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Free Lesson
Why your AI roadmap is lying to you
30 min
Feb 27, 2026 1:30 PM
Virtual (Zoom)
In this video
What you'll learn
Why AI failures start with data, not models
Understand how data trade-offs quietly break AI systems that look fine in demos.
The speed, cost, quality triangle for AI data
Learn how teams unintentionally pick the wrong two and why context matters.
How data strategy changes by use case
See why prototypes, user features, and analytics demand different data decisions.
What’s changing in AI data right now
Understand the shift from big data to better, curated, and synthetic data.
How to make defensible data trade-offs
Use a simple checklist to decide where quality matters and where it doesn’t.
Why this topic matters
Most AI roadmaps fail because data decisions are made implicitly, not deliberately. Teams optimize for speed and cost while assuming quality will hold. In production, it doesn’t. This lesson reframes AI strategy around data trade-offs, helping leaders choose the right level of quality, cost, and speed for each use case before failures show up in customers, metrics, or trust.
You'll learn from
Dr. Marily Nika
Gen AI PM Lead @ Google | ex-Meta, Fellow @ Harvard | TED AI Speaker | 40u40
Jeanne Williams
ex-Head of tPgM/Ops @ Google & ex-Apple