Generative AI initiatives are actively pursued by many organizations, though uneven data foundations present challenges. A survey by Couchbase, involving 619 professionals in product, engineering, data, and AI fields, reveals high confidence and increasing activity in areas like developer productivity, data analysis, and chatbots. However, most enterprises lack a unified data platform, with only 29 percent utilizing a multi-model database for AI, which can hinder innovation as projects scale. While 62 percent of organizations are engaged with GenAI, many rely on a single model, such as ChatGPT, and face concerns about hallucinations and data privacy. Top issues include trust, with 85 percent worried about AI hallucinations and 83 percent concerned about sharing proprietary data with large language models (LLMs). Challenges in privacy, compliance, and data pipeline management are highlighted, suggesting the need for modern NoSQL platforms that unify structured, semi-structured, and unstructured data, enhance governance, and support rapid AI performance. The gap between AI ambition and current reality underscores the potential of NoSQL databases to simplify data management, scale retrieval, and enable organizations to transition from pilots to production-ready AI applications.