AI Accelerates Progress Towards a More Sustainable Industry | Microsoft generative ai course | Generative ai tools list | | Turtles AI

AI is emerging as a key driver of innovation in the energy sector, driving efficiency and contributing to global sustainability goals.

Key Points:

• AI is transforming energy systems, improving efficiency and reducing carbon emissions.
• In China, AI is being applied to optimize carbon-intensive industrial processes, such as chemicals.
• The Chem-ELLM 2.0 model represents a significant advancement in AI-based chemical engineering
• Global initiatives are promoting the use of digital technologies to address environmental and social challenges.

At the 2025 Zhongguancun Forum, experts highlighted the role of AI and digital technologies in accelerating the greening of industry and promoting sustainable development globally. At the Carbon Peak and Carbon Neutrality Science and Technology Forum, Ding Chibiao, vice president of the Chinese Academy of Sciences, highlighted how AI is redefining energy systems and supporting China’s carbon emission reduction goals. He said AI is key to innovation in future energy structures, driving transitions to greener solutions. China aims to achieve peak carbon emissions before 2030 and carbon neutrality before 2060.

Ding noted that AI adoption has already improved efficiency in carbon-intensive sectors such as the chemical industry, in line with the Academy of Science and Technology’s strategic plan to support peaking and carbon neutrality goals released in 2022. He promised deeper interdisciplinary collaboration to promote AI-based low-carbon energy solutions

Ye Mao, a researcher at the Dalian Institute of Chemical Physics and leader of the Academy’s intelligent chemical engineering team, detailed the progress in AI-based chemical engineering. Since 2016, a team led by Liu Zhongmin, director of the institute and academician at the Chinese Academy of Engineering, has been developing AI applications in the industry. Last year, they launched Chem-ELLM, an advanced model for autonomous chemical process design, followed by Chem-ELLM 2.0 in November. The new version significantly improves capabilities in catalysis, safety, and basic chemistry, broadening industrial applicability. More than 50 chemical companies have tested the model, with adoption growing. Ye emphasized that traditional engineering and AI-human collaboration will continue during this transition. He said that building a smart chemical ecosystem takes time, but it will increase efficiency, safety, and support China’s energy transition.

At the International Forum on Science for Sustainable Development, part of UNESCO’s International Decade of Science for Sustainable Development (2024-2033), global experts examined the role of digital technology in achieving the United Nations 2030 Agenda for Sustainable Development. Guo Huadong, an academician at the Chinese Academy of Sciences and director of the International Research Center of Big Data for Sustainable Development Goals, introduced the Beijing Initiative on Digital Science and Technology for Sustainable Development. The plan calls for expanding the use of AI, big data, the Internet of Things, and space technology to address climate change, biodiversity loss, and poverty. Guo stressed that digital tools are essential to optimizing energy use, reducing emissions, and improving resource management. The initiative also promotes global platforms for sharing digital resources, integrating technology into decision-making, and increasing public literacy on sustainability. He highlighted China’s contributions, citing SDGSAT-1, the world’s first science satellite dedicated to the 2030 Agenda, which has provided more than 420,000 datasets to 104 countries since its launch in 2021. This data helps monitor urban heat islands, assess emissions, and respond to disasters.

The integration of AI and digital technologies is driving innovation in the energy and chemical sectors, contributing significantly to global efforts for sustainable development.