Poor data ownership and quality prevent companies from scaling AI deployments. Many firms prioritize flashy tools over the foundational governance required for reliable outputs. This gap creates a ceiling for LLM utility in production. Practitioners must fix fragmented data pipelines before investing in more complex AI agents or custom models.