Decoding AI : Practical Implementations for Business Operations

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Decoding AI : Practical Implementations for Business Operations

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  • 製本 Paperback:紙装版/ペーパーバック版/ページ数 360 p.
  • 言語 ENG
  • 商品コード 9781032999685

Full Description

Business operations today show evidence of profound DNA-level transformations brought about by existing artificial intelligence technology. Decoding AI: The essential book 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 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 operational greatness.

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.

Contents

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

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