Op-ed by Gohar Sargsyan, Head of Sustainability Business, Tata Consultancy Services (TCS) Europe.
Artificial intelligence is rapidly transforming how businesses, governments, and societies operate. A recent TCS study found that 57% of global CEOs are optimistic about AI’s impact, and 72% of companies plan to adopt AI technologies. But amid all the buzz, one crucial question remains: is AI itself sustainable?
AI offers clear benefits for tackling sustainability challenges – yet it also demands significant energy with serious environmental impact, creating a paradox. To fully harness AI’s promise, we must balance its potential with its environmental footprint.
AI’s role in sustainability
AI offers powerful tools in driving change in three major areas:
- Energy Efficiency & Climate Action: AI powers smart grids by predicting electricity demand and reducing waste. It improves renewable energy output through accurate forecasting of wind and solar production. Businesses are also using AI to cut carbon emissions by optimising supply chains and logistics.
- Waste Management & Circular Economy: AI enhances recycling by identifying materials in waste streams. It also enables predictive maintenance, minimising resource loss, and supports the design of sustainable materials.
- Urban Planning & Transport: AI reduces traffic congestion and emissions through optimised public transit and smart traffic management. Smart buildings use AI to reduce energy use, while AI-powered supply chain tools lower transportation-related emissions.
Beyond this, AI is helping protect biodiversity, improve agriculture, and manage water more efficiently. By leveraging AI insights, industries, governments, and individuals can make more sustainable choices for a healthier planet.
The AI energy paradox
Despite its benefits, AI’s environmental impact is growing. Large AI models require enormous computing power, which translates into high energy use. Even efficient systems can lead to higher total consumption if they’re deployed everywhere – a phenomenon known as the ‘rebound effect’. Take these examples:
- Smart Homes: AI can cut energy use per hour, but cheaper bills may encourage larger homes or more appliances – raising overall use.
- Manufacturing: AI boosts production efficiency, but lower costs may lead to overproduction.
- AI Itself: As AI becomes more embedded across industries, the energy demand of running countless models could surge – even if each is individually efficient.
Towards sustainable AI
Addressing this issue calls for both technological and policy solutions. We must improve the efficiency of AI models, integrate renewable energy, and explore innovative infrastructure options. Encouraging signs are already emerging:
- Waste Heat Reuse: Leafcloud (Netherlands) uses data centre heat to warm buildings and greenhouses. Equinix (France) heats Olympic facilities in Paris with repurposed server heat.
- Efficient Technologies: NVIDIA is building more energy-efficient GPUs. Singapore’s Sustainable Metal Cloud (SMC) cuts energy use by up to 50% using immersion cooling.
- Model Innovation: China’s DeepSeek has developed AI models that use significantly less power, offering a glimpse of what’s possible in low-energy AI.
Promising solutions must scale or improve AI efficiency to cut energy demand. Despite green pledges, hyperscale data centres (Google, Microsoft, Amazon) still emit heavily, focusing on offsets over redesign.
Ethics and regulations matter too
Sustainability isn’t only about emissions. AI must also be ethical—free of bias, respectful of privacy, and mindful of its impact on jobs. The European Union AI Act is a step in this direction, pushing for fairness, transparency, and accountability.
Powering the sustainable AI future
To build a sustainable AI ecosystem, two strategies are essential: increasing AI model and hardware efficiency, and reusing data center waste heat to offset emissions.
Only through collaboration among researchers, businesses, and policymakers can we ensure that AI drives progress without compromising the plane.
About the author
Dr Gohar Sargsyan is Head of Sustainability Business at TCS Europe and drives the company’s sustainable business growth. She has over 25 years of experience in business and IT, including in leadership roles, and has a proven track record of implementing complex multidisciplinary initiatives and solutions for industries such as manufacturing, financial services, energy and utilities, transportation and logistics, as well as the public sector. Dr Sargsyan is the recipient of the 2024 IEEE TCHS Outstanding Leadership Award.
