Agentic orchestration: Enterprise AI organizations have a deployment problem, not a platform problem — and most are calling chatbots agents

What changed

Across 101 enterprises, agent orchestration is consolidating onto model-provider platforms — Anthropic’s Claude leads by a wide margin — chosen for the gravity of the underlying model and judged on reliable multi-step execution. Asked whether they plan to adopt a new, additional, or replacement agent orchestration platform in the next twelve months, more respondents are moving here than in any other layer we track. Lock-in is also a new arrival as a top concern.

Why it matters

A concrete addition to Practical AI: Tools, Models & Frameworks: it changes what's available to builders today rather than being general commentary.

How it compares

Related prior coverage to compare against:

• The AI compute gap: Enterprises are buying infrastructure faster than they can measure what it costs
• The agent security gap: 54% of enterprises have already had an AI agent incident, and most still let agents share credentials
• The AI context gap: Enterprise AI organizations have a trust problem, not a retrieval problem — and most are still building the fix

• The AI compute gap: Enterprises are buying infrastructure faster than they can measure what it costs similarity 0.44
• The agent security gap: 54% of enterprises have already had an AI agent incident, and most still let agents share credentials similarity 0.44
• The AI context gap: Enterprise AI organizations have a trust problem, not a retrieval problem — and most are still building the fix similarity 0.42