Balancing progress with responsibility
We’ve shared before how AI can be a powerful tool for creativity, productivity, and innovation. But there’s another side of the coin: the energy it takes to make all of this possible. As AI grows, so does its environmental footprint. Here are some ways we can keep that impact in check:

Recognize the Hidden Energy Cost
Large AI models can require enormous amounts of electricity to train and run. Awareness of this impact is the first step toward using AI responsibly.
Support Greener Infrastructure
Choosing cloud providers and partners that invest in renewable energy can significantly lower AI’s carbon footprint.
Design for Efficiency
Smaller, more efficient models and optimized hardware reduce power usage — proving that better doesn’t always have to mean bigger.
Share & Reuse AI Resources
Instead of building everything from scratch, companies can lean on open-source, pre-trained models, cutting down on the duplicated compute effort across industries.
Push for Transparency
Publishing reports on the carbon footprint of AI projects helps customers and stakeholders understand the hidden costs, creating accountability and driving progress.
Set “Green KPIs” for AI Projects
Beyond accuracy and speed, teams can track energy consumption per model or per query, ensuring sustainability becomes part of the success metrics for AI.
DID YOU KNOW?
A single ChatGPT-style query consumes around 0.3 watt-hours of electricity
Roughly 10 times more energy than a standard Google search. The real environmental impact comes from the sheer volume of queries made daily around the world
Source: Integrity Energy
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