So, you think about how you use your cloud today, and you get a certain amount of usage within your seat, and if you go over the usage, you pay for that usage. That's likely the model that we will land at, but we're testing a few different models. What's clear to me is customers, sort of more broadly, are not yet willing to pay for outcomes-based pricing. Even if they know, and I'm one of these people, right? Even though I know I'm getting positive ROI and outcomes from some of the AI solutions that I'm using, it's too unpredictable and too unknown to move towards outcomes-based. It also creates a little bit of a disincentive, because you know the more you use it, the more you're going to pay.

They want to know if the efficiency gains justify the potential loss of flexibility.

It seems like the smart play is to maintain a multi-cloud strategy, even if it is harder to manage.

For large organizations, yes. But for everyone else, the complexity might outweigh the benefits. They end up betting on one provider and hoping the pricing structures don't change too drastically.

Which is risky given how fast the AI landscape is moving. New chips come out every year, and old pricing models become obsolete overnight.

That is true. The half-life of a cloud pricing strategy is getting shorter. What was a good deal last quarter might be a loss leader this quarter as the provider adjusts to new supply chains.