The new economics of enterprise AI
Enterprise AI is going through the same shift.

Proof1 independent outlet
Key points
- Imagine your company just discovered electricity.
- It becomes how efficiently the AI environment converts paid capacity into useful business outcomes.
- That’s the metric worth tracking: effective cost per useful outcome — the total platform, model, operations, and capacity cost required to complete work the business can actually use, whether a resolved request or a completed workflow.
- One of the biggest misconceptions in enterprise AI is that owning infrastructure automatically improves economics.
Sources (1)
- [1]The new economics of enterprise AIMIT Technology Review (AI) · Oct 20, 03:20 PM
Enterprise AI is going through the same shift.
Imagine your company just discovered electricity.
Extractive summary: sentences quoted from the sources.
Before this
- Oct 20, 2026Voxtral 3
- Oct 20, 2026[AINews] DeepSeek DeepInfer: Open Source SOTA Inference running 155T toks/day/cluster making $22m/day at ~80% margin for a 81 day payback
- Oct 20, 2026Do Diffusion LLMs Scale? Testing Mercury 3 + Decide
- Oct 19, 2026Developers can now access SageMaker Studio through the new AWS experience
- Oct 19, 2026Push-based KV transfer to improve TTFT and TPOT for disaggregated inference in vLLM
- Oct 19, 2026NVIDIA Open Sources Run:ai Under Apache 2.0 for Kubernetes GPU Orchestration

