Circularity advocates best get comfortable with the idea of artificial intelligence (AI). A new report from the Ellen MacArthur Foundation and Google predicts AI can “unlock” an annual value of nearly $217 billion in the food and consumer-electronics industries by 2030, simply by designing out waste.
Written with analytic support from McKinsey & Company, “Artificial Intelligence and the Circular Economy” suggests new technologies, including “faster and more agile” learning processes with iterative cycles of designing, prototyping and gathering feedback, are necessary to transition the economy from its current “take-make-dispose” model to one where products and materials are kept in use, natural systems are regenerated and economic growth is decoupled from the consumption of finite resources.
As a subset of the fourth industrial revolution, otherwise known as Industry 4.0, AI can help steer this shift by helping people parse complex and abundant data quickly and effectively. For one, it can “enhance and accelerate” the development of new products, components and materials through iterative machine-learning-assisted design processes that allow for rapid prototyping and testing. For another, AI can augment the competitive strength of circular business models, like product-as-a-service and leasing.
“By combining real-time and historical data from products and users, AI can help increase product circulation and asset utilization through pricing and demand prediction, predictive maintenance and smart inventory management,” the report’s authors wrote.
AI can also help “close the loop” in reverse logistics by improving the processes for sorting and disassembling products, remanufacturing components and recycling materials.
Among the case studies presented is that of Stuffstr, a Seattle-based social enterprise that partners with fashion retailers to buy back from customers unwanted products—clothing in particular—which it then resells on existing secondhand markets.
Stuffstr, which uses an app-based platform, employs AI algorithms to dynamically price out both the products they buy from consumers and the ones they resell in a transparent and convenient way. The backend of its service uses machine learning to ensure a “consistent classification of all re-sale items,” the report noted. “Finally, AI helps refine Stuffstr’s sales strategy through constant experimentation and rapid feedback loops.”
Not only does AI have the potential to create circular value within current business models, the study said, but it can also cut inventory levels without sacrificing the ability to meet customer demand. “This could lead to a big reduction in waste from unsold products, as well as a reduction in cost,” it added.
Is there work still to be done? Absolutely, said the Ellen MacArthur Foundation. But its point is that AI can at least bridge some of the inefficiencies that are holding back the economic overhaul that a new, circular system demands. Humans are hopelessly fallible and prone to bias; data is reassuringly less so.
“It seems clear though that new forms of cross value chain collaboration, underpinned by a shared vision and guiding principles, could harness the power of AI to help reshape the economy into one that is regenerative, resilient and fit for the long term,” the authors concluded.