After an initial push to learn new AI tools, Zapier's CMO declared the next phase of transformation is not about mastering more technology. Instead, the focus is on fundamentally changing work processes and behaviors to leverage the AI systems, like the central Marketing Brain, that they've already built.

To prepare for a future of human-AI collaboration, technology adoption is not enough. Leaders must actively build AI fluency within their teams by personally engaging with the tools. This hands-on approach models curiosity and confidence, creating a culture where it's safe to experiment, learn, and even fail with new technology.

Shopify's Head of Engineering found that placing an intern who effortlessly uses AI tools on a team prompted senior engineers to adopt the technology. The intern's non-threatening status broke through resistance, leading Shopify to hire 1,000 interns to scale this effect.

To drive AI adoption, CMO Laura Kneebush avoids appointing a single expert and instead makes experimentation "everybody's job." She encourages her team to start by simply playing with AI for personal productivity and hobbies, lowering the barrier to entry and fostering organic learning.

When employees are 'too busy' to learn AI, don't just schedule more training. Instead, identify their most time-consuming task and build a specific AI tool (like a custom GPT) to solve it. This proves AI's value by giving them back time, creating the bandwidth and motivation needed for deeper learning.

To overcome inertia and build confidence, leaders should give every person on their team a specific task to complete using an AI tool. This hands-on, mandated experimentation is more effective than broad directives, as it accelerates learning, builds momentum, and demystifies the technology across the organization.

To encourage widespread use of new AI tools, Qualcomm identifies key people to become 'super users'. As these evangelists demonstrate the tool's value and efficiency, they create a Fear Of Missing Out (FOMO) effect, generating organic demand and pulling the rest of the organization toward adoption rather than pushing it on them.

Instead of explaining AI's potential, show it. Identify the most magical, jaw-dropping internal application of an AI tool and demo it live for your leadership team. This visceral experience is far more effective at driving organizational change than any presentation.

Following an AI "build-a-thon," Zapier's marketing team naturally separated into three skill tiers. Instead of a one-size-fits-all approach, leadership embraced this by creating tailored challenges for each tier. This allows beginners and advanced users to feel a sense of progress and accomplishment.