The piece also explores emerging trends such as the use of vector embeddings and retrieval-augmented generation (RAG) in AI, which are expected to drive innovation in data handling. The introduction of GraphRAG, which combines knowledge graphs with RAG, is seen as a significant development that could enhance business intelligence by providing more context and reducing computational demands. The article suggests that while dramatic technological revolutions in data management are unlikely, the focus will be on improving existing solutions and breaking down silos within organizations to better leverage data for AI applications.
Key takeaways:
- Generative AI dominated discussions in 2024, but 2025 is expected to be the year data regains prominence as enterprises move beyond proof-of-concept stages.
- Data governance and AI governance are expected to converge, with a focus on improving data quality, privacy, security, and compliance.
- Retrieval-augmented generation (RAG) and GraphRAG are anticipated to become common practices, enhancing the integration of structured and unstructured data for AI applications.
- The importance of data management, integration, and governance will be emphasized, with existing technologies being leveraged to support AI-driven transformations.