The AI bill is the new lock-in
The demo never shows you the shape of your bill
Every major platform now has AI, and the capability is converging fast. So the useful selection question is no longer whose AI is better, it's what it costs you to use, and how that cost behaves as your people adopt it.
The pricing models diverge sharply where the capability doesn't
Some meter AI by the action, so cost climbs with use. Some bundle it in, flat until you hit a limit. Some run a base-plus-premium model on a currency that expires. Same capability, three completely different answers to one question: what happens to my bill when this works?
When AI cost scales with use
When AI cost scales with use, your most enthusiastic adopters become your biggest expense, and teams quietly start rationing the very capability the business case promised. The fix isn't avoiding any one model, it's modelling what each does to your bill, at your scale, before you sign.
Frequently asked questions
Why does AI pricing matter more than AI capability?
Capability is converging across major platforms, so the real difference between them is what each costs you to use, and how that cost behaves as adoption grows.
What pricing models do AI platforms use?
Some meter by the action, so cost climbs with use. Some bundle it in flat, until you hit a limit. Some run a base-plus-premium model on a currency that expires.
What is the new AI lock-in?
It's the cost of succeeding, not the cost of leaving. When AI cost scales with use, your most enthusiastic adopters become your biggest expense.
How do you avoid this trap?
Not by avoiding any one pricing model, but by modelling what each does to your bill, at your own scale, before you sign.
The question that follows
So before you commit: what happens to your bill when the AI actually works?