Artificial Intelligence for Business Optimization

Research and Applications

Bhuvan Unhelkar (University of South Florida), Tad Gonsalves

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Paperback

Forthcoming
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English

CRC Press
07 October 2024

Knowledge management; Operational research; Automatic control engineering; Enterprise software; Artificial intelligence

This book explains how AI and Machine Learning can be applied to help businesses solve problems, support critical thinking and ultimately create customer value and increase profit.

By considering business strategies, business process modeling, quality assurance, cybersecurity, governance and big data and focusing on functions, processes, and people’s behaviors it helps businesses take a truly holistic approach to business optimization. It contains practical examples that make it easy to understand the concepts and apply them.

It is written for practitioners (consultants, senior executives, decision-makers) dealing with real-life business problems on a daily basis, who are keen to develop systematic strategies for the application of AI/ML/BD technologies to business automation and optimization, as well as researchers who want to explore the industrial applications of AI and higher-level students.

By: Bhuvan Unhelkar (University of South Florida), Tad Gonsalves
Imprint: CRC Press
Country of Publication: United Kingdom
Dimensions: Height: 234mm, Width: 156mm,
Weight: 453g
ISBN: 9781032028866
ISBN 10: 1032028866
Pages: 288
Publication Date: 07 October 2024
Audience: Professional and scholarly , Undergraduate
Format: Paperback
Publisher's Status: Forthcoming

Foreword by Andy Lyman. Preface. Readers. Figures. Acknowledgments. Authors. 1 Artificial intelligence and machine learning: Opportunities for digital business. 2 Data to decisions: Evolving interrelationships. 3 Digital leadership: Strategies for AI adoption. 4 Machine learning types: Statistical understanding in the business context. 5 Dynamicity in learning: Smart selection of learning techniques. 6 Intelligent business processes with embedded analytics. 7 Adopting data-driven culture: Leadership and change management for business optimization. 8 Quality and risks: Assurance and control in BO. 9 Cybersecurity in BO: Significance and challenges for digital business. 10 Natural intelligence and social aspects of AI-based decisions. 11 Investing in the future technology of self-driving vehicles: Case study. Appendix A: Frameworks and libraries for ML. Appendix B: Datasets for ML and predictive analytics. Appendix C: AI and BO research areas. Index.