How AI Orchestration Layers are Functioning Like an OS in the Agentic Era

As enterprises rush to embed AI into their products and workflows, the real competitive edge is no longer about where code is written, which large language model (LLM) is used, or how many agents are deployed. Instead, differentiation increasingly lies in who owns decisions, controls context, and can orchestrate AI reliably within real business systems.

AI orchestration involves coordinating, managing, and automating AI models, data pipelines, and infrastructure.

AI can no longer operate as a collection of tools or isolated agents. Enterprises are now demanding AI systems that run continuously, coordinate workflows across systems, operate under governance, and remain auditable by design.