GENERATIVE ARTIFICIAL INTELLIGENCE AND THE FUTURE OF SOFTWARE ENGINEERING: TRANSFORMING SOFTWARE DEVELOPMENT, TESTING, AND INTELLIGENT AUTOMATION

Abstract

This study examined the role of generative artificial intelligence in transforming software engineering, particularly software development, testing, and intelligent automation. A descriptive mixed-method research design was used, and data were collected from a sample of 120 respondents, including software developers, software testers, software engineering students, system analysts, project managers, and DevOps or automation engineers. The results showed strong awareness of generative AI among respondents. Generative AI as a tool for faster software development recorded a mean score of 4.28, while its role in changing the future role of software engineers also recorded 4.28. Code completion was the most adopted AI activity, with a mean score of 3.27, followed by code generation with 3.22, documentation writing with 3.07, debugging support with 3.03, test-case generation with 2.93, and DevOps automation with 2.78. The strongest perceived benefit was increased developer productivity, with a mean score of 4.32, followed by reduced repetitive coding tasks with 4.25 and faster software delivery with 4.18. The major challenge was inaccurate AI-generated code, with a mean score of 4.28, followed by security vulnerabilities with 4.23 and overdependence on AI tools with 4.17. These findings suggested that adoption was strongest in routine coding tasks and weaker in advanced automation areas. The study concluded that generative AI supported faster, smarter, and more automated software engineering, but human supervision, training, policy guidance, and security validation remained essential for reliable professional practice.

Keywords :  Automation, Code generation, Generative artificial intelligence, Intelligent testing, Software development, Software engineering.