Strong data systems, governance, and careful use of AI allow Lenovo to scale circular supply chains while maintaining oversight. It shows how structure and technology together can make sustainability practical, not just aspirational.
Efforts to make supply chains more sustainable often focus on single initiatives—like switching to recycled materials or cutting carbon during shipping. But lasting change usually depends on how well these actions are built into the daily operations of a company. Lenovo’s approach shows how circular design, AI, and clear governance can work together to scale sustainable practices across global supply chains.
Designing for circularity from the start
Lenovo’s sustainability efforts don’t begin at the end of a product’s life—they start during product design. Circular principles are built into material choices, packaging, and serviceability, making it easier to repair and refurbish devices later on. The company has integrated recycled materials into hundreds of product lines and uses plant-based packaging, such as bamboo and sugarcane, across many of them.
“We build circularity in from the very beginning: starting with product design, selecting sustainable materials, reducing the carbon footprint during manufacturing, selling through our channels, and then taking back and refurbishing products for resale through SSG,” said Jammi Tu, Senior Vice President and Group Operations Officer at Lenovo.
This end-to-end model allows Lenovo to manage every step of the circular process internally. Refurbished products are collected, sanitised, and resold through Lenovo’s Solutions and Services Group. It’s a strategy that blends commercial goals with sustainability targets, creating a loop rather than a straight line from production to disposal.
Scaling circular innovation across markets
The company’s Asset Recovery Services now operate in 43 markets, with plans to expand to around 50. These services handle roughly one million devices each year. Scaling this kind of program isn’t simple. It involves setting up reverse logistics systems, meeting different regulatory requirements, and ensuring data is securely wiped from returned devices.
Tu explained that the challenge isn’t just about expanding capacity. It’s about making sure every part of the system is connected so the circular model can grow without losing control. “The real challenge is ensuring that this business continues to grow while still meeting our mission to reduce our global carbon footprint. That’s where end-to-end connectivity becomes critical,” he said.
To manage this, Lenovo uses AI to track carbon emissions through its Intelligent Sustainability Solutions Advisor (LISSA). This tool calculates the carbon footprint for each PC produced, helping enterprise customers make informed decisions about their purchases. By combining AI with sustainability reporting, the company can scale its circular programs while maintaining accountability.
AI’s role in oversight and trust
Lenovo’s use of AI goes beyond carbon accounting. Over the past seven to eight years, it has steadily built AI capabilities into its supply chain operations. Two years ago, it shifted from traditional AI to agentic AI systems that offer more autonomous support, though human oversight remains essential.
Tu described this as a structured process that relies on close collaboration between security, technology, and information leaders. “To adopt AI capabilities effectively, we work very closely with our Chief Security Officer, Chief Technology Officer, and Chief Information Officer. Together, we ensure full visibility, meet security requirements, choose the right architecture, and minimise risks,” he said.
Strong monitoring systems check the accuracy of AI outputs, and checkpoints across manufacturing and logistics prevent errors from spreading through operations. This balance between automation and human review is key to maintaining trust in AI-driven decision-making.
Why most AI efforts fall short
Many companies have started experimenting with AI in their supply chains, but few have moved beyond pilot projects. Tu pointed out three essentials that separate success from failure: knowledge and data, organisation and governance, and infrastructure.
“It’s not just data volume but structured, retained knowledge. If knowledge walks out the door with people, AI won’t succeed,” he said. Clear ownership and security are also critical. At Lenovo, the CIO and CTO play central roles in ensuring infrastructure and governance are solid before scaling new tools.
This long history with data and governance gave Lenovo an advantage during the pandemic. When supply chains worldwide were disrupted, the company was able to keep shipments flowing by identifying bottlenecks across both tier-one and tier-two suppliers. This visibility allowed it to convert available parts into finished products while keeping inventory lean.
A connected approach to sustainability
Circular design, reverse logistics, AI, and governance may seem like separate strategies, but Lenovo’s example shows they are closely linked. Circularity depends on good data. Data depends on governance. And AI works best when both are strong. By connecting these elements, sustainable practices can scale across complex global networks without becoming isolated pilot projects.
For other companies, the lesson is that sustainability is not a side program. It has to be designed into products, built into operations, and supported by the right technology and oversight. That’s how a circular supply chain becomes not just possible, but practical.
(Photo by Bernd đź“· Dittrich)
Want to learn more about Data Centres from industry leaders? Check out Data Centre Congress taking place in Amsterdam, California, and London. The comprehensive event is part of TechEx and co-located with other leading technology events. Click here for more information.
