The Ellen MacArthur Foundation and Google, with research and analytical support provided by McKinsey & Company have released an interesting paper talking about the intersection of two emerging megatrends: artificial intelligence and circular economy. This paper is based on the insights from over 40 interviews with experts, taking a closer look at how Artificial Intelligence can accelerate the transition to a circular economy. The paper also highlights how artificial intelligence is being used in the food and consumer electronics industries.
What is Circular Economy?
Circular economy is based on creating value from consuming finite resources. It is based around three principles:
- Design out waste and pollution
- Keep products and materials at their highest value
- Regenerate natural systems
A circular economy approach encourages manufacturers to extend the usability of products, by designing products for durability, repair or refurbishment.
Figure: Circular economy diagram
Why AI for circular economy?
“Design circular products, components, and materials. AI can enhance and accelerate the development of new products, components, and materials fit for a circular economy through iterative machine-learning-assisted design processes that allow for rapid prototyping and testing.
Operate circular business models. AI can magnify the competitive strength of circular economy business models, such as 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.
Optimize circular infrastructure. AI can help build and improve the reverse logistics infrastructure required to “close the loop” on products and materials, by improving the processes to sort and disassemble products, re-manufacture components, and recycle materials.”
For each of the three use cases, the paper also highlights three case studies where Artificial Intelligence was used to create circular value within current business models. First, project ‘Accelerated Metallurgy’, funded by the European Space Agency which used AI algorithms to analyse vast amounts of data on existing materials and their properties to design and test new alloy formulations. The second case study talks about software company ZenRobotics was the first company which uses an AI software ZenBrain to recover recyclables from waste.
The paper also talks about two other case studies where AI was used to grow food regeneratively and make better use of its by-products. The paper points that “the potential value unlocked by AI in helping design out waste in a circular economy for food is up to $127 billion a year in 2030.” In another case study, AI helped in circulating consumer electronics products, components, and materials. “The equivalent AI opportunity in accelerating the transition towards a circular economy for consumer electronics is up to $90 billion a year in 2030.”
The paper urges stakeholders and industrialists to take inspiration from the use cases and case studies explored in the paper to create and define new opportunities for circular economy applications of AI. It suggests three ways:
“Creating greater awareness and understanding of how AI can support a circular economy is essential to encourage applications in design, business models, and infrastructure
Exploring new ways to increase data accessibility and sharing will require new approaches and active collaboration between stakeholders
As with all AI development efforts, those that accelerate the transition to a circular economy should be fair and inclusive, and safeguard individuals’ privacy and data security”
Circular economy coupled with AI is still in its early stages. The true impact of AI in creating sustainable economy can only be realized with proper funding, investment, and awareness. Reports like these do help in creating awareness among the VCs, stakeholders, software engineers, and tech companies, but it’s up to them, how they actually translate it to implementation.
You can view the full report here.