With AI, applied science companies could:
- Develop their understanding of the cause-and-effect relationships between ingredients and technical or functional performance
- Facilitate assessments of material compatibility and manufacturability
- Speed up new and derivative product development
But what do you need to do to realize the promise of AI? What stands in the way of wider adoption? And how will it actually help your technical teams drive better research and product development outcomes?
Key Learning Objectives:
- The reasons why artificial intelligence is a game changer for research and product development
- The factors that make it so hard to actualize
- Why lab data capture infrastructure is critical to achieving positive outcomes through AI
- How to start, and ultimately scale, your AI initiative
Who Should Watch:
Laboratory Managers | Technical Directors | Product Development Leaders | Research and Innovation Leaders | IT Leaders
