In chemicals and advanced materials, simulation and prediction significantly impact downstream value and cost. Today's simulation tools work well until the chemistry gets hard, where performance depends on how electrons interact. Those tend to be the cases that determine whether a product wins. Quantum computing takes on exactly that piece while the rest of your workflow stays where it is. This session moves from concept to concrete use cases, walking through what companies are doing right now, such as screening catalysts before committing to synthesis, evaluating battery and electrolyte materials faster, and using quantum-grade data to make AI models for materials discovery more trustworthy. Each example includes what the technology delivers today, so you leave able to identify promising quantum problems in your own portfolio.