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The new economics of enterprise AI

David Sydow· 20 octobre 2026

Imagine your company just discovered electricity. At first only a few machines run on it, and nobody worries about efficiency — consumption is low and the value is obvious. But once electricity becomes infrastructure, every process depends on it, and the question changes from “can we use it?” to “h…

Résumé

AI as business infrastructure

Enterprise AI is transitioning from experimental tools like chatbots to a foundational layer of business operations, similar to how electricity evolved from a novelty to an essential utility.

Initially, companies focused on whether they could use AI, but now the priority is measuring how efficiently they use it.

The key metric is no longer the cost of a single token (a unit of data processed by AI models) or GPU-hour (the cost of running a graphics processing unit for one hour), but the effective cost per useful outcome.

This measures the total expense—including platform, model, operations, and capacity—required to produce a tangible business result, such as resolving a customer request or completing a workflow.

The shift reflects the growing complexity and integration of AI systems in production environments, where efficiency and scalability become critical.

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