The competitive landscape for enterprise AI is undergoing a significant shift as businesses move beyond mere experimentation with Large Language Models (LLMs) toward the deployment of complex AI agents. While previous industry discussions have relied heavily on transaction-based spending data to determine market leadership, new research from the August VB Pulse agentic orchestration tracker reveals a more nuanced reality: there is a distinct gap between model adoption and the choice of a primary orchestration platform.
The Architecture of Enterprise Agent Control
The primary-platform decision is central to modern enterprise AI strategy. When organizations deploy AI agents capable of multi-step workflows—such as retrieving files, executing tool calls, and managing exceptions—they require an “agent control plane.” This coordinating layer serves as the logic engine that manages agent runtimes, governs access permissions, and handles error recovery.
According to the data, enterprises are currently evaluating where this control plane should reside. Approximately 26% of respondents favor a provider-managed agent service, while 33% prefer a hybrid approach that combines provider-native tools with external orchestration layers. The remaining enterprises are still weighing the risks of inflexibility and potential vendor lock-in. Nearly 28% of those surveyed identified a lack of interoperability between models and tools as their primary concern, highlighting why organizations are cautious about handing over full architectural control to a single model provider.
OpenAI vs. Anthropic: Adoption vs. Integration
The data highlights a clear divergence between OpenAI and Anthropic regarding how they are integrated into enterprise stacks. OpenAI maintains a commanding lead in terms of platform maturity and trust. Among the 75 enterprises using OpenAI’s Agents SDK or Responses API, 69% designate it as their primary orchestration platform.
In contrast, Anthropic faces a different challenge. While its Claude platform and Agent Skills are integrated into 45 enterprise stacks, only 38% of those users identify it as their primary orchestration choice. This 38% figure represents the lowest conversion rate among platforms used in at least 25 enterprise environments. These figures suggest that while enterprises are enthusiastic about incorporating Anthropic’s models, they are more likely to treat the platform as a specialized component rather than the foundational hub for their entire agentic infrastructure.
The Pipeline Advantage for Anthropic
Despite the disparity in primary-platform adoption, Anthropic shows significant momentum in future-looking metrics. When measuring consideration—defined as enterprises planning to adopt, add, or replace their current platforms within the next 12 months—Anthropic emerges as a top contender. Among 121 enterprises surveyed, 36 expressed interest in adopting Anthropic, representing the highest ratio of consideration relative to an existing user base among any platform in the study.
This trend suggests that while OpenAI currently dominates the “build-on” segment of the market, Anthropic is rapidly gaining ground in organizational roadmaps. The challenge for Anthropic will be converting this high level of interest into deep-rooted technical dependency, ensuring that enterprises move from testing the platform to standardizing their agent control planes on it.
Distinguishing Spend from Strategy
Much of the industry confusion regarding AI dominance stems from reliance on transaction-based metrics, such as reports from corporate spend platforms like Ramp or routing services like OpenRouter. These datasets measure financial outflow, which does not necessarily correlate with strategic adoption.
Transaction data cannot distinguish between a team experimenting with a model for a one-off task and an engineering department building a production-grade agentic framework on top of a specific API. Because large enterprises often procure model access through complex, negotiated contracts via cloud marketplaces like Amazon Bedrock or Google Vertex AI, public-facing spending indexes often overlook the most significant enterprise deployments. Consequently, while spending data is useful for gauging consumer and developer trends, it remains an incomplete proxy for understanding which platforms are actually anchoring the enterprise’s digital infrastructure.
Moving Toward the 2026 Horizon
As enterprises look toward 2026, the question of the control plane will likely become the definitive factor in the “model wars.” The industry is moving past the phase where simply providing an API is sufficient to win market share. Instead, vendors are being judged on their ability to act as reliable orchestration layers that provide security, observability, and flexible integration.
With 60% of enterprises planning to shift or add an orchestration platform within the next year, the current landscape is fluid. For established leaders like OpenAI, the objective is to maintain the trust of their existing core users. For competitors like Anthropic and Google, the goal is to convert strong current consideration into the foundational role of the primary control plane. Whether the market eventually settles on a few dominant, vertically integrated providers or a decentralized ecosystem of specialized agents will depend on how successfully these companies address the enterprise’s ongoing concerns regarding interoperability and architectural independence.
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