Sally Paull
Strategic Advisor, most recently Executive Vice President of Human Resources Regeneron Pharmaceuticals
Seminars
Wednesday 2nd December 2026
Interactive Panel Discussion: Reflecting on the State of Play of Building an AI-Enabled Workforce in the Life Sciences Industry
8:30 am
- What do leading life sciences organizations have in terms of AI capability building that is paving a path forward for designing the AI-enabled workforce?
- What people resources and capabilities are we lacking at life sciences organizations in an AI era and how can we plug those gaps?
- When evaluating people, process, technology, and governance, how does the life sciences industry compare to other sectors in terms of AI-readiness?
- How mature are we from a workforce adoption perspective?
- Using a 7S framework (Strategy, Structure, Systems, Shared Values, Style, Staff and Skills), to what extent is AI and technology progress ahead of the skills mix and leadership behaviors in the life sciences industry? What action can we take to close the gap?
Thursday 3rd December 2026
Action Lab A: What Are the Implications of Redesigned Work on Roles, Capabilities, & Org Design Across the R&D Value Chain to Drive Innovation?
10:50 am
- What new skills and capabilities will be needed as AI reshapes work across the R&D value chain (namely across discovery, clinical and CMC/operational functions)?
- How should organizations approach upskilling, reskilling, and workforce planning where domainspecific, scientific or technical expertise remains critical?
- What role-specific capability gaps must be addressed to enable effective human-AI collaboration and accelerate innovation in these functions specifically?
Thursday 3rd December 2026
Action Lab D: How Can Organizations Reverse-Engineer Roles Based on Tasks that Will Be Automated Versus Skills Requiring Human Judgement?
1:20 pm
- As AI automates more task-based work, how should organizations deconstruct and rebuild roles around uniquely human capabilities such as judgement, decision-making, creative problem-solving, and scientific expertise?
- What does the future organizational matrix look like in an AI-enabled life sciences enterprise, and how will responsibilities be shared between people, agents, and cross-functional teams?
- How should learning and capability strategies evolve to balance broad AI fluency across the workforce with the deep domain expertise required to unlock value from specialized AI tools?
