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We recently had the privilege of spending several days amongst coatings formulators, manufacturers, suppliers, and leaders at the Coatings Trends and Technologies Summit hosted by Paints and Coatings Industry (PCI) Magazine. From the presentations we attended to conversations at our booth, it was clear that the coatings industry has a strong interest in digitalization and AI – not just for accelerating R&D, but also to influence commercial strategy.

Our COO and cofounder Ken Kisner joined the first day’s keynote panel on real-world examples of AI for coatings, and our Director of Solutions Architecture Jon Weis, PhD took the stage on day two to share customer case studies and our philosophy around digital transformation.

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From theory to practice

The keynote panel, “Real-World Successes in AI-Enabled Coatings Innovation,” was moderated by PCI’s Kristin Johansson and featured leaders from across the industry: Paul Snowwhite (Applied Molecules), Alex Gardiner (Proleit by Schneider Electric), Dheev Arulmani (Valdera), Bryan Haltom (DyStar), and Ken Kisner (Albert Invent).

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After years of talking about AI to surface knowledge, preserve institutional expertise, and move faster in the coatings industry, this panel proved that we’re at an exciting tipping point where we can share tangible wins. There was also a call-to-action for organizations to begin digitalizing as soon as possible – after all, every day of delay means your organization’s latest experiments and most up-to-date knowledge isn’t AI-ready.

AI in action

Each panelist shared real-world examples of AI in practice:

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• Dystar built a custom GPT to help synthesis chemists overcome a dead end and design creative new chemistries for defoamer.

• Proleit by Schneider Electric’s AI-powered tinting assistant links wet sample data to final cured properties, eliminating manual curing steps and boosting productivity by 11%.

• Applied Molecules uses Breakthrough, Albert’s suite of AI/ML tools trained on 15 million molecules, to optimize formulation based on target properties. “AI is like an Ironman suit,” described Paul. “It doesn’t replace scientists, but it gives them the tools to do science better – and as they feed in more data they keep getting better results.”

• Valdera shared their work on applying AI to sourcing chemicals and raw materials, from identifying suppliers for new product development to supporting supply chain agility during full scale production.

But digitalizing R&D isn’t easy: for most panelists, change management was just as much of a driver as the technology itself, and it required wins with clear business value to get the ball rolling and internal champions to keep up the momentum.

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Data security was also a shared concern, with discussions surrounding how to ensure your proprietary data isn’t training a public model and how to handle the flow of digital information with a supplier who could also be a competitor. Ken spoke to Albert’s multi-layered security, as well as how our granular access control enabled Nouryon to selectively share public information for their AI-driven sales portal, BeautyCreations.