Artificial Intelligence and Its Hidden Carbon Footprint: An Emerging Policy Challenge

 

Artificial Intelligence and Its Hidden Carbon Footprint: An Emerging Policy Challenge

Artificial Intelligence (AI) is increasingly being projected as a transformative force in sectors such as healthcare, agriculture, education and governance. However, while its socio-economic benefits are widely discussed, its environmental footprint remains a relatively under-examined dimension. Recent studies by the OECD, UNEP and other international organisations highlight that AI development and deployment impose significant energy, water and carbon costs, raising concerns for climate action and sustainable development.

Environmental Impacts Across the AI Life Cycle

AI systems require massive computational infrastructure, including data centres, cooling systems and high-performance chips. According to an OECD working paper, the global ICT sector contributes between 1.8% to 3.9% of global greenhouse gas emissions, and AI is becoming a fast-growing component of this footprint.

UNEP (2024) estimates that by 2027, data centres housing AI servers may consume 4.2–6.6 billion cubic metres of water annually, aggravating freshwater stress. Further, training a single large language model can emit 300,000 kg of CO₂, comparable to the lifetime emissions of several automobiles. Studies also show that a single ChatGPT query consumes nearly 10 times the energy of a conventional Google search.

These figures indicate that AI, while digital, has very real physical and ecological costs — energy extraction, land use, rare-earth mining, and electronic waste.

Global Regulatory Responses

Recognising these concerns, international institutions have begun addressing the sustainability dimension of AI:

• UNESCO’s Recommendation on the Ethics of AI (2021) stresses environmental responsibility.

• European Union has integrated high-compute emissions reporting under its Corporate Sustainability Reporting Directive (CSRD).

• United States has proposed the Artificial Intelligence Environmental Impacts Act, 2024.

These efforts reflect an emerging consensus that AI governance must include climate accountability.

The Indian Context: Need for Proactive Policy

In India, policy discussions on AI largely focus on its role in climate mitigation (precision agriculture, disaster forecasting, smart grids), but not on its own carbon footprint. Given India’s commitments under the Paris Agreement, SDG-13 (Climate Action) and its net-zero target for 2070, ignoring the environmental cost of AI could undermine long-term sustainability goals.

Extending Environmental Impact Assessment (EIA) to AI

India’s EIA Notification, 2006 mandates environmental clearance for physical infrastructure projects. A similar framework could be adapted for large-scale AI and data-centre projects by:

• Assessing energy intensity, water usage, carbon emissions, land and mineral use

• Introducing AI-specific sustainability benchmarks

• Mandating life-cycle assessments for high-compute models

ESG and Disclosure Standards

Environmental costs of AI can also be integrated into ESG reporting under SEBI and the Ministry of Corporate Affairs. Inspired by the EU’s CSRD, Indian companies could be required to disclose:

• Emissions from data centres

• Renewable energy share in compute operations

• Water footprint of cooling systems

• E-waste generation from AI hardware

Such transparency would enable responsible investment and policy correction.

Way Forward: Green AI Approach

To align AI with sustainable development, India should promote:

1. Energy-efficient model design and pre-trained model reuse

2. Renewable-powered data centres

3. Carbon-aware computing and scheduling

4. Standardised environmental metrics for AI

5. Public-private-academic collaboration on green AI research

Conclusion

AI must be viewed not only as a tool for development but also as a consumer of planetary resources. As the world enters an era of compute-intensive growth, the principle of “development without ecological degradation” must guide digital policy. Integrating environmental accountability into AI governance will ensure that technological progress strengthens, rather than weakens, India’s journey towards climate resilience and sustainable growth.