What are AI pricing models?

At a glance

• Four core models: per-seat (flat fee per user), usage-based (pay per token, call, or action), credit-based (prepay a pool you draw down), and outcome-based (pay only on a result)^[1].
• Per-seat is fading because AI agents do work with nobody logged in, so seat counts no longer track value or cost.
• Hybrid (fixed base plus variable charges) is now the dominant model: a predictable floor with room to scale^[5].

How the models differ

Per-seat: $500/month per attorney. Usage-based: pay per customer review the AI analyzes. Credit-based: buy 10,000 credits, spend 50 per task. Outcome-based: a recruiter pays only when a surfaced candidate gets hired. Every AI query burns real compute, so vendors run 50-60% gross margins versus 80-90% for old SaaS^[2] pushing bills toward consumption.

What it means for your budget

Match the model to your priority. Want predictable costs? Choose a hybrid with a fixed base^[5]. Swinging usage? Usage-based can be cheaper but harder to forecast. Care most about results? Outcome pricing aligns the bill with value: Intercom’s Fin charges $0.99 per resolution and nothing if it hands off^[4]. Salesforce kept rechanging Agentforce after per-conversation bills proved unpredictable^[3]. Before signing, pin down the billable unit and ask for a cap.

Bottom line

There is no single right model, only the one fitting how you buy increasingly a hybrid base plus a charge that tracks the value delivered.