Welcome to "The Power of People and AI: Driving Performance Through Experience and Skills." This course is based on a fireside conversation at Transform 2026 between Lars Schmidt, Founder & CEO of Amplify Talent, and Jacqui Canney, Chief People & AI Enablement Officer at ServiceNow. Together, they explored why AI adoption succeeds only when leaders treat it as a people and culture transformation — not a technology deployment. Across three units, you'll practice diagnosing cultural barriers to AI adoption, applying a prioritization rubric to launch high-impact initiatives, and redesigning work around outcomes, skills, and higher-value capacity. Each unit builds on the frameworks and real examples the speakers shared.

Let's start with the conversation's foundational argument: if you treat AI as a tech rollout, you'll miss the biggest change-management moment of your career.

You'll recall that the speakers didn't mince words about where AI implementations actually break down. One put it directly: "successful AI rollouts and introductions often stall at the culture level, not at the technology level." This wasn't a soft observation — it was positioned as the central diagnostic error organizations make. As the conversation underscored, "People will pay a lot of money for tech. They won't get the value" if culture, comfort, and adoption aren't addressed first.

The implication for you as a people leader is critical: when your AI rollout is struggling, your first question shouldn't be Is the tool working? It should be Is the culture ready? The discussion described AI adoption as "the largest change management I've ever seen in my career" and argued that unless this transformation lives in the people lane, organizations will invest heavily and capture almost nothing. That diagnosis — cultural resistance versus fear versus a genuine technology gap — determines whether you need better enablement, more honest communication, or simply a different tool.

Building on that diagnostic, the conversation turned to what leaders should do once they recognize the barrier is human, not technical. When the audience was asked about their own fear around AI, few hands went up — prompting a pointed reminder that leadership confidence often masks widespread employee anxiety. The speakers argued that the goal isn't to ignore this reality, but to manage it: "That’s how you mitigate the fear. We're not trying to remove it."

The speakers argued that mitigating fear means making people's future visible — helping employees "see themselves in the future" by mapping current capabilities to adjacent skills and reinforcing their employability, not just their current job security. As one speaker framed it, this includes "the directness, the responsibility, the employability" — treating candid conversation as an obligation, not a nice-to-have.

And when top-down pressure mounts from boards demanding rapid deployment, the conversation surfaced a critical pushback question: "if you have someone who's pushing and pushing and pushing for capacity, my challenge is what are you going to do with that capacity? What's the end game on that?" Is freed capacity going to build new revenue streams and better service — or is it purely cost-cutting? That single question reframes the conversation from speed to strategy.