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@article{192780,
        author = {Kajin Karunakaran and Chandni K Nair},
        title = {The Impact of AI on Code and Productivity: A Case Study of GitHub Copilot Adoption in a Large Enterprise},
        journal = {International Journal of Innovative Research in Technology},
        year = {2026},
        volume = {12},
        number = {9},
        pages = {1970-1973},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=192780},
        abstract = {Artificial Intelligence (AI) tools are increasingly integrated into software development workflows, promising significant productivity gains and reshaping organizational practices. This article presents our practical experiences with GitHub Copilot (GHCP) in a large-scale enterprise environment. We highlight measurable improvements in development speed, collaboration across developer and non-developer roles, and innovations in code review and tool development, which we have experienced within our organization. At the same time, we discuss challenges encountered when applying AI-assisted coding to large-scale legacy systems. We also demonstrate how GenAI catalyzed internal innovation— supporting POCs, legacy modernization, domain specific copilots, and full-fledged AI assistants. These insights provide empirical evidence that AI not only accelerates coding but also redefines roles, workflows, and organizational learning.},
        keywords = {Generative AI, GitHub Copilot, Impact of AI, Productivity, Software Development.},
        month = {February},
        }