How Machine Learning Is Changing Software Development Workflows
Machine Learning (ML) is no longer limited to data science teams or experimental projects. In today’s digital-first world, machine learning is transforming how software is designed, developed, tested, deployed, and maintained . Modern development workflows are becoming faster, smarter, and more adaptive as ML-driven tools automate repetitive tasks, improve code quality, and enable data-driven decision-making. This article explores how machine learning is reshaping software development workflows , the key areas of impact, real-world benefits, and what development teams must do to adapt. Read More: The Rising Value of Human Expertise in an AI-Driven Workflow The Evolution of Software Development Workflows Traditional software development workflows relied heavily on manual processes—handwritten code reviews, static testing, rule-based automation, and human-driven decision-making. While effective, these approaches often struggled with scalability, speed, and complexity. Machine le...