A recent Google DORA survey highlights the evolving role of AI coding tools in software development, revealing mixed effects on delivery speed and stability. Conducted among 5,000 respondents, the survey found a slight uptick in software delivery throughput and code quality, despite increased instability associated with AI adoption. Specifically, a 1.5% decrease in throughput and 7.2% drop in stability were noted for every 25% rise in AI adoption. While trust in AI remains a concern—30% of respondents expressed minimal trust—overall, productive relationships with AI tools seem to be improving. DORA identified seven best practices that organizations utilizing AI effectively share, including clear communication of AI strategies and a robust data ecosystem. As organizations adapt workflows to leverage AI’s capabilities, focusing on software quality and developer productivity becomes paramount. Understanding AI’s limits while integrating it thoughtfully can help mitigate stability challenges within software deliveries.
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