Effective AI adoption requires more than just providing tools; it hinges on building AI fluency within teams. GitLab found that a hybrid governance model, balancing centralized standards with decentralized functional strategies, was crucial. Enterprise AI serves as the central hub for standards and security, while AI Transformation Owners embed AI strategy within specific functions. AI Champions within each function promote correct adoption and provide local support. This federated approach ensures speed and control, aligning with the company's principle of Speed with Quality.Crucially, a partnership between Enterprise Technology and Talent Development was essential. They developed the AI Literacy Ladder, a self-assessment tool to tailor learning pathways to individual needs. Engineering pathways focus on practical, day-to-day workflows, building durable judgment rather than just tool proficiency. Hands-on upskilling sessions, including practical labs, significantly increased engineers' reported ability to apply new knowledge. Measuring success involves evaluating reach, depth of engagement, and applied value through feedback and tool usage metrics. The key lessons learned emphasize collaboration, adaptable governance, meeting individuals where they are, treating enablement as a living product, teaching durable judgment, and embracing iterative progress. This comprehensive approach fosters an AI-first culture by equipping team members with the tools and fluency needed to navigate the evolving landscape.