Measuring the Impact of AI on Software Engineering Productivity
SMRTR summary
AI-assisted coding tools have transformed software engineering since GitHub Copilot's 2021 launch. With 75% of developers using AI tools and 90% enterprise adoption expected by 2028, these technologies are reshaping development practices. Key uses include prototyping, code generation, and automation. While AI promises increased productivity, measuring its impact remains challenging. Metrics like throughput, delivery speed, code quality, and team health are crucial for evaluating AI's effectiveness. Organizations must develop strategies to maximize AI's benefits and ensure positive business outcomes.
SMRTR provides this summary for quick context. The original article belongs to DZone.
Read the original article