background imageCanva Pro

Smarter, greener, circular: the AI-driven path to sustainability

author image

By Prasanth Warrier

· 4 min read


Every product has a story - from the materials it’s made of, to how it’s used, and finally, how it’s discarded. But what if we could rewrite the end of that story? What if waste wasn’t the finale, but the beginning of something new?

This transformation is happening, powered by the remarkable synergy of Artificial Intelligence (AI) and circular business models. AI helps businesses reimagine how resources are used, products are designed, and waste is managed. Together, they are not only reducing carbon footprints but also creating a more resilient and sustainable future.

Let’s see how:

1. Optimizing resources to reduce waste

AI helps businesses achieve more with less by analyzing vast amounts of data to optimize resource use. For instance, Google reduced energy consumption in its data centers by 40% using AI to manage cooling systems. Supply chain platforms powered by AI are streamlining material flows, cutting down on waste, and recovering resources for reuse.

How you can use this:

• Implement AI-driven energy management systems to lower energy use in production facilities

• Use AI to optimize logistics, cutting transportation emissions

How can you measure success?

Track energy savings (%) and CO2 emissions (tons) avoided in supply chain operations.

2. Designing for a circular future

AI takes product design to a whole new level, enabling durable, repairable, and recyclable products. For example, Siemens uses AI to create modular designs that simplify disassembly and recycling. Philips’ AI-powered "Lighting as a Service" predicts maintenance needs, extending product life and minimizing waste.

How you can use this:

• Leverage AI for sustainable design processes that prioritize longevity and recyclability

• Simulate and test new materials using AI for better durability and sustainability

How can you measure success?

Monitor

• Increase in product lifespan (%)

• Improvement in product recyclability rate (%)

• Reduction in virgin material use (%)

3. Revolutionizing waste management

AI is changing how we handle waste, turning it into a resource rather than a problem. For example, ABB integrates AI with recycling systems to recover valuable materials and reduce landfill waste. AI-driven robotics and computer vision systems sort waste more efficiently, reducing contamination in recycled materials.

How you can use this:

• Adopt AI-powered waste sorting solutions in recycling facilities

• Develop AI algorithms to identify and upcycle valuable materials from waste

How can you measure success?

Measure

• Increase in waste diversion rate (%) 

• Reduction in contamination of recycled materials (%)

• Increase in recovery rate of valuable materials from waste streams (%)

4. Extending product lifecycles with AI

Predictive maintenance, powered by AI, extends product lifespans. For instance, Michelin’s AI-driven tire-as-a-service program optimizes tire usage and maintenance. Cisco uses AI for predictive maintenance and remanufacturing processes, reducing waste.

How you can use this:

• Develop AI-powered predictive maintenance systems for products and equipment

• Create digital twins of products to simulate wear and tear, informing maintenance schedules

How can you measure success?

Measure

• Increase in product lifespan through predictive maintenance (%)

• Reduction in unplanned downtime (%)

• Decrease in replacement part production (%)

5. Creating innovative circular models

AI isn’t just optimizing existing systems; it’s enabling entirely new business models. For example, TerraCycle’s innovative approach to recycling hard-to-recycle materials could be further enhanced with AI integration. AI platforms match suppliers with underutilized resources to potential buyers, creating new revenue streams.

How you can use this:

• Build AI-powered platforms to enable resource-sharing networks or product-as-a-service offerings

• Analyze customer behavior and preferences with AI to tailor circular solutions

How can you measure success?

Monitor

• Increase in resource utilization rate (%)

• Growth in circular revenue streams (%)

• Customer adoption rate of circular offerings (%)

The Future of AI and circular economies

AI is more than just a tool - it’s a catalyst for a greener, more sustainable world. By weaving AI into circular business models, companies can reduce their environmental impact, save costs, and create innovative new revenue opportunities.

This article is also published on LinkedIn. illuminem Voices is a democratic space presenting the thoughts and opinions of leading Sustainability & Energy writers, their opinions do not necessarily represent those of illuminem.

Did you enjoy this illuminem voice? Support us by sharing this article!
author photo

About the author

Prasanth Warrier is Head of Strategic Sourcing & Trading at JTC, where he manages significant spending and equipment trading across multiple regions. With over 25 years of experience in sales, business development, and supply chain management, Prasanth has held progressive leadership roles across manufacturing, industrial, and heavy machinery sectors, and is a specialist in driving sustainable transformations and profitability.

Other illuminem Voices


Related Posts


You cannot miss it!

Weekly. Free. Your Top 10 Sustainability & Energy Posts.

You can unsubscribe at any time (read our privacy policy)