Most product teams are 100% using AI. Almost none of them can tell you what it's actually worth.
The moment of truth is the QBR or the next planning cycle, when leadership asks what the AI feature delivered and the answer is 'users seem to like it' or 'we saved some time.' Neither survives budget scrutiny.
The problem isn't that PMs don't care about ROI. It's that nobody taught them how to calculate it before they built the thing. So they either overpromise in discovery, dodge the question in reviews, or inherit a project that leadership already suspects isn't working.
This workshop fixes that with a framework you can use on any AI project, before you build it.
What You'll Learn
Why AI ROI Numbers Fall Apart in the Room
Vague time savings, made-up percentages, no baseline. Leadership stops trusting the numbers. The result: AI budgets get cut, projects get shelved, and PMs lose credibility.
We'll break down why this happens and what the fix looks like.
The Framework (4 Steps)
Map the workflow What's actually happening today, step by step. You can't measure what you don't understand.
Quantify the baseline Time × hourly cost × frequency = current cost. This is the number you're improving against.
Model the AI scenario Realistic reduction, not fantasy automation. We'll show you how to estimate conservatively and still make a compelling case.
Build the business case Savings vs. implementation cost, payback period, and the one-pager that gets leadership to say yes.
A Real Example (Live Walkthrough)
We'll walk through one workflow end to end and show the full math — from zero to a concrete ROI number you can present to leadership the same day.
From Feature Shipper to Business Outcome Owner
You stop being the PM who ships features and start being the one who moves business outcomes. That's what gets you a seat at the strategy table.
What's Included
- ✓The 4-step AI ROI framework (template included)
- ✓Live walkthrough with real numbers
- ✓ROI calculator spreadsheet you can reuse
- ✓3 months free access to WorkLearn Labs to run the framework on your own projects
- ✓Recording available for 30 days
Prerequisites
No data science or engineering background needed. If you can run a discovery interview and build a roadmap, you have everything you need to walk out of this with a number you can put in a deck.
