Overview

This edited volume explores AI-driven digital transformation from the perspective of a well-established higher education institution. Featuring 23 chapters organized into six thematic areas - Decision Support, Data Processing, Marketing and Product Development, Supply Chains, Finance, and Foundational Issues - it provides practical examples of how business school departments can implement AI to foster innovation.

Each chapter presents accessible case studies demonstrating AI applications in business, highlighting both benefits and risks. The volume bridges the gap between AI advancement and practical industry needs, offering actionable insights for integrating AI into decision-making, organizational processes, and curriculum development.

Key Contributions

Key contributions include demonstrating AI as a strategic enabler, positioning business schools as catalysts for change, recognizing sector-specific impacts, emphasizing ethical foundations, and promoting collaboration between academia, industry, and policymakers.

This comprehensive resource equips educators and decision-makers with the knowledge and methods necessary to thrive in the era of AI-driven innovation and serves as a strategic blueprint for business schools to lead AI-driven transformation while maintaining ethical considerations.

Target Audience

AI-Driven Digital Transformation will appeal to scholars and students of AI, technology, innovation management, and business education. It will also be of interest to business school leaders responsible for institutional strategies, educators creating study programs, curriculum specialists, and business leaders seeking AI implementation guidance within their expertise areas.