Credit consumption is the metric that tracks how many AI processing units a customer support automation platform uses when handling tickets, typically measured per interaction or per task completed.

Unlike seat-based pricing, credit consumption aligns costs with actual usage. When an AI agent resolves a ticket, it consumes credits based on the complexity of the reasoning required—a simple FAQ lookup uses fewer credits than a multi-step order modification that requires API calls and policy evaluation.

The shift to credit-based models reflects a fundamental truth about AI support: value comes from resolution, not availability. A traditional help desk charges per agent seat regardless of whether that agent handles 10 tickets or 100. Credit consumption flips this, making costs proportional to work performed. For high-volume support teams, this creates predictable unit economics—you know exactly what each resolved ticket costs.

Watch for hidden credit multipliers. Some platforms charge extra credits for tool usage, knowledge retrieval, or handoffs. The best models are transparent: one credit equals one complete interaction, regardless of what happens under the hood.

Related terms: Agent Handle Time, Ticket Complexity, Warm Handoff