Artificial Intelligence Applications in Contemporary Multidisciplinary Research with Management Development

Abstract

Analysis Artificial intelligence can increase the analytical ability of multidisciplinary studies, but its role varies with the way institutions build the managerial judgment, integrate expertise, and test evidence. The literature based study looks at the applications in fields of scientific discovery, environmental analysis, social research and knowledge work in organizations. It links these applications to management development which becomes the purposeful enhancement of leadership potential, decision making and organizational learning. The choice of publications is examined in terms of a comparative framework discriminating between predictive performance, shown task benefits, and hypothetical outcomes in the institutions. The examples published support the fact that artificial intelligence can assist specialized prediction and improve some functions of knowledge; they do not insist on the improvement of the quality of research or managerial abilities in general. The main hypothesis is that technical capability can be converted to the practice of responsible research through a mediation process of management development. A proposed implementation framework, therefore, is a synthesis of disciplinary validation, shared responsibility of data, orchestrated experimentation and mindful learning. Three comparative tables are generated from this argument which represents application choices, evidence boundaries, and evaluation controls. The analysis provides a practical plan to evaluate the scientific utility as well as the further evolution of human experience. No primary survey, organizational intervention or computational experiment was carried out.