The book explores AI model types including Large Language Models and multimodal embeddings alongside reinforcement learning and decision-priming simulations while discussing their impact on finance and marketing alongside healthcare and customer service and fraud detection and personalized commerce functions.
Business operations today show evidence of profound DNA-level transformations brought about by existing artificial intelligence (AI) technology. Decoding AI: Practical Implementations for Business Operations reveals real artificial intelligence potentials through practical insights and innovative frameworks, and transformative case studies that operate across different business sectors.
The book explores AI model types, including large language models (LLMs) and multimodal embeddings alongside reinforcement learning and decision-priming simulations while discussing their impact on finance and marketing alongside healthcare and customer service, and fraud detection and personalized commerce functions. Through its blend of academic AI knowledge and practical business insights, the content enables readers to understand complex algorithms better while achieving improved operational facility.
Key highlights include:
- Ethical frameworks for responsible AI and human-aligned intelligence
- Data-centric strategies to improve transparency, explainability, and governance
- Domain-specific innovations in pricing, negotiation modeling, and behavioral prediction
- Real-world case studies demonstrating the transformative power of AI in decision-making
- A special focus on the integration of AI in strategic, financial, and customer-facing functions
Whether you’re a C-suite executive, startup founder, researcher, academician, or tech enthusiast, this book is designed to equip you with both the strategic vision and technical foundation to embrace AI confidently in your business journey.
Let this volume be your guide in navigating the evolving AI landscape — not just to keep up with innovation, but to lead it.
Chapter 1: The Silent Revolution: How AI is Rewriting the Rules of
Organizational Power
Chapter 2: Equitable AI: Aligning Human Expertise with
Algorithmic Value
Chapter 3: Responsible AI: Mitigating Ethical Concerns and
Promoting Decent Work
Chapter 4: Evaluating LLMs as Facilitators and
Moderators in Strategic Sessions: An Expert-Driven Framework for Enhancing
Small Group Intellectual Efforts
Chapter 5: Multimodal Embeddings for
Predicting States of Negotiators, Their Changes and Contents
Chapter 6:
Simulating Dynamics of the Recognition-Primed Decision Model on Financial
Markets Using LLM
Chapter 7: AI and Finance: Redefining Risk Analysis Through
Advanced Technologies
Chapter 8: AI in Financial Fraud Detection and
Prevention
Chapter 9: The Role of AI in Combating Financial Fraud: A Case
Study Perspective
Chapter 10: Neural Correlates of Impulse Buying: A Causal
AI Approach to Consumer Preference Reversals
Chapter 11: Instantaneous
Personalization in E-Commerce: A Reinforcement Learning Approach with
Language Model Enhancement for User Agnostics for T-Shirt Recommendations
Chapter 12: Enhancing Investable Art Market Accessibility and Explainability
through Data-Centric AI Techniques
Chapter 13: AI-Powered Customer Service:
Enhancing User Experience with Chatbots and Virtual Assistants
Chapter 14:
Case Study on AI-Powered Healthcare: Improving Patient Outcomes with
Predictive Analytics
Chapter 15: Case Study on Implementing AI for Dynamic
Pricing in the Hospitality Industry
Dr. Hemachandran K has been a passionate teacher with 14 years of teaching experience and five years of research experience. A strong educational professional with a scientific bent of mind, highly skilled in AI & ML. After receiving a Ph.D. in embedded systems at Dr. MGR Educational & Research Institute, India. He started doing interdisciplinary research in AI. An open-ended positive person who has stupendous peer-reviewed publication records with more than 20 journals and international conference publications. He was an effective resource at various national and international scientific conferences. His editorial skills have included him as an editorial board member in numerous reputed SCOPUS / SCI journals.
Dr. Raul Villamarin Rodriguez is the Pro-Vice-Chancellor, Woxsen University, and Dean of the School of Business at Woxsen University. He holds a Ph.D. in Artificial Intelligence and Robotics Process Automation applications in Human Resources. Fmr. Co-CEO at Irians Research Institute, a research institute specializing in the field of neuromarketing, AI, ML, market research, behavioral science, social research, and behavioral engineering. His areas of expertise and interest are Machine Learning, Deep Learning, Natural Language Processing, Computer Vision, Robotic Process Automation, Multi-agent Systems, Knowledge Engineering, and Quantum Artificial Intelligence. He has experience and feels comfortable using Prolog, Java, C++, Python, R/RStudio, Julia, Swift, Scala, MySQL, and Spark, among others. He is a registered expert in Artificial Intelligence, Intelligent Systems, and Multi-agent Systems at the European Commission, a nominee for the Forbes 30 Under 30 Europe 2020 list, and an awardee in the Europe India 40 Under 40 Leaders. Alongside this, he is a member of the GRLI Deans and Directors cohort. He has co-authored two reference books: New Age Leadership: A Critical Insight and Retail Store, and has more than 70 publications to his credit. He is a weekly contributing writer to various magazines in the field of analytics and emerging technologies. Alongside this, he is a journal reviewer and associate editor in various publications such as IEEE.
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