Under current energy policies, the adoption of AI is expected to lead to a cumulative increase of 1.2% in greenhouse gas emissions during the same period, although greener policies could limit this rise.

The social cost of these emissions is estimated at around $39 per ton, translating to an overall cost of $50.7 to $66.3 billion, which remains lower than the expected economic benefits from AI.

Independent analysts emphasize that the environmental and economic impacts of AI will largely depend on its application, particularly in promoting energy efficiency and sustainable consumption practices.

An IMF report titled 'Power Hungry: How AI Will Drive Energy Demand' was released during the IMF's annual spring meeting in Washington on April 22, 2025.

The report predicts that economic gains from artificial intelligence (AI) will boost global output by approximately 0.5% annually from 2025 to 2030, despite the associated increase in carbon emissions from AI data centers.

The Grantham Research Institute suggests that AI could potentially help reduce carbon emissions if it fosters advancements in low-carbon technologies across various sectors.

The report emphasizes that while AI-driven economic benefits are substantial, they will not be distributed evenly across the globe, prompting calls for policymakers and businesses to address the societal costs.

Experts warn that market forces alone may not effectively guide AI towards climate-friendly applications, highlighting the necessity for proactive involvement from governments, tech companies, and energy firms.

In northern Virginia, which houses the largest concentration of data centers globally, the space occupied by these facilities is comparable to eight Empire State Buildings, illustrating the scale of infrastructure needed for AI.

The increase in emissions related to AI will depend significantly on tech companies' ability to reduce their carbon footprint through the adoption of renewable energy sources.

As AI adoption rises, the demand for energy-intensive data processing is expected to surge, coinciding with global efforts to reduce carbon emissions.

The report calls for increased funding for research and development, alongside policies to address inequalities exacerbated by advancements in AI.