Enterprise AI teams have shifted from relying on a single orchestration platform to running multiple — typically three — to avoid dependency on one vendor and address security and control concerns. Microsoft leads current usage, with Anthropic gaining interest as a next step, but challenges remain in cost visibility and controlling token usage. A survey of 107 enterprises shows 85% use two or more orchestration tools, and 64% use three. Hybrid control planes are expected to grow, with many firms planning platform changes within a year. Enterprises prioritize flexibility, security, reliability, and agent execution control over factors like model alignment or latency. Spending focuses on monitoring, security, and workflow tooling to ensure multi-step task completion rather than just user experience. Control issues persist, with 20% unable to stop excessive AI agent spending in real time, relying on a mix of platform controls, custom middleware, and reactive monitoring. Despite progress, most AI systems are still evolving from basic chatbots to true multi-step autonomous agents, with only a small fraction widely deployed at scale. Enterprises are building infrastructures for future agentic capabilities but are still early in realizing their full potential.
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