Gartner® Research
Supercharge AI DevSecOps by Fixing Your Flow Problems First
Why leading engineering organizations are finding that workflow bottlenecks, not AI itself, are limiting software delivery, and discover practical steps to restore flow before scaling AI across development.
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AI adoption across software engineering is accelerating, yet many organizations are struggling to realize the productivity gains they expected.
This Gartner® research explains why improving development flow, not simply adding more AI, is becoming essential for delivering software faster and more predictably. The report explores how engineering leaders can reduce friction, improve delivery performance, and apply AI where it creates measurable impact.
In this Gartner® research, you'll learn how to:
- Identify the workflow bottlenecks preventing AI from improving software delivery
- Restore engineering flow by reducing work-in-progress and delivery variance
- Use value stream mapping to uncover systemic constraints across the SDLC
- Improve software delivery by reducing rework, delays, and decision latency
- Apply AI strategically after stabilizing development workflows
Key Insights
AI productivity gains are nominal, with about 71% engineering leaders reporting less than-expected gains."
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Source: Gartner does not endorse any vendor, product or service depicted in its research publications and does not advise technology users to select only those vendors with the highest ratings or other designation. Gartner research publications consist of the opinions of Gartner’s research organization and should not be construed as statements of fact.
Gartner®, Supercharge AI DevSecOps by Fixing Your Flow Problems First, Aaron Harrison, Manjunath Bhat, 8 June 2026.
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