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.

Instead of relying solely on top-down, consultant-led workflow automation, enterprises should empower individual employees with AI tools. This builds user fluency and intuition, allowing them to pull AI into their own workflows, resulting in greater overall impact and less disempowerment.

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.

The most successful companies deploying AI use a "leadership lab and crowd" model. Leadership provides clear direction, while the entire organization is given access to tools to experiment and discover novel use cases. An internal team then harvests these grassroots ideas for strategic implementation.

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.

Effective AI adoption requires a three-part structure. 'Leadership' sets the vision and incentives. The 'Crowd' (all employees) experiments with AI tools in their own workflows. The 'Lab' (a dedicated internal team, not just IT) refines and scales the best ideas that emerge from the crowd.

AI agent platforms are typically priced by usage, not seats, making initial costs low. Instead of a top-down mandate for one tool, leaders should encourage teams to expense and experiment with several options. The best solution for the team will emerge organically through use.

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.

Instead of picking a single AI tool "winner" for internal use, Canva intentionally gives its teams access to a wide array of models and platforms. This encourages constant experimentation and upskilling, ensuring the company's talent adapts quickly to the fast-changing AI landscape.