CoBooster: How Can AI Be Put to Practical Use in R&D?
On September 1, 2026, Sylvac in Yverdon-les-Bains will host a new CoBooster event dedicated to the practical integration of artificial intelligence into research and development. Organized in collaboration with Sylvac, AI Swiss, and several partners from the innovation ecosystem, this half-day event will bring together companies, experts, and academics to address a question that has become central to R&D teams: How can we move beyond initial experiments with AI to truly integrate it into innovation processes?
New Digital Tools to Accelerate and Rethink R&D
Beyond generative AI and its most visible applications, the event will explore its integration into all aspects of the innovation process: technology research and sourcing, intellectual property, product development, automation using AI agents, and collaboration between human and artificial intelligence.
A deliberately cross-functional approach that will also address the organizational and human aspects essential for moving from experimentation to practices that are truly integrated into R&D activities.
Among the presentations that will highlight these various issues, you'll have the opportunity to explore topics such as:
- AI in R&D and Collaborative Innovation: Key IP Considerations with Adrien Marcone, European and Swiss Patent Attorney at P&TS
- "How AI Is Reshaping Discovery, Development, and Decision-Making " with Cristina Apetrei, Director of Innovation Execution & Strategic Projects; Cosmin Cioroiu, Director of New Business, Commercial Innovation Ecosystem; and Bo Jiang, Principal Scientist in Electronics Innovation at Philip Morris International
- AI Solution for Technology Sourcing and Procurement with Nicolas Souvlakis, Managing Partner for Europe at Embiggen X
- Beyond the Tools: Leading Responsible AI Adoption in R&D with Vincent Nassar, CEO of IntoFlow
For SMEs in French-speaking Switzerland, this event offers an opportunity to move beyond an AI approach focused solely on tools and to consider how to integrate AI into their entire innovation chain. The various case studies will help identify concrete use cases, as well as provide a better understanding of the intellectual property, organizational, and human-machine collaboration issues that accompany their deployment. This is a way to better determine where AI can truly add value to R&D and how to gradually transition from experimentation to integrated practices tailored to business needs.
