The AI Revolution in Customer Service and Support: A Practical Guide to Impactful Deployment of AI to Best Serve Your Customers

In the rapidly evolving AI landscape, customer service and support professionals find themselves in a prime position to take advantage of this innovative technology to drive customer success. The AI Revolution in Customer Service and Support is a practical guide for professionals who want to harness the power of generative AI within their organizations to create more powerful customer and employee experiences. This book is designed to equip you with the knowledge and confidence to embrace the AI revolution and integrate the technology, such as large language models (LLMs), machine learning, predictive analytics, and gamified learning, into the customer experience. Start your journey toward leveraging this technology effectively to optimize organizational productivity. A portion of the book’s proceeds will be donated to the nonprofit Future World Alliance, dedicated to K-12 AI ethics education. IN THIS BOOK YOU’LL LEARN About AI, machine learning, and data science How to develop an AI vision for your organization How and where to incorporate AI technology in your customer experience fl ow About new roles and responsibilities for your organization How to improve customer experience while optimizing productivity How to implement responsible AI practices How to strengthen your culture across all generations in the workplace How to address concerns and build strategies for reskilling and upskilling your people How to incorporate games, play, and other techniques to engage your agents with AI Explore thought experiments for the future of support in your organization “Insightful & comprehensive—if you run a service & support operation, put this book on your essential reading list right now!” —PHIL WOLFENDEN, Cisco, VP, Customer Experience “This book is both timely and relevant as we enter an unprecedented period in our industry and the broader world driven by Generative AI. The magnitude and speed of change we’re experiencing is astounding and this book does an outstanding job balancing technical knowledge with the people and ethical considerations we must also keep front of mind.” —BRYAN BELMONT, Microsoft, Corporate VP, Customer Service & Support “The authors of this book are undoubtedly on the front lines of operationalizing Gen AI implementations in customer support environments... and they know undoubtedly that at its core, support is about people and genuine human connections. This book walks you through their journey to keep people at the center of this technical tsunami.” —PHAEDRA BOINODIRIS, Author, AI for the Rest of Us Cover Title Page Copyright Page Contents at a Glance Contents Foreword Introduction PART I: INTRODUCTION TO AI AND ITS APPLICATIONS IN CUSTOMER SERVICE AND SUPPORT 1 THE SEEDS OF AN AI REVOLUTION Overview of Customer Service and Support How Customers Access Support Measuring Support Success Challenges in Customer Support Desire for Change and Improvement 2 OVERVIEW OF GENERATIVE AI AND DATA SCIENCE MACHINE LEARNING Unveiling the Realm of AI Technologies: A Glimpse into the Augmented Future Generative AI and Language Models LLMs and Their Applications LLMs and Customer Support Development, Optimization, Localization, and Personalization Based on LLMs Unveiling the Power of Clustering and Topic Modeling Enhancing Customer Support Through Hybrid AI: LLMs Meet Clustering and Topic Modeling 3 APPLICATION AREAS OF AI IN SUPPORT The Rationale for Using AI in Customer Service and Support Exploring the How: Key Applications of AI in Customer Service and Support PART II: BUILDING AI MODELS USING PROPRIETARY CONTENT: THE 6DS FRAMEWORK 4 VISION OF SUCCESS A Vision of Success Developing the Plan Getting Started 5 DISCOVER: LAYING THE FOUNDATION Mapping the Territory Defining a Clear Scope Developing an Ideal User Persona Content Curation 6 DESIGN: BUILDING THE BLUEPRINT Identifying Your Starting Point Steps in the Design Phase 7 DEVELOP: CRAFTING THE SOLUTION Development in the Content Management Lifecycle Creating and Testing Grounding Datasets Data Splitting Content and Model Training Data Preparation Prompt Engineering: Prompt-Based Fine-Tuning for Optimal Model Response Start Small with Content Ingestion Methods and Considerations 8 DIAGNOSE: ENSURING EFFECTIVENESS Definition and Overview The Importance of Rigorous Testing and Training Metrics for AI Model Validation Integrating Responsible AI In AI Model Validation Validating Chatbot Deployment in Controlled Environments Prompt Tuning 9 DEPLOY: LAUNCHING THE SOLUTION Integrating the AI Model into the Real-World Environment Establish Feedback Channels and Encourage Discussion Plan for Integration with Existing Tools Identify Your Stakeholders Deployment Goals Creating a Deployment Plan Diverse SMEs and Validation Team Signoffs Continuous Evaluation for Consistent Model Performance 10 DETECT: MONITORING AND FEEDBACK The Necessity of Post-Deployment Monitoring AI Model Relevancy in Changing Data Environments Supervised Learning and Reinforcement Learning from Human Feedback (RLHF) for Better Model Outputs Detection Through the Use of Synthetic Transactions PART III: ORGANIZATIONAL CONSIDERATIONS FOR AI MODEL CREATION AND DEPLOYMENT 11 RESPONSIBLE AI AND ETHICAL CONSIDERATIONS IN CUSTOMER SUPPORT Foundations of Responsible AI Challenges and Opportunities Frameworks and Governance Implementing Responsible AI: A Strategic Blueprint for Ethical Integration Addressing the Shadows: Mitigating Potential Harms in LLMs Navigating the Bias in Large Language Models Bias in LLMs: Case Studies and Impact Considerations 12 CULTURAL CONSIDERATIONS The Human Element in AI Adoption The Nature of Technological Change AI Adoption in the Multigenerational Workplace AI Adoption and Customer Expectations A New Era of Sustainability and Inclusion A Culture of Innovation for AI Future-Ready Growth 13 DEFINING THE METRICS THAT MATTER IN THIS NEW ERA OF AI The Human Need for Measurement and the Pursuit of Success Navigating the Metrics Mesh 14 UTILIZATION OF AI FOR OPERATIONAL SUCCESS Case Volume Forecasting Case Analysis and Troubleshooting Routing Financial Considerations Customer-Facing AI: Risk and Reward 15 EVOLUTION OF SUPPORT ROLES WITH AI A Journey Through History Evolving Needs of the Business Preparing Your Workforce for the Future Real-World AI Adaptation Policy Perspectives Preparing for the Future: Individual and Collective Actions PART IV: GAMIFIED LEARNING AND THE FUTURE OF WORK IN SUPPORT 16 GAMES, PLAY, AND NOVELTY IN THE AGE OF AI Humans and Play: A Deeper Dive with Historical Context Historical Origins and Evolution The Intersection of Gamification and Psychology Where Games Work and Where They Don’t: The Skills–Behaviors Matrix Games and Big Data: Crowdsourcing Data Generation Elements of Enterprise Game Design Gamification Strategy for AI Adoption Measuring the Impact of Gamification Learning from Successes and Failures Beyond Points and Leaderboards: The Future of Gamification Strategies 17 LEADERSHIP EXCELLENCE IN THE ERA OF AI Leadership in the Age of AI The Transformational Journey 18 FUTURE OF WORK: NAVIGATING THE AI REVOLUTION Navigating the AI Revolution Thought Experiment Considerations How Will AI Reshape Customer Service and Support? 19 NEXT STEPS AND CONCLUSION Next Steps Conclusion GLOSSARY A B C D E F G H I K L M N O P Q R S T U V W Z INDEX A B C D E F G H I J K L M N O P Q R S T U V W Y Z