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Artificial Intelligence (AI) is transforming industries at an unprecedented pace. With AI tools becoming a part of workplaces and everyday life, it’s clear that AI is here to stay. But at what environmental cost?
Training and running AI systems require a lot of computing power, which can lead to large increases in the amount of electricity and cooling water used by data centers. Building the hardware needed for these systems requires specialized raw materials, each with their own set of environmental challenges. While some have attempted to estimate the carbon footprint of AI models, these figures can vary wildly depending on a variety of factors.
Despite these challenges, AI tools hold huge potential for sustainability. AI-powered automation can enhance a company’s pollution prevention (P2) efforts by optimizing supply chains, improving energy management in processes, identifying inefficiencies and more.
Do the benefits outweigh the costs? Or are we simply shifting environmental burdens from one area to another? The truth is, we don’t know. One thing is certain, though: as AI becomes more popular, sustainability must be part of the conversation. Rather than dismissing AI due to its environmental footprint, we need to ask ourselves: How can we apply P2 principles to make AI itself more sustainable?
This is the first article in our E-Tips series exploring AI and sustainability. Stay tuned as we dive deeper into how AI can support - or hinder - environmental progress.
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