AI is redefining your revenue model, whether you’re an AI company or not.

But most SaaS companies aren’t prepared for what that actually means.

For the past two decades, software pricing revolved around access: subscriptions, tiers, and seat-based models. Customers paid for permission to use tools that made users more productive.  

There were, of course, exceptions for underlying services, information, and technology, which were billed on the basis of resources consumed, but the majority of B2B software was priced via some form of subscription.

AI flips that model on its head. When software does the work itself, value is no longer tied to access. It’s tied to outcomes.

If your monetization strategy is still optimized for access, you’re exposed in two critical ways: competition and value readjustment.

This isn’t a pricing tweak. It’s a systemic reset. 

The last comparable shift occurred in the early 2000s, when the internet killed install-based licenses and paved the way for SaaS. The move from perpetual licences to SaaS changed the underlying economics, the metrics by which companies were valued, the markets that could be reached, and the speed of adoption.

What’s different now is velocity. AI has collapsed product cycles, shifted buyer behavior, and blurred the line between software and services. Consumption is surging, token costs are dropping, and legacy pricing infrastructure wasn’t built to handle any of it.

The real shift is about how customers define value. Outcomes matter more than access, and time saved and results delivered matter more than features unlocked.

Companies must now ask: 

• What exactly are we charging for? 
• What pricing model enables us to move fast, experiment freely, and still protect our margins?

The companies staking out a competitive advantage are modernizing their revenue infrastructure to match. Usage-based, outcome-based, and hybrid models have gained traction not because they’re trendy, but because they’re necessary to stay competitive.

You can’t run an AI-native GTM motion on static pricing tools. You need infrastructure that’s flexible, programmable, and real-time. The same experimentation mindset you apply to product development now needs to extend to pricing.

I broke this down in detail in a recent webinar with Metronome CEO Scott Woody.

If you want to see what usage models are working and how SaaS leaders are adapting faster than the market, here’s where to start.