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@article{191218,
        author = {Dr Amit R Popat},
        title = {AI's Transformative Impact on Applied Statistics},
        journal = {International Journal of Innovative Research in Technology},
        year = {2026},
        volume = {12},
        number = {8},
        pages = {6262-6264},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=191218},
        abstract = {Applied statistics has traditionally provided systematic tools for data collection, analysis, interpretation, and inference in real-world contexts. However, the exponential growth of large, high-dimensional, and unstructured datasets has challenged the limitations of classical statistical methods. Artificial Intelligence (AI), particularly machine learning and deep learning, has emerged as a powerful extension to applied statistics, enabling advanced modeling, automation, and predictive accuracy. This paper presents a comprehensive conceptual and analytical review of the role of artificial intelligence in applied statistics. It examines theoretical linkages between AI and statistical foundations, reviews significant literature, discusses applications across healthcare, education, business, economics, and social sciences, and highlights ethical and methodological challenges. The study concludes that AI, when integrated with sound statistical reasoning, significantly enhances applied statistical analysis while requiring responsible governance to address transparency, bias, and ethical concerns.},
        keywords = {Artificial Intelligence, Applied Statistics, Machine Learning, Statistical Learning, Predictive Analytics, Ethics},
        month = {January},
        }