Digitalization is an important aim as organizations seek to improve efficiency through data-driven workflows, reduce the cost of bringing products to market, and accelerate innovation. Digitalization is also the necessary step before data can be leveraged for AI, and even greater productivity.
The goal is clear but the road to digitalization and AI-enablement is fraught with challenges.
Join us to hear from leaders with decades of experience in the digitalization of complex scientific workflows.
You will learn:
- How R&D teams are succeeding with digitalization projects
- Strategies for prioritizing data and workflows
- Key factors to consider for data structuring and management
- Approaches to ensure successful implementation of digitalization projects
- The state of AI-readiness, the possibilities, and potential risks