Artificial intelligence is one of the biggest topics in business right now, and solar is no exception. The narrative around AI in solar is largely focused on the increased demand for power from hyperscalers and data center operators, seeking to power their operations with reliable, clean power. And for good reason – according to the International Energy Agency, data centers accounted for approximately 50% of all U.S. electricity demand growth in 2025, more than residential, industrial, or transportation sectors combined.
We’re following this trend closely, particularly as we partner with hyperscalers and AI and digital infrastructure providers to support their end-of-life asset management needs. But we have also been exploring how AI can help solve problems in solar circularity, from evaluating used panels to improving how materials are recognized and recovered. In practice, that means asking a simple question: where can better intelligence help preserve more value?
Three of our AI-related patent applications are now public. Taken together, they reflect how we think about AI across the recycling system. At SOLARCYCLE, we use AI to help us evaluate incoming modules and determine the right path forward; recognize what’s happening after key processing steps; and classify and sort recovered materials based on their properties.
Not every retired solar panel needs to follow the same path. Some still have enough life left for a second use. Some may be better suited for refurbishment. Others should move directly into recycling. Those are important decisions because the circular economy works best when value is preserved for as long as possible, not when everything is treated the same way from the start. This is particularly important for large asset owners that are repowering aging systems with newer technology to increase energy output, but have large volumes of decommissioned panels that, while older, still have life to give.
We have a proprietary AI model to help us assess which panels can be reused. The model helped us recover more than 1,000 used panels and build a 500 kW power plant at our Texas facility. Projects like that are a reminder that circularity is not only about recovering raw materials at the end. It is also about understanding when a panel still has useful life left and making the right call about what should happen next.
After a panel is evaluated for recycling and reaches our facilities, AI continues to play a role. We have AI technology that enables close monitoring and real-time learning from what is happening during processing. Our model allows us to see whether separation steps are working well, spot when materials are ending up where they should not, and identify where a process can be improved. It serves not as a substitute for engineering, but as an additional layer of intelligence that helps us understand a complex system more clearly.
That matters because solar recycling is not a simple task. Panels come in different designs, conditions, and material combinations. Once they enter a recycling process, the challenge is not just to move them through equipment, but to make good decisions throughout the process so that more value can be recovered in a reliable and scalable way.
Finally, AI can help us recognize and sort the various materials and ensure they are pure enough to be useful downstream. Mixed material streams have limited value. Distinct streams of glass, metals, and semiconductor material are much more valuable. Better recognition supports better separation, and better separation supports better recovery.
AI will not solve solar recycling. This is still a young industry, and there is no shortcut around the hard work of process development, testing, materials science, and operational discipline. But AI can become an important part of how a modern solar recycling platform gets better over time.
In our view, AI only matters if it improves real outcomes. In solar circularity, that means better decisions about modules, better visibility into process performance, and better recovery of valuable materials. It is not about adding a label to familiar processes. It is about building a more capable system.
The solar industry has spent decades improving how panels are designed, manufactured, and deployed. That work helped make solar one of the most important energy technologies in the world. The next challenge is to bring the same sophistication to what happens when those panels reach the end of one life and the beginning of the next.
At SOLARCYCLE, we believe recycling should be treated as a technology challenge, not just a waste-management task, and that the companies defining the future of solar circularity will be the ones willing to build smarter systems, test new ideas, and keep improving how value is preserved across the full life of a panel. That is the role we see for AI. AI is not the mission; better circularity is. But if AI helps us build a smarter, more effective, and more valuable system for recovering materials from retired solar panels, then it is more than just a buzzword, it is part of the future of solar recycling infrastructure.
