Agentic AI drives real productivity gains and reduces friction only when applied across multiple stages of the SDLC. Software engineering leaders can leverage this research to systematically eliminate bottlenecks, reimagine workflows, and automate inefficiencies.

What is the impact of AI on the software development lifecycle?

According to Gartner, by 2028, asynchronous software engineering (SWE) agent workflows will boost team productivity by 30%–50%, exceeding the 0%–20% gains from AI code assistants in 2025.

Does AI-augmented software development solve the ROI gap?

Focusing only on AI inside the IDE leads to diminishing returns. Coding is rarely the primary constraint to value delivery. Greater ROI comes from applying AI across the full software development lifecycle—planning, testing, integration, governance, and delivery. Beyond productivity, AI-driven SDLC transformation unlocks:

• Stronger competitive advantage through faster innovation
• Higher customer and user satisfaction
• Improved developer experience and retention

Zero-Friction SDLC With Autonomous Software Delivery: A 3-Phase Framework for Leaders

Maximizing AI impact requires a structured, end-to-end approach that connects engineering gains to measurable business outcomes.

Download the Gartner report to explore insights on driving measurable agentic AI business impact.

You’ll learn how to:

• Apply a proven three-phase approach to scale agentic AI across the software development lifecycle
• Unlock the full potential of platform engineering with AI
• Connect AI productivity gains to business value

Gartner, How to Maximize the Impact of Agentic AI in the SDLC, Manjunath Bhat, Philip Walsh, 19 January 2026

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