Analysis of the role of AI in driving a circular economy
- Sylvain Richer de Forges
- 2 hours ago
- 1 min read
AI & Sustainability series - Can AI help us close the loop in a truly circular economy?
The promise of a circular economy lies in designing out waste, keeping materials in use, and regenerating nature. But the complexity of tracking materials, predicting product life cycles, and optimizing reuse pathways has always been a challenge.
That’s where AI steps in. And it might just be the game-changer we’ve been waiting for.
Material flow analytics: AI can trace products and components across supply chains—identifying where value is lost and how to recapture it.
Demand prediction: Machine learning helps companies forecast product usage patterns, enabling more efficient repair, remanufacturing, and redistribution strategies.
Smart waste sorting: AI-driven robotics can now sort waste with up to 95% accuracy [Ellen MacArthur Foundation], improving recycling rates and reducing contamination.
Product-as-a-Service optimization: AI can dynamically manage leasing or sharing platforms, improving asset utilization and reducing the need for new resource extraction.
The circular economy needs more than intention. It needs intelligence—the kind AI can deliver at scale.
As we push toward more sustainable business models, AI isn’t just an enable, it’s fast becoming a catalyst.
What examples have you seen of AI driving circular innovation in your industry?
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