Treating enterprise AI as an operating layer
TL;DR
There’s a fault line running through enterprise AI, and it’s not the one getting the most attention. The public conversation still tracks foundation models and benchmarks — GPT versus Gemini, reasoning scores, and marginal capability gains. But in practice, the more durable advantage is structural: who owns the operating layer where intelligence is applied, governed,….
Nauti's Take
The thesis holds up: structural ownership of where AI is applied gives more durable competitive advantage than model selection. You can already see it in how Salesforce, ServiceNow and Microsoft are positioning.
The risk for enterprises is lock-in — committing to a proprietary operating layer today makes switching harder later. CIOs should treat interoperability as a first-order criterion before the lock-ins deepen.
Summary
There’s a fault line running through enterprise AI, and it’s not the one getting the most attention. The public conversation still tracks foundation models and benchmarks — GPT versus Gemini, reasoning scores, and marginal capability gains.
But in practice, the more durable advantage is structural: who owns the operating layer where intelligence is applied, governed,…
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