NTT DATA, a global leader in AI, digital business, and technology services, has released a new white paper titled “Sustainable AI for a Greener Tomorrow,” urging organizations to embed sustainability into every layer of AI development and deployment. The paper highlights the growing environmental impact of AI — from massive electricity use to increased water consumption and e-waste — and proposes actionable strategies to make AI more resource-efficient and environmentally responsible.
According to NTT DATA, the rapid rise in AI workloads could account for more than 50% of data center energy consumption by 2028, amplifying pressure on global resources. The paper underscores that AI’s growing demand for computation, model training, and hardware production creates a significant carbon and material footprint — one that must be mitigated through smarter design, lifecycle awareness, and collective accountability.
“AI can both cause and solve environmental challenges — but sustainability must be built in from the start,” says David Costa, Head of Sustainability Innovation, NTT DATA.
“The resource consequences of AI’s rapid growth and adoption are daunting, but the technology also can empower innovative solutions to the environmental problems it creates,” said David Costa, Head of Sustainability Innovation Headquarters, NTT DATA. “AI’s capabilities can help manage energy grids efficiently, reduce emissions, and conserve water. It’s vital for organizations to recognize the challenge and build sustainability into AI systems from the start.”
The white paper outlines four core priorities for sustainable AI:
- Expand from performance to green priorities by integrating efficiency as a design principle.
- Quantify environmental impact using standardized metrics like the AI Energy Score and Software Carbon Intensity (SCI).
- Adopt a lifecycle-centric approach that considers every stage — from hardware sourcing to disposal.
- Foster shared accountability among data center operators, developers, policymakers, and consumers.
To bridge the gap between intent and action, NTT DATA recommends green software engineering, running AI workloads alongside renewable energy availability, and extending hardware lifespans through reuse and modular design.
The company concludes that an end-to-end redesign of the AI lifecycle can ensure that innovation does not come at the expense of the environment — enabling AI to become a force for sustainable progress rather than unchecked consumption.
