Design "AI Products Customers Actually Pay For"
Move from AI features to revenue loops, pricing, retention, and a CFO-ready business case.
Most AI features are built as cost centres, not revenue engines. In four hours, you'll name the failure pattern your product is living, map it to the right revenue loop, choose a pricing model you can defend to a CFO, and leave with a 30-day experiment plan — a complete one-page Revenue Design Brief.
From features to a loop that pays.
Why AI products fail to monetise
50 minMost AI features are built as cost centres, not revenue engines. This block names the four failure patterns — and you'll identify which one your product is living right now.
AI Revenue Readiness Audit — score your product across six dimensions.
ArtefactYour failure pattern named and ranked.
The revenue loop framework
60 minThree types of AI revenue loops: efficiency loops, engagement loops, expansion loops. You'll identify which loop your product is capable of running — and why forcing the wrong loop kills monetisation even when the AI itself works.
Loop Discovery Workshop — map your product to one primary loop.
ArtefactYour AI revenue loop mapped and loop type selected.
Pricing and packaging AI value
60 minFour AI pricing models: outcome-based, usage-based, seat + AI tier, embedded AI uplift. Which model your loop demands — and why India and APAC teams default to the wrong one. How to present AI pricing to a CFO who doesn't trust the ROI yet.
Pricing model selection — choose, score, and defend your model in one slide.
ArtefactPricing model selected with a one-line CFO-ready justification.
Includes: the race-to-the-bottom trap, value-based pricing in trust-deficit markets, and the conversation to have when a buyer asks "what does everyone else charge?"
Retention mechanics & your 30-day plan
40 minWhy retention in AI products breaks differently from SaaS: the trust cliff, the accuracy plateau, the value-erosion loop. Three retention mechanics that compound rather than decay. Hot seats: two to three participants present their revenue loop and pricing choice — the group pressure-tests it.
30-day experiment design — one retention mechanic to implement this week.
ArtefactYour completed one-page Revenue Design Brief — loop + pricing model + retention mechanic + 30-day plan.
The AI Revenue Audit — five days before.
Five days before the workshop, you'll receive the AI Revenue Audit — a 30-minute diagnostic you complete on your own product. Participants who bring it done consistently say it's where the real value starts. If you arrive without it, the session still works.
The AI Revenue Design Kit.
- AI Revenue Readiness ScoreKnow whether your AI feature is a demo, cost saver, retention lever, or revenue engine.
- Revenue Loop CanvasMap whether your product should monetise through efficiency, engagement, or expansion.
- AI Pricing & Packaging DecisionChoose between usage-based, outcome-based, seat-plus-AI, or embedded uplift.
- CFO-Ready Business CaseExplain why the customer should pay more, renew, or expand.
- 30-Day Revenue Experiment PlanOne practical experiment to test monetisation after the workshop.
Built for a specific moment.
This workshop is for you if
- You're a PM at a Series A or B company with an AI feature live or in build
- You're a founder building an AI-native product, or embedding AI into an existing one
- You can describe what your AI does — but can't yet explain why someone should pay more for it
- You're building in India, Singapore, or Australia, where the US monetisation playbook consistently fails
Not for you if
- You're looking for a technical AI course
- You haven't started building yet
Stop shipping AI features you can't charge for. Start designing revenue loops customers pay into.
Ready to make your AI product pay?
Runs as a live cohort or as a private in-house session for your product and commercial teams. Message directly to check dates and find the right fit.
Live cohort · or a private in-house session for your team
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