The rapid progress of artificial intelligence, which appoints algorithms based on deep learning and machine learning to automate various types of procedures, has suppressed software development. This chapter examines the role of ML/DL technology in AI-driven software development, focusing on their application in code construction, bug identity, program adaptability and future maintenance. The efficiency of the important ML and DL models in automatic development processes is examined, including the decision trees, nervous networks, transformers, and generic models. There is also a discussion of such moral issues, model interpretation and difficulties in data quality. This study demonstrates AI’s ability to increase productivity, reduce the time of development and increase software reliability by providing insights into ML/DL-Interactive Automation.