Companies warned about AI semantic lock-in when buying analytics platforms

The author argues that companies evaluating AI analytics platforms must look beyond data migration and consider risks associated with semantic model lock-in, agent interoperability, model optionality, and workflow portability. Platforms that encode business definitions and instructions in proprietary systems make it expensive to switch tools as technology evolves. To maintain flexibility, organizations should prioritize open semantic standards, portable context, and inspectable code. Open article →