Event Overview
This webinar explores how this technological leap is fundamentally redefining the role of the CDM and moving past the era of the “day-to-day builder” and entering the era of the strategic quality steward. This session will provide a deep dive into how AI-powered workflows are reshaping the way studies are designed, reviewed and launched, setting a new industry benchmark for trial readiness.
Whether you are looking to slash build-to-launch timelines or seeking to elevate your team’s impact, this session will move beyond the AI hype to provide a practical roadmap for implementation. The session will discuss the measurable value this transformation brings to sponsors, CROs and sites, from airtight standardization to radical efficiency gains.
Key Learning Objectives
- How AI agents are solving the technical complexity of modern study builds and eliminating manual bottlenecks.
- Why strategic oversight and governance is the new standard for the modern data manager.
- How AI-driven builds reduce rework, boost compliance and raise expectations across the global clinical landscape.
- Practical strategies for implementation, from establishing new governance models to managing the human side of digital transformation.
Who Should Attend:
This webinar is designed for leaders and practitioners who are navigating the evolution of clinical trial EDC study build. It is particularly relevant for:
- Heads and Directors of: Clinical Operations, Data Management, Clinical Programming, Data Science, and Clinical IT.
- Strategic Leads: CIOs, CTOs, and Heads of Clinical Analytics.
- Study Builders & Data Managers: Professionals currently managing manual builds who are ready to transition into the role of strategic quality stewards.
- Operational Managers: Senior Managers and above responsible for clinical operations, data management, and digital transformation.
Whether you are overseeing a global portfolio or are on the front lines of study building and data management, this session provides the roadmap to move from manual execution to AI-driven oversight.
