This article is drawn from the Circular Weekly newsletter from GreenBiz, running Fridays.

A key principle of the circular economy is keeping materials at their highest and best use. But with the amount of material flowing through our industrial system, "highest and best" can be a moving target.

It doesn’t have to be, according to a new report (PDF) by the Ellen MacArthur Foundation and Google. The white paper posits that artificial intelligence (AI) can be a valuable tool to help accelerate and scale the transition to a circular economy while creating new forms of value.

AI is an umbrella term for technologies that can learn, reason and perform human-like functions (pattern recognition, prediction, optimization) with more accuracy, speed and efficiency than humans. Given humanity’s inefficient, waste-ridden industrial systems, AI can help solve some complex problems that stand between the current linear system and a more circular one.

And where there’s efficiency, there’s economics. Through product and material design, operating new business models and optimizing infrastructure, AI could unlock up to $127 billion annually for the food value chain and up to $90 billion for consumer electronics, all by 2030, according to the report.

AI could unlock up to $127 billion annually for the food value chain and up to $90 billion for consumer electronics, all by 2030. Here are three companies already harnessing the power of AI for circularity:

TOMRA : Despite the growing acceptance of ugly produce — misshapen or imperfect fruits and vegetables that consumers may deem unattractive — grocery stores struggle to sell non-uniform fruits and vegetables, which leads perfectly edible foods to wind up in the compost bin (or worse, a landfill). But this waste is avoidable. The ability to quickly sort food by its uniformity can ensure that a pristine potato ends up on the grocery store shelf while its less-attractive cousins become potato chips. TOMRA is already in adjacent businesses, such as reverse vending machines, which dispense cash for empty containers; and recycling optical sorters, used by waste-handling facilities to sort materials. Now, TOMRA is using its algorithms to analyze images and data from cameras, near-infrared spectroscopy, X-rays and lasers — to identify non-uniform produce and sort it according to its highest and best use. Stuffstr : Built on the vision of "No Unused Stuff," Stuffstr helps consumers sell their used clothing back to retailers, regardless of condition. In doing so, the company boosts reuse, increases consumer awareness about the value of unused and lightly worn clothing and builds a financial incentive to ensure unwanted apparel is kept out of landfills. On the back end, Stuffstr uses AI algorithms to forecast demand and strategically price the products it buys from consumers and sells in secondary markets. AI also helps refine Stuffstr’s sales strategy to enable experimentation and rapid feedback loops. Optoro : The rise of e-commerce has created the growing challenge of what to do with product returns. Currently, roughly 25 percent (PDF) of returns end up in landfills, as doing so is cheaper than sorting returns and returning what’s resellable back to inventory. Optoro uses AI and predictive analytics to help retailers and brands manage, process and sell returns and excess inventory through the highest-value channel.

That’s just a start. From identifying plant-based alternatives to meat to rapidly testing new and recyclable alloys, there is broad, growing and largely untapped potential to leverage AI to accelerate circularity.