AI monetization is starting to feel kind of like Mad Max: Fury Road.
The terrain is chaotic. The wasteland warlords are everywhere. Systems that worked perfectly well on smooth SaaS highways are suddenly getting stress-tested by fluctuating inference costs, unpredictable usage spikes, and increasingly diverse AI workflows.
You’re in the desert now. You need to build your own Mad Max car, your own personal V8 Interceptor. That is exactly why AI credits are becoming more common. Today you can find them in roughly 30% of AI services, from established players like Workday and Salesforce to incumbents like Notion and Higgsfield.
Credits are essentially the shock absorbers of monetization systems. On smooth roads, you barely notice them. But once the terrain becomes unstable, they suddenly become critical for maintaining stability and control. Otherwise, you’ll crash hard in the post-saaspocalypse outback.
The challenge is that many companies are installing the suspension system before understanding whether the road actually requires it. This is where Michael Mansard’s COMPASS Flash Triage framework becomes incredibly useful. Rather than treating credits as either inevitable or universally superior, the framework helps companies evaluate when credits are actually justified by the underlying economics and operating realities of the business.
Credits are most valuable when they absorb genuine complexity, not when they simply add another abstraction layer. In the spirit of Mad Max (and in honor of our own V8 Interceptor – a cool new AI Pricing Simulator), here are four principles worth keeping in mind when considering AI credits.
Start with metrics before introducing credits.
Before you bolt a credit system onto your business, ask whether a simpler pricing approach can solve the problem. Could you capture value through tiered subscriptions, usage-based pricing, or bundled offerings? If so, those options are often easier for customers to understand and easier for your finance team to forecast. Credits are most valuable when they help you manage real complexity across different workflows and cost structures.
Treat credits as a tool, not a philosophy.
You don’t have to assume that credits are the inevitable future of AI monetization. The right pricing model depends on where your business is today. If you’re running a mature AI platform with diverse capabilities and variable costs, credits may make sense. But if you’re an early-stage company focused on accelerating adoption and shortening sales cycles, a simpler subscription model may be the better choice. Your pricing strategy should reflect your business goals and customer behavior—not blind allegiance to a particular model. After all, not every company needs to join Immortan Joe’s convoy.
Cost variability is often the deciding factor.
When you’re evaluating whether credits make sense, pay close attention to your cost-to-serve variability. Traditional SaaS businesses benefited from relatively predictable marginal costs, but AI changes that dynamic. Inference workloads, GPU utilization, and agent activity can all cause costs to fluctuate based on how customers use your product. If your costs remain stable, subscriptions may continue to work well. But when costs become unpredictable, credits can help absorb that variability and keep your War Rig running at full speed.
Pricing should evolve over time.
You shouldn’t think of pricing as a permanent decision. As models become more efficient, infrastructure costs stabilize, and customer usage patterns mature, you may find opportunities to simplify your pricing again. In fact, simpler pricing often creates a better customer experience and reduces operational overhead. The goal isn’t to build the most sophisticated monetization system possible—it’s to build the one that best fits the road your business is actually traveling today. That’s how Max and Furiosa live to fight another day.
If you’re interested in trying out some of these concepts yourself, take the Simulator out for a spin.
