Last updated on November 18, 2025
KUALA LUMPUR, 08 November 2025 — As artificial intelligence (AI) continues to transform industries, NTT DATA, a global leader in AI, digital business, and technology services, is calling for sustainability to be embedded into every layer of AI development and deployment to mitigate its growing environmental footprint.
In its latest white paper, Sustainable AI for a Greener Tomorrow, NTT DATA highlights the pressing need to address the environmental costs of AI, which demands vast amounts of energy, water, and hardware resources. The report notes that by 2028, AI workloads could account for more than 50% of global data centre power consumption, driven by surging computational demands to train large language models, run inference pipelines, and maintain always-on services.
“The resource consequences of AI’s rapid growth are daunting, but the technology also holds the power to solve the very problems it creates,” said David Costa, Head of Sustainability Innovation Headquarters at NTT DATA. “From optimizing energy grids and reducing emissions to improving water conservation, AI can be a force for sustainability, if designed responsibly from the start.”
The report calls for a fundamental shift in how organizations design and evaluate AI systems. Rather than focusing solely on speed and accuracy, NTT DATA urges companies to adopt holistic sustainability goals, integrating efficiency as a core design principle. It also emphasizes the importance of quantifiable environmental metrics, such as the AI Energy Score and Software Carbon Intensity (SCI), to embed sustainability into governance, procurement, and compliance frameworks.
NTT DATA further advocates a lifecycle approach to AI development that considers environmental impact from hardware manufacturing to deployment and end-of-life management. This includes extending hardware lifespans, optimizing cooling systems, and applying circular economy principles to reduce waste and resource depletion.
The report also highlights that responsibility for sustainable AI extends across the entire ecosystem, encompassing hardware manufacturers, data centre operators, software developers, cloud providers, policymakers, and investors. Cross-sector collaboration, it says, is essential to achieving meaningful progress.
At present, fragmented assessment frameworks and inconsistent sustainability metrics remain major barriers. Many organizations still measure only energy use or carbon emissions while overlooking other factors such as water consumption, rare material depletion, and e-waste generation.
To address these challenges, NTT DATA recommends best practices such as applying green software engineering principles, running AI workloads during periods of renewable energy availability, leveraging remote GPU services, and using modular, upgradable components to minimize waste.
While the path to sustainable AI is complex, NTT DATA concludes that an intentional, end-to-end redesign of the AI lifecycle is critical to ensuring that innovation aligns with planetary well-being. By doing so, organizations can balance technological advancement with environmental responsibility—and help build a greener, more resilient digital future.
