Many organizations have started using artificial intelligence (AI), but far fewer have built the workforce capability to make it work at scale. Problems often show up after the pilot phase: teams have tools, use cases and executive interest, but not the role-based skills, workflows or change support needed to turn AI investment into measurable performance.

In this webinar, LearnQuest managing director, Dimitri Schneiberg, examines why most AI initiatives stall after early adoption and what organizations must change internally to turn AI investment into real operational performance. Schneiberg will share a clear framework for aligning AI initiatives with workforce readiness, role-based capability development and scalable execution. Attendees will leave with a stronger understanding of why AI strategies fail and what leading organizations are doing differently to close the gap between adoption and impact.

This interactive webinar will provide easy-to-understand insights on:

• Identifying the organizational gaps that prevent AI initiatives from moving beyond experimentation into scalable operational use
• Applying a practical framework for aligning AI workforce capability with real business workflows and performance goals
• Recognizing the warning signs of “capability debt” and understanding how it impacts AI adoption, productivity and execution
• Evaluating what separates organizations successfully operationalizing AI from those struggling to generate measurable business outcomes