7 AI KPIs Every Engineering Leader Should Track

Measure What Matters in the Age of AI Engineering

AI coding tools have become inseparable from modern engineering, but most leaders are still asking the same question: Is AI actually improving performance?

This new guide uncovers the seven key metrics every engineering leader needs to measure the real impact of AI across Adoption, Productivity, and Outcomes.

You’ll learn how to:

✓ Track adoption with KPIs like Daily Active Users and AI-Generated Code
✓ Measure productivity via throughput, satisfaction, and code quality
✓ Connect AI to business outcomes like cost efficiency and growth capacity
✓ Avoid vanity metrics that distort what success really looks like

Start measuring what matters in the age of AI now.