How to monetize AI apps
In brief
Pick a model that covers variable inference cost: subscriptions and usage pricing work for high-value segments; ads work when most usage stays free.
Compare the models
- Subscriptions: Predictable revenue, but only works when users have strong willingness to pay.
- Usage-based pricing: Aligns price to cost/value, but adds friction for casual use.
- Freemium limits: Helps acquisition, still leaves you paying for free-tier compute.
- Ad-funded (inference-time): Scales with usage by monetizing the existing wait window.
When ads are a fit
Ads are a fit when a large share of usage is free and prompts are frequent. Inference-time ads monetize the wait window instead of inserting extra interruptions.
Use Free tier economics to plug in your CPM, fill rate, slots per prompt, and cost per prompt.
Operational requirements
If you go ad-funded, make these pieces explicit:
- Consent gating and profiles: Compute Sponsoring
- Data minimization: Data firewall
- Fail-closed behavior: Safety
- Proof and settlement: Engineering evidence
- Policy controls (categories, industries, formats): SDK configuration
Next step
If you want implementation detail, start with How wavebird works and then move into the SDK Quickstart.
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Last updated: 2026-04-03