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Microsoft Dynamics 365 AI for Business Insights

You're reading from  Microsoft Dynamics 365 AI for Business Insights

Product type Book
Published in Mar 2024
Publisher Packt
ISBN-13 9781801810944
Pages 178 pages
Edition 1st Edition
Languages
Author (1):
Dmitry Shargorodsky Dmitry Shargorodsky
Profile icon Dmitry Shargorodsky

Table of Contents (18) Chapters

Preface 1. Part 1: Foundations of Dynamics 365 AI
2. Chapter 1: Introduction and Architectural Overview of Dynamics 365 AI 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 this chapter, we recognize the profound transformation that MS Copilot has brought to the Dynamics 365 AI environment. This journey has not only highlighted the capabilities and adaptability of MS Copilot but also underscored its pivotal role in revolutionizing business processes and decision-making across various industries.

The integration of MS Copilot into Dynamics 365 AI has demonstrated a seamless melding of cutting-edge AI with sophisticated business processes. This powerful combination enhances every facet of business operations, from the way we approach code generation to the intricacies of implementing predictive analytics and automating customer interactions. MS Copilot emerges not just as a tool but as a driver of innovation, steering businesses toward more efficient, precise, and intelligent operational models.

Through in-depth case studies covering the retail, healthcare, manufacturing, and financial sectors, we have seen tangible evidence...

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