AI is everywhere in the materials industry - hailed by some as transformative, dismissed by others as overhyped. The reality sits in between.

When applied strategically, AI can accelerate materials innovation by synthesizing complex datasets, recommending formulations, predicting performance, and enabling truly agile R&D. The challenge isn’t whether to use AI - it’s knowing which tools to use, when, and how to apply them effectively.

This interactive session will cut through the noise and focus on practical application. We’ll explore the roles of Generative AI, Analytical AI, and Statistical Modeling - and how each fits into real-world materials development workflows.

What you’ll gain:

· A clear understanding of Generative AI, Analytical AI, and Statistical Modeling - and when to use each

· A walkthrough of a real-world materials R&D use case

· Insight into the minimum data and technical requirements needed to successfully implement AI

· Practical guidance on accelerating R&D timelines using AI-driven approaches

· The opportunity to ask questions across the full AI journey - from getting started to integrating multiple approaches (e.g., combining GenAI with DOE)