•    Democratizing AI Experimentation: How decentralized innovation frameworks enable frontline teams to identify high-impact use cases that corporate-level initiatives might overlook, creating a diversified portfolio of AI applications tailored to real operational needs
•    Accelerated Proof-of-Concept Cycles: Leveraging domain expertise of specialized teams to rapidly prototype, test, and iterate AI solutions in controlled environments before investing in enterprise-wide implementation
•    Cross-Pollination of Success Stories: Establishing internal communities of practice where teams share implementation insights, failure points, and unexpected benefits from AI experiments to build collective organizational intelligence
•    Scalability Assessment Framework: Developing systematic evaluation criteria to identify which team-level AI successes contain the transferable elements and ROI potential to warrant broader deployment across operational units