Measuring Developer Productivity in AI-Powered Software Development

AI-assisted development is rapidly becoming the norm, with 78% of surveyed executives and IT professionals currently using AI in software development or planning to do so within the next two years, up from 64% in 2023. This increase is largely due to AI’s ability to generate code and offer suggestions, significantly speeding up software development and deployment cycles.

Accelerated Development and Onboarding Challenges

Despite the hyper-productivity enabled by AI, measuring its impact remains a challenge for IT managers and business leaders. GitLab's survey of 5,315 executives and IT professionals revealed that 67% of respondents have mostly or completely automated their software development lifecycle. Furthermore, 69% of executives report shipping software twice as fast as the previous year. However, onboarding new developers is taking longer, with 52% stating it now takes more than three months, up from 42% the previous year.

Executive Concerns About AI

Executives are more cautious about integrating AI into the software development lifecycle than their staff members. A majority (56%) express concerns about privacy and data security, compared to only 40% of IT professionals. Additionally, 35% of executives worry about a lack of appropriate AI skills, whereas only 26% of IT professionals share this concern.

Benefits of AI in Onboarding

Respondents using AI for software development report faster onboarding times, with 43% indicating it takes less than a month, compared to 20% of those not using AI. The same trend is observed with DevSecOps platform usage, where 44% of users report onboarding within a month, compared to 20% without a platform.

Popular AI Applications in Development

The survey highlights several key uses of AI in development:

• Code generation and suggestion: 47%

• Explanations of code functionality: 40%

• Summaries of code changes: 38%

• Chatbots for natural language documentation queries: 35%

• Summaries of code reviews: 35%

Future AI Applications Desired

IT professionals and managers want AI to assist in:

• Forecasting productivity metrics and identifying anomalies: 38%

• Explaining vulnerabilities and remediation steps: 37%

• Chatbots for documentation queries: 36%

• Suggesting code reviewers: 34%

• Fixing failed pipeline jobs: 31%

Software Supply Chain Security

Software supply chain security remains a concern, with 67% of professionals reporting that at least a quarter of their code comes from open-source libraries. However, only 21% of organizations currently use a software bill of materials (SBOM) to document their software composition.

Challenges in Measuring Developer Productivity

Executives acknowledge the critical importance of developer productivity but struggle with measurement. Slightly more than half (51%) admit their current methods are flawed or are unsure how to measure productivity. Additionally, 45% are not measuring productivity against business outcomes.

A majority (55%) agree that developer productivity is important, and 57% believe measuring it is key to business growth. Despite this, only 42% are satisfied with their current measurement approach, while 36% find their methods flawed, and 15% are unsure how to measure productivity.