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Your AI Bill Is Coming Due Soon — Has Anyone Asked What That's Going To Cost?
AI can answer customer questions, but tech docs teams need to ask what each answer costs — and whether better content structure can lower the bill
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Most conversations about generative AI and tech docs are too focused on what AI can do and not nearly focused enough on what AI costs when we ask it to do those things at scale.
That doesn’t mean the discussion about capability is wrong; it’s just incomplete.
We’ve spent a lot of time marveling at AI’s ability to summarize, rewrite, classify, retrieve, generate, explain, translate, categorize, and answer customer questions. But somewhere behind the flashy demo, the meter is running. 💰
And not metaphorically speaking. Every AI-powered answer has a cost. The infrastructure to keep AI systems grounded, current, auditable, secure, and useful isn’t free.
Tokens cost money. Retrieval does, too.
As does inference, monitoring, rework, escalations, and human review.
Related reading: What Is Token-Based Pricing for AI Models
My concern is that many organizations treat AI as a clever feature when it’s more like operating infrastructure. And infrastructure has a nasty little habit of sending invoices. 🧾
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Recent Reporting Shows Many Companies Are Already Wrestling With This Shift
Reuters reports that Target is weighing AI tool costs as vendors move toward usage-based pricing, where token consumption and scale can quickly change the economics.
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