AI features are quickly becoming table stakes for modern SaaS products. From intelligent workflows to agentic experiences, product teams are under pressure to “add AI” — fast.
But when it comes to cost, most teams are still guessing. They estimate loosely, ship optimistically, and hope usage behaves. And then the invoices arrive.
The problem isn’t that AI is expensive. It’s that AI cost is rarely designed for upfront.
Above: Imagine being able to estimate your usage costs before you start building. With the Launchpad Units Estimator, you can predict the usage and cost of your future app as soon as you complete your design in Launchpad Blueprint.
Why AI costs are hard to predict
Traditional SaaS pricing is familiar territory. You know your infrastructure, your licensing model, and your usage patterns. AI changes all of that.
With AI-powered features, cost is driven by a mix of variables that are easy to overlook early on:
Usage frequency: how often users trigger AI-driven actions
Workflow complexity: multi-step automations, agents, and decision logic
Data access: the size, shape, and movement of data involved
Model interactions: how many calls, retries, and parallel executions occur
Growth effects: What happens when one AI feature becomes wildly popular?
Most teams don’t account for these dynamics until after the feature is built — when changes are expensive and politically painful.
The “we’ll figure it out later” trap
A common pattern we see is this:
- An AI feature is approved based on customer demand or competitive pressure
- The team prototypes quickly to prove feasibility
- Cost assumptions are made at a high level (or ignored entirely)
- The feature ships
- Usage grows faster than expected — and so does spend
By the time finance asks, “Why is this so expensive?”, the feature is already live and embedded in customer workflows.
At that point, teams are left with three bad options:
- Throttle usage and degrade the experience
- Rush optimizations that increase risk
- Absorb the cost and hope pricing catches up
None of these are great outcomes.
Designing AI features with cost in mind
The most successful teams flip the sequence. Instead of asking, “How much does this cost now that it’s built?”, they ask: “What will this cost if it succeeds?” This requires visibility early — before building.
It means designing:
- Workflows and AI behavior, not just UI
- Usage assumptions, not just functionality
- Scale scenarios, not just MVPs
When cost becomes a design input, teams can make smarter tradeoffs — and avoid surprises.
Making cost predictable, not painful
This is exactly why Launchpad built tools like Blueprint and the Units Estimator.
With Launchpad Blueprint, teams can design AI-powered applications visually: defining workflows, rules, and GenAI steps upfront. While designing your workflows with Blueprint, it becomes crystal clear where to integrate AI to get the best output.
Then, with the Units Estimator, those designs can be analyzed to predict:
- Expected usage patterns
- Resource consumption
- Delivery cost as the app scales
Instead of guessing, teams can model different scenarios:
- What happens if usage doubles?
- Which workflows drive the most cost?
- Where will optimizations have the biggest impact?
This gives product, engineering, and finance teams a shared view of reality — early.
Why this matters more than ever
As AI features become more autonomous and agentic, the gap between what you build and what it costs to run will only widen. Teams that win won’t be the ones who move fastest at any cost. They’ll be the ones who move fast with control. Predictable cost isn’t a finance problem. It’s a product design advantage.
Design first. Estimate early. Scale confidently.
AI doesn’t have to be a financial black box. With the right approach (and the right tools), teams can design AI features that scale technically and economically.
If you’re exploring AI-powered features for your SaaS product, start by designing them in Launchpad Blueprint, then estimate delivery costs with the Units Estimator.
Because the best time to understand the cost of AI isn’t after launch — it’s before.
About the Author
Kat Austin works in product marketing for Launchpad and helps companies of all sizes understand how to use SaaS to innovate and grow revenue faster than ever before.