Most AI training programs are built the wrong way. They teach people about AI through static elearning and then expect them to use AI effectively in dynamic workflows. The result is low adoption, surface-level usage, and learning investments that fail to improve performance.
Using Golin’s global AI transformation as a live case study, this session explores how a 1,700-person communications agency increased AI adoption from 15% to more than 90% in 18 months by rethinking its instructional design approach. You will examine the learning architecture behind those results, including role-specific pathways, expert-led microlearning, a globally scaled AI mentoring program, and adoption metrics tied to business outcomes.
Drawing on additional lessons from AI upskilling efforts across 115,000 employees at Publicis Groupe, Joe Leslie will share the strategic frameworks and instructional models that supported these initiatives, including a problem-first methodology centered on real workplace challenges.
By the end of this session, you will be able to
- Apply a problem-first framework to AI training design.
- Build role-specific AI learning pathways.
- Evaluate AI training using adoption and performance metrics.
