Artificial intelligence (AI) is redefining how new materials are discovered, designed, and brought to market. Across the chemical and material sciences industries, companies such as Syensqo, Microsoft, NVIDIA, Schrödinger, and Citrine Informatics are demonstrating how AI can accelerate scientific progress and enable more sustainable innovation. During our participation at K2025, we had the privilege of speaking with leading experts from these companies in a panel discussion on the future of AI, and we’re sharing some of their key insights in this article.
At Syensqo, AI already plays a central role in helping scientists uncover new polymers, optimize experiments, and develop next-generation sustainable materials.
Our experiments today are broader, deeper, and faster. These tools are not hypothetical; they are in place today, and they are saving our employees thousands of hours of work.
How AI is transforming chemistry and materials research
Artificial intelligence allows researchers to explore material combinations and chemical reactions at a scale previously impossible. Using advanced modelling, Syensqo scientists can simulate millions of potential polymer formulations, narrowing down the best candidates for real-world testing and reducing time-to-innovation dramatically.
AI is also embedded in our internal systems:
SyGPT, the company’s AI assistant, accessible to all 13,000 employees
SyGrow, a digital “sales buddy” that has helped uncover more than 140 million dollars in new opportunities
Together, these tools show how artificial intelligence in scientific research can free scientists from repetitive tasks and enhance creative problem-solving.
Agentic AI and accelerated discovery
Artificial intelligence is not only changing how we work, but also how discoveries are made. Microsoft’s Discovery Platform, led by Aseem Datar, Vice President of Advanced AI and Quantum at Microsoft, demonstrates the power of what he calls “agentic AI”, intelligent agents working collaboratively to drive faster and more precise R&D outcomes.
For example, Microsoft used AI to design a battery electrolyte using 70 percent less lithium. By modelling 32 million potential material combinations in silico and testing just 18 in the lab, they achieved in weeks what might have taken years through traditional experimentation.
The whole idea is to accelerate and compress scientific discovery so we make it better, faster, cheaper, and efficient.
This kind of AI in chemistry augments human expertise, helping scientists reason, simulate, and predict the best materials for performance and sustainability.
From physics to machine learning
At Schrödinger, AI is being integrated into a long tradition of physics-based simulation. As Andrea Browning, Senior Technical Lead at Schrödinger, explains, by combining quantum-level accuracy with machine learning force fields, Schrödinger can perform high-precision atomistic simulations faster and more efficiently than ever before.
“How well those models understand chemistry,” Andrea notes, “is how well you can design a new material.”
This approach sits at the heart of chemistry and AI innovation, allowing researchers to design new molecules and materials with confidence in their physical validity.
Bridging discovery and manufacturability
For industrial companies, innovation only matters when it can scale. Greg Mulholland, CEO of Citrine Informatics, emphasizes that AI in sustainable materials must also ensure manufacturability and real-world feasibility.
Citrine’s data-driven platform uses real experimental data to guide AI toward materials that can be produced efficiently in existing facilities. This pragmatic approach has already helped improve catalyst design, increasing plant output by around 10 percent while reducing energy use and operational costs.
For Syensqo, this mindset aligns with its goal of turning molecules into meaningful, scalable innovations that advance sustainability.
Sustainable chemistry breakthroughs
Artificial intelligence is driving measurable progress across the materials and chemistry landscape.
Microsoft’s Discovery Platform is accelerating the development of advanced materials, such as battery electrolytes containing 70 percent less lithium, designed in a fraction of the time compared to traditional research.
Citrine Informatics is also using AI-driven models to optimize industrial processes and accelerate innovation, helping companies move from concept to production more efficiently and with lower energy use.
At NVIDIA, Isabel Wilkinson, Solutions Architect, describes how the company’s Alchemy platform brings GPU acceleration to chemistry and materials science. The software enables high-throughput molecular simulations and the use of machine-learned interatomic potentials for faster, more scalable R&D. One early-access partner generated a dataset of 100 million molecules, leading to a new battery electrolyte that doubles energy density, a breakthrough for applications such as drones and robotics.
“You’re using AI to make AI better and more efficient,” says Aseem Datar of Microsoft. “That’s the circular power of intelligent design.”
Each of these examples demonstrates what AI in sustainable materials can achieve - smarter design, better performance, and lower environmental impact.
Looking to the future
As AI systems evolve, their role in material discovery and product design will continue to expand. Industry leaders expect the coming years to bring agentic AI ecosystems, automated laboratories, and data-driven decision-making across chemistry and materials science.
For Syensqo, this means building an ecosystem where AI and scientific expertise work hand in hand to create materials that advance sustainability and improve quality of life.
As Aseem Datar puts it, “Our vision is to compress 250 years of scientific discovery into 25.”
The opportunity for AI extends well beyond discovery; it will be the glue that brings together scientists, product designers, capital facilities, and customer needs.
AI, innovation, and sustainability
At Syensqo, AI is woven into our broader innovation strategy. Every step, from molecular modelling to product scale-up, is guided by sustainability principles, with a focus on reducing carbon footprint, waste, and resource consumption.
By combining AI in chemistry with Syensqo innovation, we’re shaping a future where discovery happens faster, products last longer, and circularity is built in from the start.
Learn more about Syensqo’s commitment to sustainable innovation:
Beyond the lab: collaboration for sustainable innovation
Syensqo’s digital transformation extends beyond the laboratory and into real-world exploration. Through our partnership with UM6P (Mohammed VI Polytechnic University), Syensqo is combining its deep material science expertise with UM6P’s strength in digital technologies and AI to accelerate research in clean energy and advanced materials.
One of the most visionary examples of this collaboration is Climate Impulse, a mission led by explorer Bertrand Piccard and Raphael Dinelli to design and fly a hydrogen-powered aircraft that will circumnavigate the globe with zero emissions. AI plays a key role in supporting the development of new materials and system optimization for this ambitious project.
Together, Syensqo and UM6P are demonstrating how AI, science, and human ingenuity can unite to tackle some of the world’s most pressing challenges, from cleaner mobility to a carbon-neutral future.
