The automation shift: Why 64% of developers use AI agentic tools

Agentic AI, which refers to AI tools that act as autonomous agents rather than passive assistants, is transitioning from experimental use to everyday application in software development, with 64% of developers now integrating these tools into their workflows. This shift signifies a move from individual task execution by humans to a model where developers set goals and supervise autonomous systems executing complex processes. Developers are strategically deploying agentic AI in areas where it naturally excels, such as code documentation, automated test generation, and code review, although they remain cautious about using it for high-stakes tasks like security vulnerability patching. Despite the growing adoption, the effectiveness of AI agents varies by task, with documentation being the most effective and automated code review less so, highlighting ongoing concerns about the quality of AI-generated outputs. Smaller teams, particularly within small-to-medium businesses, are finding significant value in these tools as they act as force multipliers, enabling agile teams to undertake generative tasks efficiently. However, as agentic AI contributes more to codebases, there is an increasing need for robust verification processes to ensure code reliability and maintain code health, emphasizing that rapid code generation is only beneficial if accompanied by rigorous oversight and validation.