Artificial Intelligence Applications in Multidisciplinary Research: A Theoretical Review

Abstract

Artificial Intelligence (AI) has become a revolution in multidisciplinary research because it enhances the analysis of data, pattern recognition, predictive modeling and integration of cross-disciplinary knowledge. The theoretical and practical role of AI in the various fields of research is reviewed in the paper with specific interest in the fields of healthcare, environmental science, and research productivity. The systematic review methodology that the study employs based on the PRISMA principles synthesizes existing literature in the field of the role of AI in interdisciplinary collaboration, discovery acceleration, and efficient research process optimization. It has been found that AI can play an important role in managing large and complex data, automating analysis, providing real-time monitoring and assisting decision-making in various areas of science. The review also brings out the fact that AI can be particularly helpful with complex global problems, which entail collaboration across disciplinary lines. Simultaneously, the research considers such obstacles as the methodological dissimilarity, coordination problems, and the necessity of ethical and responsible AI usage in the research. In general, it can be concluded that AI is not merely a technological tool but a strategic facilitator of innovation in multidisciplinary research and has a high potential of more integrated, scalable, and effective knowledge production in the future.