AI In Modern Software Development: Current Practices, Challenges and Future Possibilities
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Artificial Intelligence is fast emerging as an inseparable part of software engineering. Its impact on
modern software development is significantly high. Though writing code or to be more precise, generating
code through AI systems and tools facilitates the development of a wide variety of products, there are
ethical considerations, risks, and limitations that ultimately affect the overall quality of the software. This
research paper highlights how AI is used in modern software design, development, testing, security, and
management processes and they are flawlessly streamlined for enhanced productivity and quality. The
research describes how AI is important in software engineering as firms without employing AI in SDLC are
susceptible to underperforming. It provides insights into, what it could help with in terms of developing modern and scalable applications, and the ethics involved in AIdriven software engineering. It also highlights
limitations underlying the applications of AI in the past, present, and future.
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2025-01-23Artificial Intelligence is fast emerging as an inseparable part of software engineering. Its impact on modern software development is significantly high. Though writing code or to be more precise, generating code through AI systems and tools facilitates the development of a wide variety of products, there are ethical considerations, risks, and limitations that ultimately affect the overall quality of the software. This research paper highlights how AI is used in modern software design, development, testing, security, and management processes and they are flawlessly streamlined for enhanced productivity and quality. The research describes how AI is important in software engineering as firms without employing AI in SDLC are susceptible to underperforming. It provides insights into, what it could help with in terms of developing modern and scalable applications, and the ethics involved in AIdriven software engineering. It also highlights limitations underlying the applications of AI in the past, present, and future.