The current landscape of semantic layers in data management is fragmented, with numerous competing standards leading to forced compromises, lock-in, and inefficient APIs. As LLMs evolve, they may redefine the use of semantic layers, promoting more flexible applications despite the existing challenges of interoperability and profit-driven designs among vendors. A push for a universal standard remains hindered by the lack of incentives to prioritize compatibility across different data systems.

A semantic model enhances consistency in business logic across various BI and AI tools by centralizing definitions and improving interoperability. The Open Semantic Interchange (OSI) initiative, led by Snowflake and partners like Select Star, aims to standardize semantic metadata, allowing for seamless integration and improved data management. By using a governed semantic layer, organizations can achieve reliable metrics, reduce migration costs, and accelerate analytics adoption.