In this episode, Siobhan Savage sits down with Sandra Loughlin, Chief Learning Scientist at EPAM Systems, to explore how enterprises redesign workforce architecture for the AI era.
AI transformation requires moving beyond static job structures. Organizations need to understand work at the task level to align learning, execution, and outcomes.
This conversation focuses on how workforce architecture evolves. Sandra shares how enterprises shift from skills-based models to task-based approaches, redesign learning strategies, and integrate AI into how work is performed. The discussion highlights practical ways to connect capability building with real execution.
In this episode, you’ll learn:
Why workforce architectures must evolve for AIHow task-based models improve executionWhat role learning plays in workforce redesignHow enterprises align skills, work, and AIWhat it takes to modernize workforce strategySandra Loughlin is Chief Learning Scientist at EPAM Systems, where she focuses on workforce transformation, learning innovation, and AI-driven strategy.
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