Integrating AI for Intelligent Automation: A ...

Integrating AI for Intelligent Automation: A Paradigm Shift in Software Engineering Practices for Optimizing Development Lifecycles

Author Name : Manoj Bhoyar

ABSTRACT Applying AI to software engineering processes puts software development life cycles in an intelligent automation era, thus creating a paradigm shift. This paper seeks to demystify how AI tools and techniques have revolutionized software development to be faster, more reliable, and more productive. More conventional mechanisms that are tedious, time-consuming, and occasionally error-prone are increasingly giving way to AIfirst approaches to code generation, debugging and testing, and continuous integration and deployment. This results in superior quality in developed software and enhanced project management since AI cuts out a lot of time that would otherwise be spent on repetitive tasks, could involve a lot of errors, and cost a whole lot more to undertake. The paper also presents real-life examples of AI implementation and its most efficient use in different fields. These case studies show how the application of AI can address the persistent issues of software engineering with real examples that have evolved as solutions While providing perspective on the barriers of AI, including technical ones, ethical issues, and the idea of human supervision. Furthermore, possible trends for the hypothetical future new product include characteristics such as integrating predictive analytics and AI in project management. In the future, as the software engineering world grows, AI-based intelligent automation will become a new standard for development life cycles, providing an opportunity for improvement. This paper offers a systematic review of this transition; it presents information on both the current and potential use of AI in software engineering processes and explores its role in changing the current development lifecycle into intelligent systems.