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Microsoft Dynamics 365 AI for Business Insights

You're reading from   Microsoft Dynamics 365 AI for Business Insights Transform your business processes with the practical implementation of Dynamics 365 AI modules

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Product type Paperback
Published in Mar 2024
Publisher Packt
ISBN-13 9781801810944
Length 178 pages
Edition 1st Edition
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Author (1):
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Dmitry Shargorodsky Dmitry Shargorodsky
Author Profile Icon Dmitry Shargorodsky
Dmitry Shargorodsky
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Toc

Table of Contents (18) Chapters Close

Preface 1. Part 1: Foundations of Dynamics 365 AI
2. Chapter 1: Introduction and Architectural Overview of Dynamics 365 AI FREE CHAPTER 3. Chapter 2: Microsoft Dynamics 365 AI Architecture and Foundations 4. Part 2: Implementing Dynamics 365 AI Across Business Functions
5. Chapter 3: Implementing Dynamics 365 AI for Sales Insights 6. Chapter 4: Driving Customer Service Excellence with Dynamics 365 AI 7. Chapter 5: Marketing Optimization with Dynamics 365 AI 8. Chapter 6: Financial Analytics with Dynamics 365 AI 9. Part 3: Advanced Applications and Future Directions
10. Chapter 7: Leveraging Generative AI in Dynamics 365 11. Chapter 8: Harnessing MS Copilot for Enhanced Business Insights 12. Chapter 9: “Virtual Agent for Customer Service” in the Context of MS Copilot and Microsoft Dynamics 13. Chapter 10: Fraud Protection with Dynamics 365 AI 14. Part 4: Looking Ahead
15. Chapter 11: Future Trends and Developments in Dynamics 365 AI 16. Index 17. Other Books You May Enjoy

Summary

As we conclude the chapter, it becomes clear that the integration of advanced virtual agents represents a significant evolution in customer service technology. The journey through this chapter has provided a comprehensive overview of the transformative impact these AI-driven solutions have on customer support, particularly within the MS Copilot and Microsoft Dynamics ecosystems.

The chapter began with an exploration of the implementation of virtual agents for automated customer support. It highlighted how these AI-driven solutions enhance operational efficiency and responsiveness in handling customer inquiries. This integration streamlines the customer service process, allowing human agents to concentrate on more complex and nuanced customer needs, thereby optimizing overall workflow and efficiency.

Delving into the development of conversational AI interfaces and chatbots, the chapter emphasized the crucial role of advanced NLP technologies. These technologies are instrumental...

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