Enterprise AI teams are now deploying three orchestration platforms on average rather than trusting a single vendor, according to new research.
The shift reflects widespread concerns about security, permissioning, and cost control—with one in five enterprises unable to stop an AI agent's spending in real time.
While Microsoft leads current usage and Anthropic leads in enterprise consideration for next deployments, the real issue is that no single platform yet offers the security, visibility, and spending controls enterprises demand.
What happened
Enterprise AI teams are now running a median of three orchestration platforms (software that coordinates AI agents) simultaneously rather than relying on a single vendor, according to VB Pulse research. This shift reflects distrust in individual vendors' security and permissioning capabilities, prompting enterprises to impose their own controls.
Why it matters
The fragmentation reveals a critical gap in the current AI orchestration market—enterprises cannot fully trust any single platform to manage both performance and cost. One in five enterprises report they cannot stop a runaway AI agent's spending in real time, creating financial and operational risk. For CIOs and enterprise AI leaders, this signals that multi-platform strategies, while adding complexity, are becoming a practical necessity to maintain security and cost visibility.
What to watch
Microsoft currently leads in primary platform usage among enterprises, while Anthropic is leading in what enterprises are evaluating for future deployment. However, the broader challenge enterprises face centers on token usage visibility and agent spending controls—capabilities that will likely become differentiators as AI agent adoption accelerates.
Ask the AI about this article →
The shift to multi-platform orchestration reflects a maturing but still-uncertain enterprise AI market. Rather than the typical software adoption pattern—where a clear leader consolidates the market—AI orchestration is fragmenting as enterprises deliberately hedge their bets. This is not merely risk-aversion; it signals real gaps in the current market. Vendors have not yet convinced enterprises that their permissioning and security models are robust enough to merit exclusive reliance, nor have they solved cost visibility and control—the two operational levers enterprises prioritize most. The fact that one in five enterprises cannot stop an AI agent's spending in real time indicates that token usage tracking and real-time spend management remain unsolved problems. Microsoft's lead in primary usage contrasts sharply with Anthropic's lead in what enterprises *plan* to adopt, suggesting a potential shift in preference as enterprises evaluate alternatives for future workloads.
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