AI-Driven MBA Programs for Personalized Learning and Skill Development for Future Business Leaders

The possibility of including federal education (FL) into the master's degree in business administration programs is investigated in this paper in order to improve the personal learning and skills of forthcoming business leaders. The current educational system finds it difficult to adapt the traditional Master of Business Administration program to fit the demands of the corporate environment. Federated learning is based on the theory that one could distribute training models without a central database. One can provide this capacity using a technique of machine learning. This study intends to close a gap in the present Master of Business Administration curriculum by means of a fresh approach leveraging public education. This study seeks to identify how this method might be used to customise learning resources so that they satisfy the specific needs of every student while maintaining anonymity and security. This paper intends to understand the effects of FL-oriented self-learning on cognition and well-being by means of a mixed-method research comprising qualitative and quantitative data respectively. The results of the experiment will provide interesting information on the practicability and benefits of using state education under the Master of Business Administration degree. This study is supposed to be the foundation for significant changes in business education, hence ensuring that future business leaders have the tools needed to succeed in a professional transition.