Enterprise AI teams are running three orchestration platforms simultaneously, revealing deep distrust in single-vendor solutions for managing AI agents. The median enterprise deploys multiple systems not for redundancy alone, but because existing platforms lack sufficient security, permissioning, and cost control capabilities that companies need to govern autonomous agents safely.
The fragmentation reflects a critical gap: one in five enterprises cannot stop a runaway AI agent's spending in real time. This cost-control blindness exposes companies to financial risk when agents operate autonomously, making spending visibility a top concern alongside safety and security.
Microsoft dominates current primary usage for agentic orchestration, but Anthropic leads significantly in enterprise consideration for future deployments. This divergence between current adoption and intended direction signals enterprises are actively evaluating alternatives to their existing solutions.
Security and permissioning remain the core pain points driving multi-platform strategies. Enterprises don't fully trust vendors to enforce their own governance rules, so they layer multiple orchestration platforms to impose custom security policies independently. Vendor lock-in concerns matter, but they rank behind the fundamental need for direct control over agent behavior and resource consumption.
The data underscores a market reality: orchestration platforms today lack mature governance tooling. Enterprise AI teams want autonomous agents that can operate with minimal human intervention, but only within guardrails they define and monitor themselves. Single-platform solutions haven't delivered that balance convincingly.
This multi-platform approach creates operational complexity. Managing three separate systems requires engineering effort, integration work, and training. Yet enterprises accept this friction rather than depend on a single vendor's security model. The willingness to absorb complexity signals how serious the governance concerns are.
As agentic AI moves from pilots to production, cost metering and real-time spending controls become non-negotiable. The 20 percent of enterprises lacking visibility into agent spending face budget surprises and potential runaway costs. This