AI in Product — Strategy to Ship
Your team has too many AI ideas and no clear way to choose between them. This workshop helps product, design, and engineering align on the right use case — then plan how to ship it responsibly.
Format: 1 day · in-person or remote. Audience: Product leaders, innovation managers, design and engineering teams shipping AI features.
Duration: 1 day. Group size: Up to 20 participants. Delivery: In-person or remote. Languages: English.
What you will learn
- A prioritised list of AI use cases worth your roadmap slot
- Patterns for trustworthy, transparent AI interactions
- A discovery-to-ship plan for your first or next AI release
- A prioritised AI use case list — scored by user value, technical feasibility, and strategic fit.
- Interaction patterns for AI features that build trust: explainability, fallback states, user control.
- A discovery-to-ship plan for your highest-priority AI release.
- Clarity on where AI is genuinely useful in your product and where it's adding noise.
- A shared vocabulary for AI feature conversations across design, product, and engineering.
- Confidence presenting AI strategy to leadership without over-promising or under-delivering.
Why this matters now
- Most product teams are not short of AI ideas. They are short of a framework for choosing between them — and short of confidence that what they build will earn user trust rather than erode it.
- The pressure to ship AI is real. So is the risk of shipping something that gets abandoned in three weeks, creates legal exposure, or makes users feel like the product is guessing on their behalf without explanation.
- This workshop gives product, design, and engineering teams a practical end-to-end method: score the ideas, design the trust layer, and leave with a delivery plan for the one AI feature most worth building right now.
Green Effort AI · Allianz Global UX/UI Center of Excellence
Your team has too many AI ideas and no clear way to choose between them. This workshop helps product, design, and engineering align on the right use case —.