Shifts in how talent operates: –Learning moves from episodic to continuous, AI-embedded capability-building tied directly to work. –AI captures tacit and frontline knowledge from real work, converting it into reusable, system- wide guidance embedded in workflows. –Personalized learning pathways align with capability gaps, demand forecasts and real work requirements. –Retention shifts from standalone programmes to an adaptive system linked to career progression, capability growth and predictive risk signals. –Agents surface the right checklist, template, example or expert, capture what works and escalate complex cases to humans. Organizational changes observed: –Learning systems are integrated with workflow tools and capability maps, not segregated learning management systems (LMS) platforms. –AI is used to anticipate future skill needs and adapt development pathways proactively. –Retention strategies are aligned with capability evolution and employee growth journeys. –Organizations invest in systematically capturing, structuring and reusing institutional and frontline knowledge. –Establish collaboration with intelligent agents as foundational workforce skills, not specialist capabilities limited to technical roles. Early vs advanced adopters: –Early: Deliver AI-personalized learning recommendations for targeted roles. –Advanced: Build enterprise-wide adaptive capability pipelines that support continuous reskilling, redeployment and retention at scale. AI shifts talent and workforce planning from a role-based HR function to a continuous capability system that aligns human and digital capacity with evolving work and priorities. Leading organizations treat talent as a strategic execution asset, building skills ahead of demand, redeploying capabilities fluidly and adapting continuously.5.4 From fragmented learning to continuous upskilling, reskilling and adaptive retentionCASE STUDY 25 Redesigning organization for the agentic AI era Moderna combined its HR and IT functions under a single Chief People and Digital Technology Officer. The company redesigns teams around “what work should be done by humans versus AI tools”, deploying thousands of custom generative pre-trained transformers (GPTs) across business functions to automate routine tasks and elevate human judgement. This integrated model accelerates AI adoption, improves workflow design and ensures decisions about people and technology are made in concert.49 Organizational Transformation in the Age of AI: How Organizations Maximize AI’s Potential 35

Organizational Transformation in the Age of AI How Organizations Maximize AI%27s Potential 2026