How AI Accelerates the Circular Economy: The Synergy of AI and Circular Economy
By Dr. Vikas Khare
The abbreviation ‘AI’ stands for artificial intelligence which refers to the creation of computer programs capable of carrying out activities usually attributed to humans. Some of them are learning from the experience of machine learning, natural language understanding, pattern recognition and problem-solving, among others. What the circular economy does is reduce waste and utilize scarce resources. Contrary to the conventional linear economy model of “take-make-dispose”, the circular economy model seeks to preserve products, materials and resources for the longest time possible. It promotes recycling, re-using and refurbishes and reduces waste disposals and the impact of raw material removal on the environment.
The combination of AI and circular economy shows a lot of potential for dealing with environmental problems as well as sustainability. Moreover, AI technologies have great application during all the stages of the product lifetime and supply chain, which help increase resources’ efficiency, decrease waste and enhance the performance of machinery. This amalgamation can transform industries globally.
AI technologies such as machine learning algorithms and advanced data analytics that optimize processes and guide decision-making offer new insights into resource flows are made possible. They lead to reduced waste generation which creates a sustainable and green economy.
AI’s predictive maintenance, supply chain optimization and waste sorting minimize waste creation while maximizing resource utilization. These AI algorithms use data extracted from sensors and historical performance to predict potential equipment failures. Thanks to this approach, the equipment can be used for a longer duration, thus leading to fewer premature replacements. This approach is perfectly in line with the durability and longevity principles of the circular economy.
The use of robotics and computer vision in artificial intelligence can improve waste sorting and recycling. It allows getting more value out of the waste streams and improving efficiency in recycling processes as well as implementing a closed-loop system and promoting circular economy. AI helps in design suited for circular economy principles, which include recyclability, repairability, and eco-friendly materials. AI should be integrated into the designing process of businesses for the creation of products that can be easily remanufactured or recycled.
Adapting AI into a circular economy leads to the generation of different jobs in related industries like AI development, maintenance and data analysis. The need for specific skills such as those tied towards sustainable practices for greener technologies is also emerging promoting the need for a well-trained and adaptable workforce.
The usage of AI helps improve energy efficiency by identifying energy conservation measures as well as areas that require to be improved upon. Energy efficiency is aligned with the goals of a circular economy to reduce the environmental impact of production processes. The adoption of circular economy approaches through AI enables increased resource efficiency and reduces dependence on limited or non-renewable resources. Such resilience could shield societies from resource scarcity and economic decline, and contribute to the creation of more robust and stable economies.
Conscious consumerism has emerged of late as consumers are becoming more aware of the adverse effects of their choices on the environment. This causes a significant change in purchasing behavior and creates a feeling of environmental responsibility.
Speeding up the circular economy using AI not only deals with environmental problems but also promotes future economic sustainability and social accountability. Besides environmental benefits, it holds great potential in f creating employment, promoting innovation and equitable distribution of resources.
(The author is Dr. Vikas Khare, PhD, M.Tech, MBA, B.E. Associate Professor, STME, NMIMS, INDORE, Certified Data Analyst (IIT MADRAS), Certified Energy Manager- Bureau of Energy Efficiency, India, and the views expressed in this article are his own)
