Balancing AI Growth with Clean Energy

• 30 Apr 2025

For Prelims: International Monetary Fund, Artificial Intelligence, Renewable energy, Fossil fuels, Rare-earth minerals, IndiaAI Mission 

For Mains: Environmental impact of Artificial Intelligence, Integration of Renewable Energy in emerging technologies, Sustainable AI infrastructure in India 

Source:TH 

Why in News?  

The International Monetary Fund (IMF) has noted that the economic benefits of Artificial Intelligence (AI) may outweigh its environmental costs from increased energy demand in data centres, especially in countries integrating renewable energy.  

• As India’s AI infrastructure expands, integrating renewable energy into AI development becomes crucial. 

How Can AI Drive Economic Growth in India? 

• Massive Economic Potential: A Google report projects AI adoption could generate Rs 33.8 lakh crore in economic value by 2030.  
  • AI will be crucial in achieving India's USD 1 trillion digital economy target by 2028, contributing 20% to the nation’s GDP. 
• Enhancing Productivity Across Sectors:  
  • AI in Agriculture: With 70% of rural households dependent on agriculture, AI can optimize farming through satellite imagery and machine learning, predicting crop diseases and enhancing yields. 
    • Project Farm Vibes, leverages AI to empower farmers with data-driven insights for sustainable farming. It improves crop production by 40%, reduces water use by 50%, and lowers fertilizer costs by 25%.  
  • Manufacturing: AI adoption in manufacturing is increasing, with companies like Tata Steel using AI for predictive maintenance, customer personalization, and quality control, driving efficiency and supporting the “Make in India” initiative. 
  • Financial Inclusion: AI can help India’s unbanked population access financial services. Platforms like OnFinanceAI are using AI to identify and onboard unbanked individuals based on mobile and transaction data .  
    • AI can also enhance India’s Unified Payments Interface (UPI), streamlining financial services and contributing to greater economic participation. 
  • Public Service: AI integration into India’s Digital Public Infrastructure (e.g., Bhashini) enhances public service delivery, positioning India as a leader in AI-powered governance. 

What is the Environmental Footprint of AI? 

• Energy Consumption: AI models rely heavily on data centres, which are large-scale facilities housing AI servers and storage. These centres consume significant amounts of electricity, much of which still comes from fossil fuels. 
  • A single AI query (e.g., ChatGPT) uses 10 times the energy of a Google search. 
  • In 2024, data centres consumed 415 terawatt-hours (TWh) (about 1.5% of global electricity).  
    • By 2030, this will more than double to 945 TWh, surpassing Japan’s current consumption.  
  • According to the IMF, AI expansion alone could increase electricity prices by up to 9% in the US, putting additional pressure on energy systems. 
    • Countries that are well-prepared with renewable energy infrastructure will face lower social and environmental costs as they pursue AI growth. 
• Carbon Emissions: AI systems, especially those powered by fossil fuel-based electricity, contribute to greenhouse gas (GHG) emissions, exacerbating global warming. 
  • AI hardware and data centers contribute 1% of global GHG emissions, expected to double by 2026. 
• Water Consumption: Data centres require massive amounts of water to cool their electrical components to prevent overheating. 
  • Training a large AI model like GPT-3 can consume up to 700,000 litres of fresh water, equivalent to producing  320 Tesla electric vehicles. 
  • AI-related infrastructure could soon consume six times the water of Denmark, a country with 6 million people. 
  • As water scarcity grows, this intensifies the pressure on already limited freshwater resources, particularly in areas where access to clean water is already a challenge. 
• Resource Use and Mining: The production of AI servers and related infrastructure requires the mining of rare-earth minerals and other materials. 
  • Manufacturing just 2 kg of a computer requires up to 800 kg of raw materials, many of which are sourced from environmentally destructive mining operations. 
  • AI-powered devices depend on minerals like lithium, cobalt, and rare earth elements, which are often extracted through unsustainable methods, contributing to deforestation and soil degradation. 
• E-Waste Generation: The rapid growth of AI infrastructure leads to a significant increase in e-waste, including servers, old chips, and obsolete electronics. 
  • These items contain hazardous materials such as mercury, lead, and other toxic substances, making them harmful to both the environment and human health. 

How is AI being used to Address Environmental Challenges?? 

• Pollution Control: AI systems like IBM’s Green Horizon project are used to track air pollution, monitor sources, and recommend strategies to reduce pollution. 
  • In cities, AI can simulate the effects of different strategies to reduce air pollution or heat islands, such as planting trees or adjusting traffic patterns. 
• Weather Forecasting: Google’s GenCast uses AI to enhance weather forecasting and climate modeling by analyzing data from satellites and sensors.  
  • It improves the accuracy of extreme weather predictions like hurricanes and floods. AI also refines climate models to identify the most reliable ones for better disaster preparedness. 
• Forest Conservation: AI-powered satellite imagery is helping monitor forests in real time. It identifies changes in forest cover, illegal logging, and deforestation hotspots, enabling authorities to take swift action. 
  • AI analyzes historical data to predict forest growth trends and health, aiding in sustainable forestry management and effective reforestation efforts. 
• Ocean Conservation: AI-powered sensors and cameras track marine species and their habitats. Machine learning helps monitor animal movements and behaviors, forming the basis for marine conservation strategies. 
  • AI is capable of identifying and tracking ocean pollution sources like oil spills and plastic waste using satellite images, enabling quicker cleanup efforts. 
  • Fishial.AI is building the world’s largest open-source fish species database, promoting global collaboration for fish conservation and research. 

What is India's Approach in Integrating AI with Renewable Energy? 

• Integration of AI with Renewable Energy: India under the IndiaAI Mission is recognizing the need to integrate renewable energy sources into its growing AI infrastructure. 
  • NITI Aayog’s National Strategy for Artificial Intelligence focuses on leveraging AI for economic growth and social inclusion while integrating renewable energy to mitigate the energy-related costs of AI development. 
  • India, at the AI Action Summit in Paris, emphasized the need to align AI growth with renewable energy adoption. 
• Future Prospects with Nuclear Energy: The use of small modular reactors in emerging AI data centre clusters is being explored as a potential source of clean energy. 
• Balancing AI Growth with Net Zero Goals: India’s 2070 net-zero target requires the balancing of industrial expansion, like AI, with a scaling-down of conventional energy sources. 

How is India Transforming into a Global AI Powerhouse? 

Click here to Read: India’s AI Revolution

What are India's Challenges in Integrating AI with Renewable Energy? 

• Limited Renewable Energy Capacity: India still relies heavily on fossil fuels (only , 44.72% of the total power installed capacity is from non-fossil-based sources), limiting the use of renewables for AI infrastructure. 
  • Solar and wind energy are intermittent, making stable AI energy supply challenging. Additionally, energy storage technologies, like batteries, remain underdeveloped and costly. 
• Insufficient Grid Infrastructure: The grid faces reliability issues and transmission losses, hindering the integration of renewable energy for AI data centers.  
  • To accommodate decentralized renewable energy, India’s energy grid requires significant modernization and upgrades. 
• AI’s High Energy Consumption: AI technologies, particularly deep learning, require significant energy, raising concerns about sustainability. Rising electricity prices could increase operational costs for AI sectors. 
• Lack of Integrated Policy Framework: Policies on AI and renewable energy are largely separate, lacking a comprehensive strategy. Additionally, there are limited incentives for green data centers. 
• Economic and Financing Barriers: The significant upfront investment required for renewable energy infrastructure to support AI can be a barrier to implementation. 
  • The long-term return on investment (ROI) for renewable energy projects is often uncertain, discouraging private sector participation. 
• Environmental Trade-Offs in AI Manufacturing: The mining of minerals and metals required for AI hardware can contribute to environmental degradation. 
  • The high water consumption in the manufacturing of electronics used for AI technologies adds additional pressure on India’s already strained water resources. 

How can India Align its AI Ambitions with Sustainable Energy Practices? 

• Massive Solar and Wind Capacity: India’s climate offers an abundance of solar and wind energy, with over 300 sunny days annually and strong wind speeds.  
  • These renewable sources can fuel AI data centers, reducing reliance on fossil fuels. 
  • Expanding renewable energy capacity through initiatives like the National Solar Mission and Green Energy Corridors will further support this transition, ensuring a sustainable energy foundation for AI development. 
• Green Backup Power: India’s data centers should shift from diesel generators to green backup solutions like hydrogen fuel cells and batteries. 
  • The National Green Hydrogen Mission can drive adoption of hydrogen-based clean energy. This will reduce carbon emissions and enhance energy reliability. 
  • With water availability being a challenge, integrating technologies such as fuel cells, which produce water as a by-product, can help reduce the water footprint of AI data centers. 
• AI-Powered Smart Grids and Energy Optimization: India can leverage AI to create smart grids that optimize electricity distribution. 
  • Promote energy-efficient hardware (e.g., low-power chips) and cooling technologies (e.g., liquid cooling) to minimize electricity and water usage. 
  • AI algorithms can analyze real-time data to predict energy demand and dynamically allocate renewable resources, enhancing efficiency and reducing reliance on fossil fuels. 
• Sustainable Infrastructure Development: India can incentivize the establishment of data centers powered by 100% renewable energy, as seen in Google’s and Microsoft’s AI-powered data centers in Hyderabad and Pune, respectively. 
• Promote Pilot Projects: The government should fund and support pilot projects that explore sustainable data center designs and innovative technologies that reduce energy and water consumption. 
• Support Startups and Innovation: With over 1,000 AI startups and a growing clean energy startup ecosystem like ReNew Power, the government can foster innovation by promoting green technology integration within AI companies. 

Drishti Mains Question:

Discuss the environmental footprint of Artificial Intelligence. How can renewable energy integration help mitigate these impacts? 

UPSC Civil Services Examination, Previous Year Question (PYQ)   

Prelims

Q. With the present state of development, Artificial Intelligence can effectively do which of the following?(2020)

1. Bring down electricity consumption in industrial units 
2. Create meaningful short stories and songs 
3. Disease diagnosis 
4. Text-to-Speech Conversion 
5. Wireless transmission of electrical energy 

Select the correct answer using the code given below:  

(a) 1, 2, 3 and 5 only   

(b) 1, 3 and 4 only  

(c) 2, 4 and 5 only   

(d) 1, 2, 3, 4 and 5  

Ans: (b) 

---

Mains

Q. What are the main socio-economic implications arising out of the development of IT industries in major cities of India? (2021)

Q. “The emergence of the Fourth Industrial Revolution (Digital Revolution) has initiated e-Governance as an integral part of government”. Discuss. (2020)