Mandating AI usage can backfire by creating a threat. A better approach is to create "safe spaces" for exploration. Atlassian runs "AI builders weeks," blocking off synchronous time for cross-functional teams to tinker together. The celebrated outcome is learning, not a finished product, which removes pressure and encourages genuine experimentation.

Uzair Dada, CEO of Iron Horse, dedicates every Friday afternoon to hands-on building with AI tools. This practice of "being patient zero" has spread organically, encouraging his leadership team and company to embrace experimentation and drive tangible innovation from the top down.

To drive adoption, Axios's CEO gave all staff licensed AI access and a simple mandate: spend 10% of your day finding ways it can improve your specific job and share wins. This bottom-up, experimental approach fostered organic adoption and practical use cases more effectively than a top-down directive.

Webflow accelerates AI tool adoption using company-wide "Builder Days." This combines a top-down executive mandate (e.g., "no meetings without a prototype") with bottoms-up enablement, including tool access, support channels, and prizes. The goal is to move the entire organization up the adoption curve, not just early adopters.

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.

Media company Wait What halted all work for three days for an immersive "AI sprint." Every employee formed small teams to build AI-driven solutions for specific business problems. This collective, hands-on approach accelerates adoption and surfaces practical, immediate use cases far more effectively than traditional training.

Instead of mandating specific AI tools, Monumental's CPO fostered a culture of experimentation. He created a Slack channel for sharing discoveries and led by example, encouraging a self-driven, organic adoption process that proved more effective than a top-down mandate.

In the rapidly changing tech landscape, staying current is a core competency. Product managers should formally schedule time each week to experiment with new AI and product tools. This isn't just about learning; it's about developing new instincts and discovering areas for personal specialization.

A non-technical consulting head became an AI power user by dedicating 6-9 AM to 'vibe code'—playful, unstructured experimentation with an engineer. This protected time, free from daily job pressures, was crucial for her learning breakthrough and building a complex AI project manager.