AI is transforming software development, yet many organizations still struggle to see meaningful productivity gains. Gartner reports that nearly half of developers experience only 10 percent or less improvement, even as AI adoption grows.

Gartner explains that task level time savings rarely translate into real productivity because micro-efficiencies are lost to fragmented schedules, rework, and coordination. To achieve measurable impact, teams must redirect these savings into improved software quality, greater capacity, and higher value work.

The research shows the greatest impact of AI is achieved when applied beyond coding, especially to high-value, low-efficiency areas of the software development lifecycle, including:

• Refactoring and code migrations

• Understanding and improving legacy code

• Generating and maintaining documentation

• Enhancing and automating testing

• Supporting upstream activities such as requirements gathering and ideation

Gartner predicts that by 2028, teams that apply AI across the SDLC will achieve 25 to 30 percent productivity gains, compared to the 10 percent typically seen with code focused use.

Read the Gartner report to learn how engineering leaders can move from fragmented time savings to meaningful, system level productivity improvements.

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Gartner, How to Capture AI-Driven Productivity Gains Across the SDLC, Philip Walsh, Keith Mann, April 11, 2025.