ADVANCEMENTS IN ARTIFICIAL INTELLIGENCE AND MACHINE LEARNING: A MULTIDISCIPLINARY APPROACH

Abstract

Artificial Intelligence (AI) and Machine Learning (ML) are driving a paradigm shift across sectors by offering data-driven, adaptive, and predictive capabilities that enhance decision-making and operational efficiency. Their integration into fields such as healthcare, finance, agriculture, education, and environmental monitoring has enabled transformative innovations that address both complex challenges and routine tasks with precision.This study employs a multidisciplinary methodology, combining supervised and unsupervised ML models with domain-specific datasets to evaluate the real-world impact of AI across five critical sectors. Techniques such as Convolutional Neural Networks, LSTM networks, Random Forests, and NLP models were implemented to perform diagnostics, forecast trends, detect anomalies, and provide personalized recommendations. A unified framework was adopted to ensure consistency in model training, validation, and interpretability, supported by SHAP and LIME for explainability.The results demonstrate that AI models consistently outperform traditional systems in diagnostic accuracy, financial forecasting reliability, agricultural yield prediction, student learning adaptability, and environmental risk assessment. High precision and recall scores were achieved across domains, highlighting the robustness of the selected algorithms. Visual analytics and performance metrics further validated the scalability and transparency of these models in real-world applications.The findings emphasize the critical role of cross-sectoral collaboration, ethical oversight, and policy reform in the deployment of AI technologies. Despite infrastructure and data accessibility challenges, particularly in developing regions, AI presents unprecedented opportunities for sustainable development and societal advancement. The research concludes that a multidisciplinary, ethically aligned AI deployment strategy is essential for maximizing impact while ensuring equitable access and responsible innovation..