Overview

The integration of AI and machine Learning into business education has developed a more efficient way of training future leaders. These technologies enhance the curriculum design and equip students with critical and analytical decision skills for today s fast paced business environment. AI and machine learning tools foster experiential learning and bridge the gap between theory and practice. As industries increasingly rely on automation and predictive analytics, embedding these technologies into business education is not just innovative, it is imperative for preparing agile, tech-savvy professionals capable of navigating complex organizational challenges. Integrating AI and Machine Learning into Business and Management Education explores how the transformative capabilities of AI and machine learning can be effectively integrated into management education. This book encourages the adoption of AI for personalized learning and advanced problem-solving in management training. Covering topics such as education, AI, and management, this book is an excellent resource for academicians, researchers, corporate trainers, graduates, and policymakers.

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Manjunath B R holds a Ph.D. in Finance with a specialization in the performance evaluation of Indian and Australian mutual fund schemes, awarded by Davangere University in 2019. He currently serves as the Professor of Finance & Analytics and Director of Academic Affairs at the School of Business Management, Shoolini University, Solan, Himachal Pradesh, India. Dr. Manjunath is also a Global Visiting Professor at Tecnológico de Monterrey, Mexico, where he lectures on finance and analytics. With over 16 years of combined academic and industry experience, Dr. Manjunath has made significant contributions to the fields of business analytics, finance, and management education. His research interests include data science applications in finance, econometrics, and business analytics. He has authored over 88 peer-reviewed research papers indexed in ABDC, Scopus, and UGC journals, focusing on applied finance, analytics, and business decision-making. Dr. Manjunath has designed and delivered various workshops, faculty development programs, and management development programs on topics such as financial econometrics, data visualization, and advanced business analytics. He has extensive expertise in using tools like Python, R, Tableau, and EViews for business and financial data analysis. His innovative teaching approaches emphasize experiential learning and bridging the gap between academic theory and industry practice. Dr. Manjunath's academic excellence has been recognized with several accolades, including the MTC Global Award for Global Education Ambassador and multiple best research paper awards. He is also the author of an upcoming textbook, Machine Learning and Deep Learning, slated for publication in 2024. His commitment to advancing education and research makes him a valuable contributor to the ongoing discourse on integrating AI, machine learning, and analytics in business and management education. Sunil Kumar is an Associate Professor at the Faculty of Management Sciences, Shoolini University, India, brings over 15 years of experience in teaching, academic research, eLearning, and educational quality management. Dr. Kumar’s teaching repertoire spans various subjects, including Human Resource Management (HRM), HR Analytics, Organizational Behavior, and Industrial Psychology. His research portfolio features 50 publications in prominent journals like the International Journal of Educational Management and the Journal of Workplace Learning, with his studies often revolving around employee competencies, mindfulness in the workplace, and the impact of technology on organizational efficiency. He has presented his research at international conferences and received awards for his contributions. Dr. Kumar has authored several book chapters and edited volumes on topics such as healthcare management and organizational behavior. He has also secured copyrights for various research models, including frameworks for e-training and AI-based tools for organizational development. His ongoing research interests include AI in recruitment and employee resilience, and he is actively involved in supervising PhD candidates. Furthermore, Dr. Kumar’s editorial and reviewer roles in academic journals highlight his influence in the broader academic community.

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