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@article{185126,
        author = {Susmit Acharya and Soma Chakraborty},
        title = {Framework for Leveraging A.I. for Strategic Growth in Small-Scale Enterprises},
        journal = {International Journal of Innovative Research in Technology},
        year = {2025},
        volume = {12},
        number = {5},
        pages = {926-931},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=185126},
        abstract = {This research explores low-cost, AI-based business intelligence (AI-BI) platforms customized for Small Scale Enterprises around Kolkata, bridging infrastructure, budget, and digital preparedness constraints. With open-source machine learning software, an AI-BI dashboard prototype using Python libraries (Scikit-learn, XGBoost, FastAPI) was created and tested with synthetic data mimicking retail and manufacturing activities. Central functionalities were demand forecasting, churn prediction, and customer segmentation. Simulation evaluation revealed improved mean forecast accuracy by 35% and clearer segmentability of customers. Although the use of real business data for the models was not possible due to anonymity concerns considering the open-source nature of the research, the project contributes a reproducible, open-source platform design and evaluation framework. Results prove AI-BI adoption at scale as technically feasible in under-resourced contexts of SMEs and provide foundations for future field verifications.},
        keywords = {Robotics and Intelligent Machines; Machine Learning; Ai-Based Business Intelligence; Small-Scale Enterprises; Synthetic Data; Framework; Open-Source},
        month = {October},
        }