There's unprecedented industry buzz around generative AI, but for companies trying to deploy it, there are several key challenges. Most companies are still working on building the necessary blocks, and many are struggling with data quality and governance. The hardest part of AI is often the data, and companies need to carefully consider whether their use case would be better served by simpler predictive modeling or heuristics. To overcome these challenges, companies like Databricks and Fivetran are offering solutions such as retrieval augmented generation (RAG) that can help ensure factual and relevant outputs from generative AI models. By addressing data ownership, governance, and quality control, companies can unlock the full potential of generative AI and bring business value to their operations.