Introduction

AI credits are replacing old pricing models. Big players like Salesforce and OpenAI are pushing them as the new normal for buying AI.

What’s the problem it solves?

Traditional pricing (seats, subscriptions) can’t handle uneven AI usage. Heavy users drain profits, while light users overpay. Credits make costs fairer, flexible, and tied to value.

Quick Summary

Companies like Microsoft, Salesforce, and OpenAI are moving to credit-based pricing for AI. Instead of paying per seat or flat subscriptions, buyers get a pool of credits to use however they want. This system gives companies more control over usage and lets vendors align costs with actual work delivered.

Credits aren’t new, but adoption lagged because buyers worried about unpredictable bills. Now that large players are educating the market, credits are becoming the standard. Vendors can use them to manage expensive AI models, prevent power users from eroding margins, and introduce flexible plans. Customers can test features, use credits on what matters most, and scale at their own pace.

In practice, credits vary widely. Some are tied to costs (like raw API usage), while others connect to business outcomes (like Salesforce charging credits for case resolution). The second approach is clearer for buyers because it links price directly to value delivered, not abstract token math.

Key Takeaways

• AI credits are now the most common way to sell AI, used by major companies like OpenAI and Salesforce.
• Heavy AI usage is concentrated among a small group of users, making credits essential to control costs.
• Cost-based credits are simple but feel like passing the bill; outcome-based credits tie pricing to real value.
• Including baseline credits, offering annual rollovers, and showing usage transparency builds trust.
• Credits are a bridge toward true value-based pricing, not the final model.

What to do

• Adopt credits early: Align pricing to usage before margins suffer.
• Bundle wisely: Include base credits in all plans so customers form habits.
• Prioritize value outputs: Charge for completed tasks, not raw compute.
• Go annual with rollovers: Reduce churn and improve forecasting.
• Build transparency tools: Help customers see and predict how credits get spent.

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