Kristian Bainey

Ai-Driven Project Management

Harnessing the Power of Artificial Intelligence and ChatGPT to Achieve Peak Productivity and Success

• Broschiertes Buch

Produktbeschreibung

ENHANCE YOUR PROJECT MANAGEMENT TOOLKIT WITH AI AND CHATGPT In AI-Driven Project Management: Harnessing the Power of Artificial Intelligence and ChatGPT to Achieve Peak Productivity and Success, distinguished IT and project management professional Kristian Bainey delivers a practical and incisive discussion of how to automate and augment the administration and management of projects with AI. In the book, he focuses on four critical areas where project leaders can dramatically improve results with AI's data-centric capabilities in AI-Driven Project Management (PM-AI): Enhanced Decision-Making and Risk Management; Optimization and Efficiency; Innovation and Strategic Insights, Ethics, Bias Reduction and Quality Control. The author demonstrates how artificial intelligence and large-language models - and ChatGPT in particular - work, as well as how they fit into Agile, Hybrid, and Predictive approaches to project management. You'll learn how to accurately forecast a project with ChatGPT and develop techniques for crafting a powerful AI project management strategy using timeless project management principles. An indispensable resource for managers, executives, and business leaders around the world and in organizations of all types and sizes, AI-Driven Project Management is also a must-read for project management professionals, IT specialists, and anyone else interested in the intersection of artificial intelligence, machine learning, and project management.

---

Hinweis: Dieser Artikel kann nur an eine deutsche Lieferadresse ausgeliefert werden.

Produktdetails

• Verlag: John Wiley & Sons Inc
• Seitenzahl: 384
• Erscheinungstermin: 22. April 2024
• Englisch
• Abmessung: 241mm x 186mm x 21mm
• Gewicht: 706g
• ISBN-13: 9781394232215
• ISBN-10: 1394232217
• Artikelnr.: 69076709

Autorenporträt

KRISTIAN BAINEY, M.S., PMP, CSM, Prosci, ITIL, PM-AI, is an experienced IT and project management professional with over 15 years focusing on digital transformation development in generative AI-Driven Project Management (PM-AI), DevOps, and the SDLC elements of waterfall, agile, and hybrid approaches. He is an expert in directing business and digital transformation, AI, data management, operations, continuous improvement, and change management projects. He manages a consulting corporation specializing in generative AI integration for organizations, lecturing part-time at universities and creating global course content and podcasts. Additionally, he served as the President of the PMI Northern Alberta Chapter (2023-2024), and actively speaks at numerous worldwide conferences on AI/ChatGPT in Project Management.

Inhaltsangabe

Foreword xxi
 
Introduction xxiii
 
Part I Foundations of AI in Project Management 1
 
Chapter 1 Introducing ChatGPT: The AI Revolution in Project Management 3
 
Evolution of AI 3
 
What Is ChatGPT? 5
 
Accessing ChatGPT 7
 
The ChatGPT Advantage for Project Managers 7
 
Your Roadmap to Productivity and Success 8
 
Chapter 2 AI-Driven Project Management (PM-AI) 9
 
What Is Project Management? 9
 
What Is Fine-Tuning? 10
 
What Is Customized Modeling? 10
 
What Is Model Training from Scratch? 10
 
What Is Artificial Intelligence, and How Does It Affect Project Management?
11
 
What Is Generative AI's Effect on Project Management? 13
 
Artificial Intelligence 14
 
Machine Learning 14
 
Deep Learning 15
 
Generative AI 15
 
Large Language Models 15
 
Generative Pretrained Transformers 15
 
ChatGPT 15
 
Generative AI Tools for Project Managers 19
 
Machine Learning and Its Effect on Project Management 20
 
Deep Learning and Its Effect on Project Management 22
 
Chapter 3 AI-Driven Predictive Approach to Project Management 23
 
The Initiating Process Phase 24
 
Example: Initiating a New Solar Energy Farm Project 24
 
The Planning Process Phase 24
 
Example: AI-Driven Cybersecurity for Network Intrusion Detection 24
 
The Executing Process Phase 25
 
Example: Remote Patient Monitoring in a Healthcare Application 25
 
The Monitoring and Controlling Process Phase 26
 
Example: Smart Building Management System in Construction 26
 
The Closing Process Phase 27
 
Example: AI-Driven Inventory Management System in the Supply Chain 27
 
The Benefits and Limitations of Using a Predictive Approach in AI 27
 
Chapter 4 AI-Driven Agile and Hybrid Approaches to Project Management 31
 
The Concept Phase 31
 
Example: Personalized Fitness and Nutrition Mobile App in Software
Development 32
 
The Initiating Phase 32
 
Example: Telemedicine Platform in the Health Sector 33
 
The Planning and Design Phase 33
 
Example: AI-Powered Driver Assistance System in the Automotive Sector 33
 
The Iterative Development (Sprint and Cycles) Phase 34
 
Example: Recommendation Engine in the E-commerce Sector 34
 
The Release and Transition Phase 35
 
Example: Mobile Banking Application in the Financial Services Sector 35
 
The Deployment Phase 35
 
Example: Streaming Service Platform in the Media and Entertainment Sector
36
 
AI-Driven Hybrid Approach in Project Management 36
 
The Concept and Initiating Phase 36
 
Example: Cloud-Based CRM System in the IT Sector 37
 
The Planning and Design Phase 37
 
Example: Web Application Development in the IT Sector 37
 
The Iterative Development and Testing phase 38
 
Example: Construction Project that Integrates Advanced Technologies 38
 
The Deployment and Closing Phase 39
 
Example: Mobile App Deployment in the Insurance Sector 39
 
Benefits and Limitations of Using an Agile or Hybrid Approach 39
 
Chapter 5 The Implications of AI in Project Management 43
 
Steps to Identifying AI Challenges in Project Management Using a Systemized
Approach 44
 
Chapter 6 Navigating Ethical Challenges in PM-AI 47
 
Addressing Inclusivity 47
 
Accountability 50
 
Training Data and Ethical Implications 51
 
Transparency and Trust 53
 
Part I Conclusion 55
 
Key Takeaways 55
 
Thought-Provoking Questions 56
 
Understanding PM-AI 56
 
Practical Application in Data-Driven Decisions 56
 
GenAI Capabilities 56
 
Predictive Capabilities 57
 
Skill Development and Learning 57
 
Integration and Compatibility 57
 
Measurement and KPIs 57
 
Multiple Choice Questions 57
 
Part II Unleashing the Power of ChatGPT 61
 
Chapter 7 Using ChatGPT 63
 
The Chat Interface 63
 
Updates and Versioning 65
 
How Does ChatGPT Work? 66
 
Input Processing 66
 
Tokenization 66
 
Input Embedding 67
 
Transformer Neural Network 67
 
Text Generation and Output 68
 
Safety, Data Storage, and Accuracy of ChatGPT 68
 
Tailor ChatGPT for Project Managers 69
 
Guidelines for Effective Interactions 70
 
Expanding Beyond Project Management 70
 
ChatGPT Format Types 70
 
ChatGPT Human Voice Tone Types 73
 
Temperature Settings 75
 
Safety and Ethical Considerations 76
 
Chapter 8 Transforming Communication with ChatGPT 79
 
Project Inquiries and Faster Information Gathering 79
 
Streamlining Project Inquiries 79
 
Faster Information Gathering 80
 
Client Communication and Stakeholder Management 83
 
Enhancing Team Collaboration and Information Sharing 85
 
Simplifying Internal Communications and Agendas 87
 
Documenting and Archiving Communications 91
 
Chapter 9 Risk, Ethics, Prediction, and Decision Making in AI Projects 93
 
Revolutionizing Decision Making with ChatGPT 93
 
Risks and Ethics of Using Prediction for Decision Making 96
 
Human-in-the-Loop 97
 
Part II Conclusion 101
 
Key Takeaways 102
 
Thought-Provoking Questions 103
 
The Future of Project Management with AI 103
 
Engaging with AI Tools 103
 
Ethics and Responsibility 103
 
Community and Continuous Learning 103
 
Multiple Choice Questions 103
 
Part III Mastering Prompt Engineering in Project Management with Chatgpt
107
 
Chapter 10 Prompt Engineering for Project Managers 109
 
What Is Prompt Engineering? 109
 
Prompt Engineering in Project Management 110
 
Prompt Engineering: Real-World Use Cases for Project Managers 110
 
Project Development Lifecycles 118
 
Process Groups and Project Management Processes 121
 
Project Management Knowledge Areas 121
 
Project Scope Management 124
 
Project Schedule Management 134
 
Project Schedule 137
 
Project Cost Management 141
 
Activity Cost Example 142
 
Determine Budget Example 142
 
Cost-Benefits Analysis Example 145
 
Earned Value Management (EVM) Example 145
 
Project Quality Management 149
 
Project Resource Management 152
 
Project Communications Management 160
 
Project Risk Management 161
 
Project Procurement Management 165
 
Project Stakeholder Management 167
 
Project Integration Management 171
 
Project Change Management 177
 
Project Performance Management 179
 
Chapter 11 Unlocking ChatGPT Tips and Tricks 183
 
Part III Conclusion 191
 
Key Takeaways 191
 
Thought-Provoking Questions 192
 
Role Transformation in Project Management 192
 
Limitations and Solutions 192
 
Integration with Project Management Methodologies 192
 
Future Outlook 192
 
Enhancing Project Efficiency and Effectiveness 193
 
Training and Skill Development 193
 
Risk Management and Decision Making 193
 
Stakeholder Engagement and Communication 193
 
Ethical Considerations and Compliance 193
 
Measuring Success and ROI 193
 
Adapting to Changing Project Dynamics 194
 
Collaboration and Team Dynamics 194
 
Innovation and Creative Problem-Solving 194
 
Project Management Across Industries 194
 
Sustainability and Long-Term Planning 194
 
Security and Data Privacy 194
 
User Experience and Customer Satisfaction 195
 
Digital Transformation and AI Integration 195
 
Change Management and Organizational Culture 195
 
Training AI for Custom Needs 195
 
AI Ethics and Social Responsibility 195
 
Multiple Choice Questions 196
 
Part IV AI in Action: Practical Applications for Project Management 201
 
Chapter 12 Accurate Project Forecasting with ChatGPT 203
 
Predictive Data-Driven Analysis 203
 
Augmenting Forecasting Tasks 205
 
Advanced ChatGPT Features in Forecasting 208
 
Chapter 13 Learning and Development Powered by ChatGPT 211
 
Personalized Learning 211
 
Tailoring Learning to Your Needs 212
 
Immediate Feedback and Support 212
 
Adapting to Different Learning Styles 213
 
Professional Development and Training 213
 
Personalized PMP Exam Study Plan 213
 
Scalability of Educational Resources 214
 
Enhancing Accessibility 216
 
Chapter 14 AI and Human Talent in Projects: A Harmonious Blend 219
 
AI Chatbots in People Management 220
 
Behavioral Project Management 220
 
Misinformation 222
 
Hallucinations 223
 
The Rise of People Soft Skills in PM-AI 224
 
Part IV Conclusion 227
 
Key Takeaways 227
 
Thought-Provoking Questions 228
 
Predictive Data-Driven Analysis with ChatGPT 228
 
Automating Forecasting Tasks in Project Management 228
 
Risk Assessment and Budget Forecasting 228
 
Advanced ChatGPT Features in Project Management 228
 
Learning and Development with ChatGPT 229
 
AI and Human Talent in Projects 229
 
Multiple Choice Questions 229
 
Part V Secure AI Implementation Strategies: Principles, AI Model
Integration, and PM-AI Opportunities 233
 
Chapter 15 Security and Privacy in AI Model Integration 235
 
Strategic Integration of AI in Cybersecurity 235
 
AI and Data Security 238
 
The Pause and Reflect Process in ml 239
 
Ethical Implications and Privacy Concerns 241
 
Ethical Implications 242
 
Privacy Concerns 243
 
Regulations 247
 
Chapter 16 AI Strategic Project Management Principles 251
 
Eight Principles for Organizational AI Model Integration 252
 
AI Integration Strategy 252
 
Data Management and Protection 253
 
Ethical AI Framework 254
 
Transparency and Explainability 254
 
Security and Data Privacy 255
 
Governance and Change Management 256
 
Accountability and Performance 256
 
Scalability and Continuous Improvement 257
 
Chapter 17 Fine-Tuning and Customizing AI Models for Organizational
Benefits 259
 
PM-AI Modality Model 259
 
Fine-Tuning AI Models for Organizations 261
 
Model-as-a-Service (MaaS) 262
 
Fine-Tuning AI-as-a-Service (AIaaS) 262
 
Roles of AI Model Development 269
 
Six Layers of the AI Model Development Lifecycle 270
 
Data Gathering and Analysis Layer 271
 
AI Architecture Design Layer 271
 
Model Training and Development Layer 272
 
Model Validation and Integration Layer 273
 
AI Model Deployment Layer 274
 
Iterative Refinement and Optimization Layer 274
 
Customizing AI Models for Organizations 275
 
Fine-Tuning vs. Customized AI Models for Projects 276
 
Key Considerations for First-Time AI Implementation 277
 
Chapter 18 Realizing ChatGPT's Limitations for Project Management 281
 
Limited Analysis of Words per Interaction 284
 
Navigating the Do's and Don'ts 285
 
Part V Conclusion 287
 
Key Takeaways 287
 
Thought-Provoking Questions 288
 
Security and Privacy in AI Modeling 288
 
Strategic Integration of AI in Cybersecurity 289
 
AI and Data Security 289
 
AI Strategic Project Management Principles 289
 
Fine-Tuning AI Models for Organizational Benefits 289
 
Challenges and Considerations in AI Model Development 289
 
Multiple Choice Questions 290
 
Part VI The Future of Project Management and AI 295
 
Chapter 19 The Future Impact of AI in Project Management and Expertise 297
 
The Rise of Multimodals 298
 
Areas of Expertise for Project Managers in PM-AI 300
 
IT and Engineering 301
 
Healthcare 305
 
Education 308
 
Construction 310
 
Retail 313
 
Moving Forward 316
 
Part VI Conclusion 317
 
Key Takeaways 317
 
Thought-Provoking Questions 319
 
Decision Making and Automation in PM-AI 319
 
Integration of AI and Human Skills in Project Management 319
 
Adapting to Rapid AI Development 319
 
The Role of AI in Communication and Stakeholder Engagement 320
 
The Evolution of AI as a Strategic Partner 320
 
Multimodal AI in Project Management 320
 
Preparing for the Future of AI in Project Management 320
 
Multiple Choice Questions 321
 
Answer Key to Multiple Choice Questions 325
 
Part I: Foundations of AI in Project Management 325
 
Part II: Unleashing the Power of ChatGPT 326
 
Part III: Mastering Prompt Engineering in Project Management with ChatGPT
326
 
Part IV: AI in Action: Practical Applications for Project Management 328
 
Part V: Secure AI Implementation Strategies: Principles, AI Model
Integration, and PM-AI Opportunities 329
 
Part VI: The Future of Project Management and AI 331
 
References 333
 
Part I: Foundations of AI in Project Management 333
 
Part II: Unleashing the Power of ChatGPT 334
 
Part III: Mastering Prompt Engineering in Project Management with ChatGPT
336
 
Part IV: AI in Action: Practical Applications for Project Management 337
 
Part V: Secure AI Implementation Strategies: Principles, AI Model
Integration, and PM-AI Opportunities 339
 
Part VI: The Future of Project Management and AI 342
 
Index 345