An artificial intelligence abstraction layer is a software boundary that presents a consistent interface over changing models, compute services, storage systems and agent runtimes. Applications can use the interface without depending directly on every provider-specific implementation detail.
The layer can make AI systems easier to develop and move between environments, but it also decides which underlying capabilities remain visible. A useful abstraction preserves access to important controls, errors and observability instead of concealing information developers need to operate the system safely.
