Unleashing AI

Name: Unleashing AI | Harnessing Artificial Intelligence for Business Success
Brand: Business Expert Press
Price: 17.49 EUR
Availability: OnlineOnly

Harnessing Artificial Intelligence for Business Success

Milan Frankl(Autor*in)

Business Expert Press

Erschienen am 20. Mai 2025

340 Seiten

E-Book

ePUB mit Wasserzeichen-DRM

Systemvoraussetzungen

978-1-63742-801-6 (ISBN)

17,49 €inkl. 7% MwSt.

Systemvoraussetzungen

für ePUB mit Wasserzeichen-DRM

E-Book Einzellizenz

Als Download verfügbar

Beschreibung

Weitere Details

Weitere Ausgaben

Person

Inhalt

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?
Summary
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
Business Applications
Quantum Machine Learning
Key Advancements
Business Applications
Real-World Applications of Machine Learning
The Power and Limitations of Machine Learning
The Future of Machine Learning
Summary
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
Summary
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
Summary
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
Summary
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
Summary
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
Summary
Types of Data for AI Applications
Structured Data
Examples
Applications
Challenges
Preparation
Unstructured Data
Examples
Applications
Challenges
Preparation
Semistructured Data
Examples
Applications
Challenges
Preparation
Time-Series Data
Examples
Applications
Challenges
Preparation
Collecting and Preparing Data for AI
Data Collection
Data Cleaning
Data Annotation
Data transformation
Summary
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
How It Works
Common Unsupervised Learning Algorithms
reinforcement Learning Algorithms
How It Works
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
Summary
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
Summary
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
Summary
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
Summary
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
Summary
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
Conversational AI and Chatbots
Instant, 24/7 Customer Support
Handling Inquiries and Resolving Issues
Facilitating Purchases
Advancements in Natural Language Processing
Enhancing Customer Experience
Freeing up Human Resources
Summary
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
Challenges and Considerations
Summary
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
Summary
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
Challenges and Considerations
Future Trends
Summary
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
Challenges and Considerations
The Future of AI in Demand Forecasting
Summary
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
Challenges and Considerations
The Future of AI in Inventory Optimization
Summary
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
Challenges and Considerations
The Future of AI in Logistics
Summary
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
Real-World Applications
delivery Services
Supply Chain Logistics
Factory Operations
Benefits of AI-Powered Route Optimization
Challenges and Considerations
The Future of AI in Route Optimization
Summary
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
Summary
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
Summary
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
Identifying Risk Factors
Assessing Probability and Impact
Stress Testing and Scenario Analysis
AI Advantages Over Traditional Methods
Summary
AI-Driven Investment Strategies in Finance and Accounting
Optimizing Investment Portfolios
Analyzing Historical data
Predicting Future Performance
continuous optimization
Developing Sophisticated Trading Strategies
Rapid Market Analysis
Identifying opportunities
Speed and Precision
Benefits of AI-Driven Investment Strategies
Summary
CHAPTER 7 AI for Human Resources
The Changing Dynamics of the AI-Human Workforce
AI for Talent Acquisition and Hiring
Employee Training and Development With AI
AI for Workforce Analytics and Planning
AI for Improving Employee Engagement
Enhancing Talent Acquisition With AI: A Game Changer for HR
Automating Resume Screening
Matching Skills and Experiences
Saving Time and Improving Quality
Reducing Turnover Rates
Summary
AI in Employee Training and Development: Personalizing the Learning Experience
Personalized Learning Experiences
Aligning Development With Organizational Needs
Tracking Progress and Providing Real-Time Feedback
Making Training Interactive and Engaging
Summary
AI-Powered Workforce Analytics: Transforming HR Decision Making
Making Informed Decisions With AI
Predicting Workforce Trends and Issues
Strategic Workforce Planning
Optimizing Resource Allocation
Improving Productivity
Reducing Costs
Summary
Enhancing Employee Engagement With AI: A New Frontier in HR
The Importance of Employee Engagement
AI's Role in Analyzing Employee Engagement
Identifying Factors Affecting Engagement
Implementing Targeted Interventions
AI-Driven Chatbots and Virtual Assistants
Creating a More Connected Workplace
Continuous Improvement Through Real-Time Feedback
Summary
CHAPTER 8 AI in the Health Care Industry
Health Care Analytics
Medical Imaging
Surgical Robots
Patient Monitoring
AI in Health Care Analytics: Transforming Patient Care Through Data-Driven Insights
Analyzing Vast Amounts of Clinical Data
Predicting Potential Health Risks
Personalizing Treatment Plans
Improving Patient Outcomes
More Accurate Diagnoses and Effective Treatments
Challenges and Considerations
Summary
AI in Medical Imaging: Enhancing Accuracy and Speed
Enhancing Accuracy in Image Analysis
Speeding up the Diagnostic Process
Reducing Radiologists' Workload
Early Disease Detection
Improving Patient Care
Summary
AI-Powered Surgical Robots: Transforming Modern Surgery
Precision and Control Beyond Human Capabilities
Minimally Invasive Surgeries With High Accuracy
Enhancing Surgeons' Abilities in Complex Procedures
Improved Patient Outcomes and Surgical Success Rates
Continuous Learning and Improvement
Challenges and Future Directions
Summary
AI in Patient Monitoring: Revolutionizing Health Care With Real-Time Insights
Continuous Tracking of Vital Signs
Detecting Abnormalities and Early Warning Systems
Proactive Patient Care
Reducing the Risk of Complications
AI-Powered Wearables and Remote Monitoring Devices
Promoting Better Long-Term Health Outcomes
AI-Powered Patient Education Videos
Summary
JAMA's AI in Clinical Practice
CHAPTER 9 AI in the Entertainment Industry
AI in Film and TV
AI in Gaming
AI in Augmented Reality
AI in Film and TV: Revolutionizing Production and Enhancing Viewer Experience
Automating Production and Postproduction
Enhancing Content Creation
Personalizing Viewer Experiences
Improving Viewer Satisfaction and Engagement
Summary
AI in Gaming: Creating Immersive and Interactive Experiences
Adaptive and Intelligent NPCs
Procedural Content Generation
Optimizing Game Testing
Enhancing Player Experience
Summary
AI and Augmented Reality: Transforming Entertainment Experiences
Enhancing AR Applications With AI
Object recognition
tracking
Interaction
AI-Powered AR in Entertainment
Interactive Storytelling
Immersive Gaming
Live Events
Creative Expression and Audience Engagement
Interactive Art Installations
Personalized Entertainment Experiences
Enhanced Social Interactions
Summary
PART 3 Implementing AI Responsibly
AI Ethics and Governance
AI Data Privacy and Cybersecurity
CHAPTER 10 AI Ethics and Governance
Ethical AI Principles
Mitigating AI Bias and Discrimination
AI Governance Frameworks
Explainable AI
Summary
The Need for Ethical AI Principles
Core Objectives of Ethical AI Principles
Examining Ethical Frameworks Worldwide
UNESco recommendation on the Ethics of AI
European Union's Ethics Guidelines for trustworthy AI
IEEE Global Initiative on Ethics of Autonomous and Intelligent Systems
oEcd AI Principles
Commonalities and Differences
Implementing Ethical AI Principles
Summary
AI Bias: Causes, Consequences, and Mitigation Strategies
Causes of AI Bias
Potential consequences of AI Bias
case Studies Highlighting AI Bias
Summary
The Growing Need for Robust AI Governance Frameworks
Why AI Governance Is Essential
Approaches to AI Governance
National and International Initiatives
Industry Self-regulation
Multistakeholder collaborations
Challenges in AI Governance
Balancing Innovation and regulation
Ensuring Global consistency
Addressing Bias and discrimination
Summary
Understanding the Complexity of AI Systems and the Role of Explainable AI
Explainable AI (XAI): Making AI Transparent and Interpretable
Importance of XAI
Techniques for Achieving Explainability
Model-Specific techniques
Model-Agnostic techniques
Trade-Offs Between Model Performance and Interpretability
Summary
CHAPTER 11 AI Data Privacy and Cybersecurity
Data Privacy Regulations
Securing AI Systems
Federated Learning
AI Cybersecurity Applications
Summary
The Importance of Data Privacy Regulations in AI
Understanding Data Privacy Regulations
General Data Protection regulation (GDPr)
california consumer Privacy Act (ccPA)
Mandating Transparency in Data Practices
The Importance of Compliance
Summary
Securing AI Systems: Protecting Against Cyber Threats and Unauthorized Access
Why AI Systems Are Attractive Targets
Sensitive Data Handling
High-value targets
Effective Security Strategies
Encryption
Access controls
regular Security Audits
Privacy by Design Principles
Key Privacy by Design Principles
Prioritizing Security to Safeguard AI Systems
Summary
The Importance of Federated Learning in Addressing AI Data Privacy Concerns
How Federated Learning Works
Ensuring Data Privacy
Benefits of Federated Learning
Privacy Protection
compliance With Data Privacy regulations
Enhanced Security
Applications in Health Care and Finance
Health care
Finance
Challenges and Future Directions
Summary
AI-Driven Cybersecurity: A Proactive Defense Against Cyber Attacks
How AI-Driven Cybersecurity Works
Detecting Patterns and Anomalies
real-time threat Detection
continuous Learning and Adaptation
Adaptive Defense Mechanisms
Proactive threat Prediction
Ensuring Security and transparency in AI Systems
Securing AI Systems
Transparency and Accountability
Ethical Considerations
Summary
CHAPTER 12 Becoming an AI-Driven OrganizationA Holistic Transformation
Embracing Innovation
The Role of Leadership in Fostering Innovation
Investing in Research and Development
Creating an Innovative Environment
Case Study: Embracing Innovation at Google
Conclusion
Investing in AI Capabilities
Advanced Computing Resources
Robust Data Management Systems
Hiring Skilled Professionals
Case Study: Investing in AI Capabilities at Microsoft
Conclusion
Ensuring Ethical AI Use
The Importance of Ethical AI
Implementing Ethical Guidelines
Conducting Regular Audits
Addressing Potential Biases
Case Study: Ensuring Ethical AI at IBM
Conclusion
Understanding AI-Driven Organizations
Key Characteristics of AI-Driven Organizations
Conclusion
Strategy Transformation
Conclusion
Cultural Transformation
Conclusion
Process Transformation
Conclusion
Skills Transformation
Conclusion
Roadmap for AI Transformation
Conclusion
Challenges and Considerations
Summary
CHAPTER 13 The Dangers and Weaknesses of Using AI in Business
Introduction
The Importance of Understanding AI's Limitations and Risks
The Dual Nature of AI
Ethical and Social Implications
Technical Limitations
Security Risks
Economic and operational Considerations
Conclusion
The Balance Between AI's Potential and Its Pitfalls
The Potential of AI in Business
The Pitfalls of AI in Business
Striking the Balance
Conclusion
AI Ethical Concerns
Bias and Discrimination in AI Algorithms
Understanding Bias in AI
Sources of Bias
Consequences of Bias
Mitigating Bias
Ethical Considerations
Conclusion
AI Privacy Issues and Data Security
Data Collection and Consent
Data Anonymization and Deidentification
Data Security and Breaches
Bias and Discrimination
Regulatory Compliance
Ethical Considerations
The Ethical Implications of AI Decision Making
Bias and Fairness
Transparency and Accountability
Privacy and Data Security
Autonomy and Human Oversight
Social and Economic Impact
Conclusion
Technical Limitations of AI
The Challenge of Achieving True General Intelligence
The Complexity of Human Cognition
Data Dependency and Bias
Transfer Learning and Adaptability
Understanding Context and Ambiguity
Conclusion
AI Dependence on Large Datasets and the Quality of Data
The Necessity of Large Datasets
Quality over Quantity
Strategies for Mitigating Data Quality Issues
Conclusion
The Limitations of Current AI Models in Understanding Context and Nuance
The Challenge of Contextual Understanding
The Nuance Problem
Implications for Businesses
Addressing the Limitations
Conclusion
AI Security Risks
Vulnerabilities to Hacking and Adversarial Attacks
Hacking Vulnerabilities
Adversarial Attacks
Mitigation Strategies
Conclusion
The Potential for AI to Be Used in Malicious Ways
Deepfakes
Autonomous Weapons
Mitigating the Risks
The Risk of AI Systems Being Manipulated or Corrupted
Data Poisoning
Model Inversion Attacks
Adversarial Attacks
Insider Threats
Algorithmic Bias
Mitigation Strategies
Conclusion
AI's Economic and Social Impact
Job Displacement and the Future of Work
The Threat of Job Displacement
Economic Implications
Social Impact and the future of Work
Conclusion
The Digital Divide and Unequal Access to AI Technology
Economic Disparities
Educational Inequities
Technological Infrastructure
Social and Ethical Implications
Bridging the Divide
Conclusion
The Potential for AI to Exacerbate Social Inequalities
Bias in AI Algorithms
Access to AI Technology
Job Displacement
Surveillance and Privacy Concerns
Health Care Inequities
Policy and Regulation
Conclusion
AI Legal and Regulatory Challenges
The Need for Robust Legal Frameworks and Regulations
Addressing Ethical Concerns
Ensuring Accountability and Transparency
Mitigating Risks and Unintended Consequences
Promoting Innovation and Competition
International Collaboration and Harmonization
Conclusion
The Difficulty of Assigning Accountability and Responsibility in AI Systems
Autonomous Nature of AI
Involvement of Multiple Stakeholders
Lack of Clear Legal Frameworks
Potential Solutions
Conclusion
Lessons Learned From Past Incidents and How They Can Inform Future AI Development
The Importance of Ethical AI Design
key Takeaways
Addressing Bias and Discrimination
key Takeaways
Ensuring Transparency and Accountability
key Takeaways
Prioritizing Safety and Reliability
key Takeaways
Fostering Collaboration and Regulation
key Takeaways
Learning From Mistakes
key Takeaways
AI Case Studies: Real-World Examples of AI Failures and Their Consequences
Microsoft's Tay Chatbot
Consequences
Amazon's AI Recruitment Tool
Consequences
Tesla's Autopilot Crashes
Consequences
Google Photos' Image Recognition Error
Consequences
Apple Card's Gender Bias
Consequences
Conclusion
AI Mitigation Strategies
Best Practices for Developing and Deploying AI Responsibly
Ethical AI frameworks
Data Privacy and Security
Bias Mitigation
Transparency and Explainability
Continuous Monitoring and Evaluation
Human-in-the-Loop
Regulatory Compliance
Ethical AI Training
Stakeholder Engagement
Social Responsibility
Conclusion
The Role of Transparency and Explainability in AI Systems
Importance of Transparency and Explainability
Strategies to Enhance Transparency and Explainability
Conclusion
The Risk of Nontransparent AI
Conclusion
Nontransparent AI Examples
Conclusion
The Importance of Continuous Monitoring and Evaluation of AI
Ensuring Ethical Compliance
Enhancing Performance and Accuracy
Mitigating Security Risks
Facilitating Regulatory Compliance
Building Trust and Transparency
Adapting to Changing Business Needs
Some Common Misconceptions About AI That Businesses Should Be Aware of
Summary
Leveraging AI for Business Success
Identifying and Assessing Risks
Implementing Robust Governance Frameworks
Fostering a Culture of Collaboration
Prioritizing Human-Centric AI
Continuous Learning and Adaptation
Balancing Innovation With Responsibility
Last Word Navigating the AI Landscape: A Strategic Roadmap for Business Transformation
About the Author
Index
Back cover

Systemvoraussetzungen

Als PDF speichern Als Link merken