WorkThe story, in brief
Presentation: Leadership in AI-Assisted Engineering
95% of AI pilots fail. Here's how leaders actually measure ROI.
The KeyNews take
Why it matters
A framework-driven analysis of why most enterprise AI engineering initiatives stall, and how to move past anecdotes to measurable outcomes using DORA metrics and the SPACE/Core 4 frameworks.
The key facts
9 to know95% of GenAI pilots fail to move into production
DORA and DX research used to measure impact
SPACE and Core 4 frameworks for ROI measurement
Focus on balancing speed vs. quality in agentic SDLC solutions
Developer adoption and fear reduction as key metrics
95% of GenAI pilots fail (GenAI Divide statistic)
DORA and DX research cited as data foundation
Focus on developer productivity and SDLC integration
Speed vs. quality trade-off guidance
Go to the source
InfoQ AI/MLinfoq.com
Publisher excerpt: Justin Reock discusses the reality of AI’s impact on engineering, moving past anecdotes to hard data from DORA and DX research. He explains the "GenAI Divide" - where 95% of pilots fail - and shares how leaders can use the SPACE and Core 4 frameworks to measure true ROI. He explains how to balance…