Chief AI Officers Are Now Using Outcome Based Pricing Models

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In the context of Artificial Intelligence (AI), Outcome-Based Pricing means you only pay when the AI successfully completes a specific task or achieves a goal.
Instead of paying for the software's monthly access (subscription) or how many words it writes (usage), you pay for the actual result it delivers.
Easy-to-Understand Example: The AI Customer Bot
Imagine a company that sells an AI chatbot to help online stores handle customer questions.
• Traditional Pricing: The store pays $500 a month just to have the bot active on their site, even if it never actually fixes a problem.
• Outcome-Based Pricing: The store pays $0 to have the bot, but they pay $1.00 for every ticket the AI successfully resolves without needing a human to step in.
How it works:
• Success: A customer asks, "Where is my package?" The AI tracks the order and gives the answer. The customer says "Thanks!" and leaves. The store pays $1.00.
• Failure: A customer has a complicated complaint. The AI doesn't understand and has to call a human agent. The store pays $0 for that interaction because the AI didn't "solve" the problem.
Why this matters for AI
• Lowers Risk: You don't have to worry about buying expensive AI tools that don't work; you only pay when they do.
• Better AI: The company making the AI is motivated to make it smarter because they only get paid if the AI is successful.
• Real Examples: Companies like Intercom ($0.99 per resolution) and Zendesk have already moved toward this "pay-for-success" model for their AI agents.