Software development models have been evolving significantly with the integration of artificial intelligence (AI), allowing for improvements in efficiency, quality, and new ethical and social perspectives. Traditional approaches, such as the waterfall model, agile development, and DevOps, are being complemented and sometimes transformed by AI. These approaches, some characterized by iterative cycles and continuous improvement, incorporate AI tools to automate tests, optimize deployments, and predict problems, facilitating failure prediction and efficient infrastructure management and improving continuous delivery and software quality. AI makes it possible to analyze large volumes of data to detect patterns and make accurate predictions, translated into predictive models to anticipate user needs, optimize performance, and personalize experiences. It also facilitates understanding user behaviors and preferences by analyzing usage data. This allows for creating more intuitive interfaces and continuously improving the user experience, dynamically adapting to their needs. AI systems are revolutionizing the automation of repetitive and complex tasks, from code generation to testing; AI tools can efficiently generate prototypes, perform automated code reviews, and conduct regression testing. With growing concerns about technology's social and ethical impact, developers are adopting approaches that incorporate fairness, transparency, and accountability in software development. AI is used to detect and mitigate bias in algorithms, ensure data privacy, and ensure ethical use of technology. This paper presents an extensive study about the impact of AI on software development focusing on the ethical and social challenges.