Unleashing AI : Harnessing Artificial Intelligence for Business Success.

Format:

Book

Author/Creator:

Frankl, Milan.

Series:

Big data, business analytics, and smart technology collection.

Big data, business analytics, and smart technology collection

Language:

English

Physical Description:

1 online resource (342 pages)

Edition:

1st ed.

Other Title:

Unleashing artificial intelligence

Place of Publication:

New York : Business Expert Press, 2025.

System Details:

Mode of access: World Wide Web.

System requirements: Adobe Acrobat reader.

Summary:

Unleashing AI: Harnessing Artificial Intelligence for Business Success is a comprehensive guide for business leaders, professionals, and entrepreneurs looking to understand and leverage the transformative potential of AI technologies. Unleashing AI is an actionable resource that equips the readers with the knowledge and strategies to harness the power of AI for competitive advantage. This book goes beyond the hype and technical jargon, offering a clear and accessible exploration of AI's applications, implementation challenges, and ethical considerations. It reviews the fundamental concepts of AI, its applications across various business functions, and the ethical considerations associated with its deployment. Through detailed chapters and practical insights, readers will gain a deep understanding of how to integrate AI into their business strategies to drive innovation, efficiency, and competitive advantage. By combining expert insights, and practical frameworks, Unleashing AI empowers readers to navigate the AI landscape, identify opportunities, and develop effective AI strategies aligned with their business goals.

Contents:

Frontcover

Half title

Title

Copyright

Description

Contents

Acknowledgments

Introduction

The AI Revolution in Business

AI: More Than Just Automation

The Democratization of AI

Navigating the AI Landscape

Looking Ahead

What Is Artificial Intelligence

What Is Human Intelligence?

Intelligence Relevant to Business Applications

The Distinction Between Data, Information, Knowledge, and Wisdom

DIKW: Definitions, Characteristics, Examples, and Role in AI

Summary

AI and Consciousness

Ready for an AI Definition?

PART 1 AI Fundamentals for Business

Chapter 1 Understanding AI Technologies

Chapter 2 AI Data and Algorithms: The Building Blocks of Intelligent Systems

Chapter 3 The AI Ecosystem

CHAPTER 1 Understanding AI Technologies

What Is Machine Learning

The Basics of Machine Learning

How Does Machine Learning Work

Types of Machine Learning

Business Applications

Neuromorphic Computing

Key Advancements

Quantum Machine Learning

Real-World Applications of Machine Learning

The Power and Limitations of Machine Learning

The Future of Machine Learning

What Is Deep Learning

The Basics of Deep Learning

How Does Deep Learning Work

What Makes Deep Learning Special

Challenges and Limitations of Deep Learning

The Future of Deep Learning

Some Key Real-World Examples of Deep Learning in use Today

What Is Natural Language Processing

The Basics of Natural Language Processing

How Does Natural Language Processing Work

Real-World Applications of Natural Language Processing

The Power and Limitations of Natural Language Processing

The Future of Natural Language Processing

What Is Computer Vision.

The Basics of Computer Vision

How Does Computer Vision Work

Real-World Applications of Computer Vision

The Power and Limitations of Computer Vision

The Future of Computer Vision

What Is Robotic Process Automation

The Basics of Robotic Process Automation

How Does Robotic Process Automation Work

Real-World Applications of Robotic Process Automation

The Power and Limitations of Robotic Process Automation

The Future of Robotic Process Automation

CHAPTER 2 AI Data and AlgorithmsThe Building Blocks of Intelligent Systems

The Importance of Data for AI

Data: The Lifeblood of AI

Quality Matters: The Need for High-Quality Data

Diversity: Representing the Real World

Abundance: More Data Equals Better Performance

Impact on AI System Performance and Reliability

Types of Data for AI Applications

Structured Data

Examples

Applications

Challenges

Preparation

Unstructured Data

Semistructured Data

Time-Series Data

Collecting and Preparing Data for AI

Data Collection

Data Cleaning

Data Annotation

Data transformation

AI Algorithms Explained

AI Algorithms Explained: How Machines Learn and Make Decisions

Supervised Learning Algorithms

How It Works

Common Supervised Learning Algorithms

Unsupervised Learning Algorithms

Common Unsupervised Learning Algorithms

reinforcement Learning Algorithms

Common reinforcement Learning Algorithms

Deep Learning Algorithms

Common Deep Learning Algorithms Architectures

Ensemble methods

Common Ensemble methods

Collaborative Filtering (Unsupervised Learning).

Content-Based Filtering (Supervised Learning)

Deep Learning

Reinforcement Learning

Evaluating AI Model Performance

Why Evaluating AI Model Performance Is Important

Key Metrics for Evaluating AI Models

For Classification models

For regression models

techniques for Evaluating AI models

Interpreting AI model Performance

CHAPTER 3 The AI Ecosystem

AI Hardware and AI Cloud Computing Powering the Future of AI

The Synergy of Hardware and Cloud

Challenges and Future Directions

AI Software Platforms and Tools: The Engines of AI Development

Development Environments and Platforms

AI Frameworks and Libraries

machine Learning operations (mLops) Platforms

The Evolution and Future of AI Software Platforms

AI Service Providers

Tech Giants Leading the Charge

Specialized Start-Ups Making Waves

The Role of AI-as-a-Service (AIaaS)

Making AI More Accessible

PART 2 Harnessing AI Across Business Functions

Chapter 4 Covers Marketing and Sales

Chapter 5 Covers Operations and Supply Chain

Chapter 6 Covers Finance and Accounting

Chapter 7 Covers Human Resources

Chapter 8 Covers the Health Care Industry

Chapter 9 Covers the Entertainment Industry

CHAPTER 4 AI for Marketing and Sales Revolutionizing Customer Engagement and Business Growth

Predictive Analytics for Marketing Campaigns

Conversational AI and Chatbots

AI for Customer Segmentation and Personalization

Sales Forecasting With AI

What Is Predictive Analytics

How Does Predictive Analytics Work

Predicting Customer Behavior

finding the Best Marketing Channels

timing Is Everything

Making data-driven decisions

Real-World Examples

Challenges and Considerations

The Future of Predictive Analytics in Marketing

Implementing Predictive Analytics.

Summary

Instant, 24/7 Customer Support

Handling Inquiries and Resolving Issues

Facilitating Purchases

Advancements in Natural Language Processing

Enhancing Customer Experience

Freeing up Human Resources

AI-Powered Customer Segmentation and Personalization

The Power of AI in Customer Segmentation

How AI Analyzes Customer data

Creating Microsegments

Personalization: Beyond Basic Segmentation.

tailored Content

Product recommendations

Personalized offers

Benefits of AI-Powered Segmentation and Personalization

The Importance of Accurate Sales Forecasting

Why Accurate Sales Forecasting Matters

How AI-Powered Sales Forecasting Works

Historical data Analysis

Complex Variables

Seasonality

Valuable Insights for Strategic decision Making

AI Sales Forecasting Tools

CHAPTER 5 AI in Operations and Supply Chain Transforming Business Efficiency and Resilience

Predictive Maintenance: Revolutionizing Equipment Upkeep

How AI Predictive Maintenance Works

Benefits of AI Predictive Maintenance

Real-World Applications

Future Trends

Demand Forecasting: Revolutionizing Supply Chain Management

Why Accurate Demand Forecasting Matters

How AI Is Improving Demand Forecasting

processing Complex datasets

Real-Time Analysis

pattern recognition

Handling Uncertainty

Practical Applications of AI in Demand Forecasting

Benefits of AI-Powered Demand Forecasting

The Future of AI in Demand Forecasting

AI-Powered Inventory Optimization: Striking the Perfect Balance

The Inventory Challenge

How AI Is Revolutionizing Inventory Management

Analyzing Complex datasets.

predictive Analytics

real-time Adjustments

Multivariable Optimization

Practical Applications of AI in Inventory Optimization

Benefits of AI-Powered Inventory Optimization

The Future of AI in Inventory Optimization

AI Revolutionizes Logistics: The Rise of Smart Warehouses

AI-Powered Robots

Automated Guided Vehicles (AGVs)

Intelligent Storage Systems

Route Planning and Optimization

Load Optimization

Last-Mile Delivery

The Benefits of AI in Logistics

The Future of AI in Logistics

AI Routing: Paving the Way for Efficiency

The Challenge of Route Planning

How AI Transforms Route Planning

Processing Vast Amounts of Data

dynamic route Adjustment

predictive Analytics

Multiobjective Optimization

delivery Services

Supply Chain Logistics

Factory Operations

Benefits of AI-Powered Route Optimization

The Future of AI in Route Optimization

CHAPTER 6 AI in Finance and Accounting

AI for Fraud Detection

Analyzing Transactional Data

Behavioral Data Analysis

Identifying Subtle Patterns and Anomalies

Real-Time Detection and Swift Response

Continuous Learning and Adaptation

AI-Powered Automation in Finance and Accounting

What Is AI-Powered Automation?

Streamlining Data Entry

Enhancing Reconciliation

Simplifying Report Generation

Improving Efficiency and Reducing Errors

Freeing up Human Workers for Strategic Activities

AI-Powered Financial Forecasting and Risk Analysis

Understanding Predictive AI Models

Enhancing Financial Forecasts

Processing Historical Data

Incorporating Real-Time Information

Projecting Future Trends.

Highlighting Areas of Concern Providing Deeper Insights Into AI Potential Risks.

Notes:

Includes bibliographical references and index.

Description based on publisher supplied metadata and other sources.

ISBN:

1-63742-801-4

OCLC:

1518284740