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DORA insights: Where is AI really driving developer productivity?

Join industry experts from Google Cloud, GitLab and (other company) share subject A, subject B, and Subject C in the DORA State of DevOps 2024. This is where we’ll provide an overview of the webinar.

January 17, 2025

For over a decade, the DORA research program has examined what distinguishes high-performing technology teams and organizations. Their four key metrics — lead time for changes, deployment frequency, change fail rate, and failed deployment recovery time — have become the industry standard for assessing software delivery performance. The 2024 Accelerate State of DevOps Report highlights the ongoing importance of developer experience, the rise of platform engineering, and how AI adoption affects software development across multiple levels.

Software developers across all industries increasingly depend on AI to minimize a wide range of repetitive tasks and boost team performance, security, and code quality — and over a third of developers report "moderate" to "extreme" productivity gains from using AI. However, effective change management and a comprehensive AI strategy are essential to address the challenges of early adoption, such as the AI training gap, “AI sprawl,”  a lack of trust in AI-powered tools, and the need for clear productivity metrics.

Creating a work environment where teams feel supported, valued, and motivated is crucial for achieving high performance and minimizing burnout. How can organizations ready their teams, processes, and cultures to harness the full potential of an AI strategy for driving innovation?
In this webinar, Derek DeBellis, lead researcher on Google's DORA team, and Stephen Walters, Field CTO at GitLab, reveal the latest research findings from the 2024 Accelerate State of DevOps DORA report, followed by an interactive Q&A.

Join us as we explore:

  • Benefits and challenges of AI adoption: Learn how AI boosts productivity, job satisfaction, retention, and code quality, while addressing potential roadblocks in early adoption.
  • Platform engineering and AI: Discover how platform engineering can elevate developer productivity and performance when combined with AI.
  • Measuring performance with AI: Understand how assessing the  right quantitative metrics can help organizations better understand AI's impact on business goals.
Key takeaways
  • DORA research underlines the significance of developer experience, the emergence of platform engineering, and AI's role in software development across various levels.
  • AI has proven effective in enhancing team performance across the software development process; however, a robust change management and comprehensive AI strategy are critical to counter early adoption challenges.
  • Creating a supportive, valued, and motivated workspace is key to high performance and mitigating burnout, making it essential for organizations to ready their teams for AI's innovative potential.