Why AI Isn't Inherently Unsustainable
Boris Gamazaychikov
AI Sustainability Leader
AI is unsustainable right now - but it doesn't need to be.
AI is unsustainable right now - but it doesn't need to be.
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Why AI Isn't Inherently Unsustainable
2 mins 18 secs
Key learning objectives:
Outline what better AI would look like
Overview:
AI is not inherently unsustainable. Instead of relying on massive general-purpose models in giant data centres for simple tasks like summarising a document, a sustainable future relies on small, domain-specific open models running on distributed chips, laptops, and phones. Enterprises have a major opportunity to reorient the industry toward sustainability. By using procurement actions (such as specific RFP questions and strict contract requirements) buying organisations can demand environmental accountability from AI vendors.
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Summary
How can enterprise buyers drive sustainability across the AI industry?
Individual users cannot directly control the footprint of AI, but enterprise buyers hold substantial leverage. The AI industry is currently in a transition period where vendors need customer revenue to justify their massive infrastructure spend, making them far more responsive to customer demands. Enterprises have a major opportunity to reorient the industry toward sustainability. By using procurement actions (such as specific RFP questions and strict contract requirements) buying organisations can demand environmental accountability from AI vendors.
What would a more sustainable future for AI look like?
AI is not inherently unsustainable. Instead of relying on massive general-purpose models in giant data centres for simple tasks like summarising a document, a sustainable future relies on small, domain-specific open models running on distributed chips, laptops, and phones. Data centres themselves can also become genuine community assets when managed properly. This includes powering them with clean energy, battery storage, and sustainable water systems, or even capturing excess heat to warm nearby homes.
How can organisations ensure they are using AI responsibly?
Organisations can approach AI responsibly by evaluating three core considerations:
AI is not inherently unsustainable. Instead of relying on massive general-purpose models in giant data centres for simple tasks like summarising a document, a sustainable future relies on small, domain-specific open models running on distributed chips, laptops, and phones. Data centres themselves can also become genuine community assets when managed properly. This includes powering them with clean energy, battery storage, and sustainable water systems, or even capturing excess heat to warm nearby homes.
How can organisations ensure they are using AI responsibly?
Organisations can approach AI responsibly by evaluating three core considerations:
- Do you need AI for this task? Start with the problem rather than the technology, as simple automation might be a better solution.
- Does this use case require a large, general-purpose model? Match the model to the specific complexity of the problem rather than assuming a bigger model is better.
- What can you do if you cannot control the footprint yourself? Actively influence providers through strategic procurement, vendor selection, and purchasing decisions.
How can enterprise buyers drive sustainability across the AI industry?
Individual users cannot directly control the footprint of AI, but enterprise buyers hold substantial leverage. The AI industry is currently in a transition period where vendors need customer revenue to justify their massive infrastructure spend, making them far more responsive to customer demands. Enterprises have a major opportunity to reorient the industry toward sustainability. By using procurement actions (such as specific RFP questions and strict contract requirements) buying organisations can demand environmental accountability from AI vendors.
Subscribe to watch
Access this and all of the content on our platform by signing up for a 7-day free trial.
Boris Gamazaychikov
Boris Gamazaychikov is an AI Sustainability Leader and environmental engineer by training, focused on aligning AI development with climate action. He is the Co-Founder and CEO of Sustainable AI Group, a research and advisory firm helping enterprises understand and act on the environmental impacts of AI. Previously, he served as Head of AI Sustainability at Salesforce, where he built the company's AI sustainability strategy from the ground up and co-created the AI Energy Score - the first standardised benchmark for measuring AI model energy use.
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