On a mission to reduce the environmental impact of manufacturing components, Siemens turned its attention to the design of a robot gripper. Making up just 2% of the robot, the impact of this hand-like device may seem inconsequential. But, reducing its weight by 90% and the number of constituent parts by 84% can save up to 3 tons of carbon dioxide emissions per robot per year. Consider the impact of equivalent savings across every gripper on the more than 4 million industrial robots worldwide—that is quite the step change. To achieve this feat, Siemens used AI-powered generative design tools to autonomously explore possible solutions and rapidly test and optimize them for functionality and manufacturability. “AI and generative AI are fundamentally reshaping how sustainability is integrated into product development,” says Pina Schlombs, sustainability lead and industrial AI thought leader at Siemens. “By enabling smarter design choices, real-time impact assessments, and circular design, these technologies empower businesses to create innovative products that meet both market and environmental demands.” DOWNLOAD THE REPORTAs global carbon emissions reached a record high in 2024, pressure is mounting on companies to reduce their environmental footprint in alignment with the UN’s Sustainable Development Goals. Consumers also increasingly value products that are better for the environment with 80% willing to spend more on sustainably produced goods, according to PWC. And regulations around the world, including the IFRS Sustainability Disclosure Standards, the EU Corporate Sustainability Reporting Directive, and the EU and UK Carbon Border Adjustment Mechanism are increasingly enforcing reporting and incentivizing sustainable production. Download the full report.This content was produced by Insights, the custom content arm of MIT Technology Review. It was not written by MIT Technology Review’s editorial staff.This content was researched, designed, and written entirely by human writers, editors, analysts, and illustrators. This includes the writing of surveys and collection of data for surveys. AI tools that may have been used were limited to secondary production processes that passed thorough human review.