A study predicts AI-related e-waste could grow from 2,600 tonnes in 2023 to 2.5 million tonnes by 2030, potentially reaching 1.2 to 5 million tonnes cumulatively between 2020 and 2030. North America is expected to produce the majority, followed by East Asia and Europe. US restrictions on GPU sales to China may exacerbate the issue. Researchers propose a circular economy strategy to potentially reduce AI-related e-waste by 86% globally, including extending hardware lifespan, reusing components, and improving computing efficiency.

**For tech companies and data centers:** You'll face increasing pressure to address e-waste concerns. Consider implementing circular economy strategies now to get ahead of regulations and public sentiment. This may involve redesigning products for longer lifespans and easier component reuse. **For electronics manufacturers:** Prepare for a surge in demand for AI-specific hardware. You'll need to balance performance improvements with sustainability concerns. Explore modular designs that allow for easier upgrades and repairs. **For all businesses:** Evaluate your AI infrastructure plans. The environmental impact of AI could become a reputational risk. Start factoring e-waste into your AI strategy and consider cloud solutions that may offer better hardware utilization.

Expect a regulatory push towards circular economy practices in the tech sector. This could lead to new business models focused on hardware-as-a-service, refurbishment, and specialized recycling. The geopolitical tensions around AI hardware could create supply chain disruptions. You may need to diversify your AI infrastructure providers or explore alternative computing solutions. Look for innovations in energy-efficient AI algorithms and specialized AI chips. These could offer competitive advantages in both performance and sustainability. Anticipate growing customer and investor scrutiny of your company's AI-related environmental impact. Prepare to report on and improve your AI hardware lifecycle management.