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All Journal Blockchain, Artificial Intelligence, and Future Research
Liza Matic Tamargo
Ifugao State University (Phillipines)
Computer Science & IT

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The Future of Management Learning: AI-Powered Pedagogies and Adaptive Strategy Implementation Rajkumar; Melba Kabelele Sitwala; Mohamed Abdel-Raheem; Liza Matic Tamargo; Rajendran K.V.
Blockchain, Artificial Intelligence, and Future Research Vol. 1 No. 2 (2025): November 2025
Publisher : WISE Pendidikan Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70211/bafr.v1i2.316

Abstract

This study explores the role of artificial intelligence (AI) in transforming management education and strategic decision-making, focusing on AI-powered pedagogies and adaptive strategy implementation. The research investigates how AI can personalize learning experiences through intelligent tutoring systems, predictive analytics, and real-time feedback mechanisms, thereby enhancing engagement, retention, and critical thinking skills essential for modern management roles. Additionally, the study examines AI’s potential to support organizations in implementing adaptive strategies through real-time data analytics, allowing for proactive decision-making and agile responses to market dynamics. The study proposes a conceptual framework that integrates AI-driven learning with adaptive strategy tools, aiming to enhance both management learning outcomes and organizational agility. Based on a systematic literature review, the findings underscore the significance of AI in both educational and organizational contexts. However, challenges such as data privacy concerns, algorithmic bias, and the need for AI expertise remain critical barriers to broader adoption. This study contributes to the growing body of knowledge on AI applications in management, offering insights into its potential to revolutionize both learning and strategic processes. The findings highlight the need for further empirical research to validate the proposed framework and explore its practical implementation.
Co-Authors Melba Kabelele Sitwala Mohamed Abdel-Raheem Rajendran K.V. Rajkumar