In SaaS, variable costs are familiar. AWS and Azure bills rise and fall with traffic, storage, and bandwidth, but you can usually forecast them and smooth them with commitments.
AI flips the model because cost is triggered by a mixture of behavior and model choice, not just scale. Each generation can add metered COGS, and multimodal makes the spikes sharper: images, audio transcription, voice output, and video generation can cost orders of magnitude more than a short text reply. Retries, longer outputs, bigger context windows, and tool calls amplify this fast.
Then comes the perception problem. Buyers are trained by ChatGPT and Gemini that AI feels cheap or “free” at the point of use, which anchors expectations. The executive challenge becomes defending value and margin while keeping usage predictable.
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