AI Pulse · Business Models & Winners

Two podcast episodes from the past six weeks landed on opposite sides of the same question: how do you actually charge for AI tools? One tracked companies abandoning per-seat pricing in favour of usage or outcome models. The other documented a swing back to per-employee pricing, noting that AI-heavy firms now spend around $7,500 per employee per month on tools. Neither episode offered a conclusion. The market hasn’t settled.

This oscillation matters because pricing models shape how you budget, how you scale, and whether a tool becomes a line item you can predict or a variable cost that spikes when your team actually uses it. Usage-based pricing sounds fair until you get a bill that doubles because three people ran heavy workflows in the same week. Per-seat pricing feels stable until you realise you’re paying for accounts that sit idle half the month. Outcome-based models sound appealing in theory, but most vendors still haven’t figured out how to define or measure an outcome in a way that works across different companies.

The fact that the industry is still swinging between these models tells you no one has cracked it yet. That’s why we built the Omni Command Centre around a flat retainer tied to outcomes, not seats or API calls. You know what you’re paying, and the system adapts to what you’re trying to accomplish rather than how many times you log in. It’s not the only answer, but it’s a defensible middle path while the rest of the market figures out whether to charge by the chair or the query.

If you’re evaluating AI tools right now, ask the vendor how they price and what happens when usage changes. If they can’t give you a straight answer, that’s useful information too.