Water scarcity is no longer merely an environmental issue, but…

Artificial Intelligence “AlphaFold” Achieves Scientific Breakthroughs
Google DeepMind is an example of an AI company that aims to take on responsibility. It was formed through the merger of two AI labs, “Google Brain” and “DeepMind.” An interdisciplinary team of scientists, engineers, and ethicists is developing the AI “AlphaFold”, which, among other things, was able to solve a 50-year-old puzzle.
AlphaFold: AI Saves Researchers Millions of Years of Research
The so-called “protein folding problem” has been a challenge for scientists for over half a century. Proteins—the building blocks of life—consist of complex 3D structures. Until now, deciphering these proteins took several years and cost hundreds of thousands of dollars.
In 2020, AlphaFold changed all that: The system can now predict the structure of proteins within minutes with remarkable accuracy. Today, over two million researchers in more than 190 countries use the “AlphaFold Protein Structure Database.” As a result, AI has already saved hundreds of millions of years in research time, which scientists can now devote to solving medical and environmental problems.
But AlphaFold is not just a theoretical model; it is a tool for real-world progress, for example in the fields of
- Medicine: Researchers were able to develop a malaria vaccine by gaining a precise understanding of how the parasite interacts with human proteins. The system is also providing crucial assistance in research on heart disease.
- Agriculture: To help farmers adapt to climate change, AlphaFold is assisting in the development of heat-resistant crops. Through molecular simulations, enzymes are modified so that plants can survive even as temperatures rise.
- Environment: 91% of all plastic ever produced has never been recycled. To tackle this plastic crisis, “plastic-eating” enzymes have been identified. They can break down plastic into its original polymers, thereby enabling 100% recycling.
AI with a Commitment to Sustainability and Responsibility
Google DeepMind is committed to Google’s AI principles: innovation, responsibility, and collaboration. This is also reflected in its use of resources: According to its 2025 Environmental Report, Google pursues a “full-stack” approach, in which efficiency guides every level of the development process—from chip design to the optimization of AI models. In this way, the company minimizes its environmental footprint. Nevertheless, the report’s focus is on the use of AI as an opportunity for economic growth and social progress. Sustainability appears to be secondary.
Energy and Water
- Energy: Google recognizes the high energy demands of its global infrastructure and is investing heavily in “clean” energy. However, it is not clear what proportion of this comes from nuclear versus renewable energy sources. AI-optimized scaling will reduce data center emissions by 12% between 2023 and 2024.
- Water: We need to manage responsibly the large volumes of cooling water that protect data centers from overheating. The majority (72%) of the freshwater required comes from regions where there is no risk of water scarcity. Google has set a goal to return more water to nature than the company withdraws. In 2024, 4.5 billion gallons of water were returned to nature.
Google DeepMind aims to use AI to solve the most difficult scientific and practical challenges. In the spirit of “AI for Good,” AI as a technology can contribute to a future worth living: curing diseases, combating climate change, and preserving the Earth’s resources.
Cover photo: CC Alex Shuper, Unsplash ; edited by Tina Teucher Team
Tina Teucher is a speaker and moderator specializing in sustainable business. In her keynote speeches and moderation sessions, she inspires audiences with her insights into the intersection of artificial intelligence, the circular economy, and megatrends, and highlights the opportunities presented by an ecological transformation. As a co-founder of startups, she brings her practical business management experience to the stage.