The most consequential contest in enterprise technology right now may not be which AI model gets the best benchmark scores. According to analysts Dave Vellante and George Gilbert, the real fight is structural: who will control the two layers that define how organizations actually put AI to work at scale.
Their analysis examines the competitive positioning of Snowflake, Databricks, and the major AI model makers. The struggle is framed around two emerging control points. The first is the intelligent client, or agentic system of engagement: the interface through which employees and developers interact with AI. Snowflake CoWork, Databricks Genie, Microsoft Copilot, OpenAI Codex, and Google Gemini Enterprise all compete in this layer.
The second — and arguably more decisive — layer is what the analysts call the System of Intelligence. This is the backend infrastructure that learns from every agent interaction, accumulates an organization's operational memory, and transforms individual productivity gains into compounding organizational capability. Whoever builds the tightest feedback loop between client and backend, the argument goes, wins enterprise AI for the next decade.
The complexity of that competitive map is significant. Snowflake now finds itself competing not just with Databricks, but with Microsoft, Google, OpenAI, Anthropic, Salesforce, ServiceNow, and SAP — each of which has its own ambitions to own the intelligent client and the backend that powers it. The same logic applies in reverse: model makers who began as infrastructure providers are rapidly building application-layer interfaces that pull them into direct competition with the data platforms.
The analysts also raise a structural risk that echoes earlier enterprise computing cycles. The proliferation of vertical AI agents — specialized tools for finance, HR, legal, and operations — is creating new silos inside organizations, similar to the departmental software fragmentation that plagued enterprises for decades. Sustainable enterprise value will require end-to-end intelligence infrastructure, not another generation of disconnected point solutions.
Why It Matters
For enterprise technology leaders, the stakes of this battle are practical and immediate. The platform that captures an organization's operational knowledge — its workflows, its reasoning patterns, its decision history — becomes deeply embedded over time and difficult to replace. Choosing where to build an AI stack is increasingly a long-term strategic commitment. Understanding who is winning the agentic client and intelligence backend contest is essential context for any organization making AI infrastructure investments over the next two to three years.