
- Urgent action is needed to promote data transparency to enable the development of sustainable AI and data center practices.
- Fostering innovation through data sharing is key to addressing the growing environmental challenges posed by the AI industry.
- Implementing transparency measures is essential for ensuring a sustainable future for the data center industry.
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