Centralized datasets impose rigid constraints on AI systems, preventing them from adapting to shifting real‑world conditions. Decentralized data infrastructure offers a different path—by distributing data collection across networks, AI models gain the flexibility to continuously learn and align with evolving market dynamics and user behaviors. This approach transforms how intelligent systems respond to change.