Why AI costs surprise teams
Gartner forecasts generative AI model spending to grow 80.8% in 2026 and data-centre spending by 31.7%. Inside companies, costs often jump when a pilot reaches real users, because usage, context length and retries all multiply.
Design patterns that cut cost
Route simple requests to small, cheap models and reserve large models for hard cases. Cache answers to repeated questions and reuse embeddings. Trim context: retrieve the three best passages, not thirty.
Batch background work such as summarisation or classification instead of calling models one item at a time.
Make cost visible
Tag every model call with the feature, tenant and user that triggered it. Show cost per feature and per customer on a dashboard, and set budget alerts.
Add cost to your evaluation suite. A prompt change that improves accuracy by 1% but doubles cost should be a deliberate decision, not a surprise.
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