New regulations, supply disruptions, cost pressure, and sustainability targets keep sending paints and coatings teams back to the bench. Every reformulation is a race. Teams that deliver a validated alternative faster can strengthen customer trust, protect existing business, and win new opportunities.

Join industry leaders and experts for real case studies showing how AI helps R&D teams use existing paint formulation and test data to evaluate alternatives, predict trade-offs, and prioritize experiments. Learn from their experience choosing AI tools, adopting them in everyday R&D, and expanding their use across the organization.

Attendees will learn how to:

• Use historical formulation and test data to identify candidate raw material replacements.
• Predict trade-offs in performance, cost, and processing before running experiments.
• Prioritize experiments to reach a validated formula with fewer iterations.
• Select, adopt, and scale AI in R&D based on real industry experience.

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