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Home » AI Agent & Copilot Podcast: Avanade’s Nancie Calder and RitewAI’s Will Hawkins on a Single Source of Truth
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AI Agent & Copilot Podcast: Avanade’s Nancie Calder and RitewAI’s Will Hawkins on a Single Source of Truth

Cam SessingerBy Cam SessingerFebruary 21, 2025Updated:September 22, 20252 Mins Read
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lcome to the AI Agent & Copilot Podcast, analyzing the latest AI Copilot and agent developments from Microsoft and its partners, delving into customer use cases, and exploring how AI plus the Cloud helps customers reimagine their business.

In this episode, Tom Smith talks with two speakers about their upcoming “Transforming Your Data Estate into a Goldmine with Microsoft Fabric” session at AI Agent & Copilot Summit:

  • Nancie Calder, Executive at Avanade, a Microsoft/Accenture Joint Venture
  • Will Hawkins, AI Engineer & Founder at RitewAI

Highlights

Speakers’ Background (01:42)

Hawkins shares his background as a certified data scientist in the Microsoft market for almost four years, witnessing the evolution of AI from traditional machine learning to agents and Copilots. Calder introduces herself as the global Dynamics CRM Practice Lead at Avanade, focusing on service transformation, particularly in contact centers and field services.

Session Overview and Key Learning Objectives (03:48)

Calder explains the session’s goal to help attendees understand how to turn their data into a strategic asset by bringing data into one place, including Azure and legacy systems. She emphasizes the importance of using Microsoft Fabric for its OneLake data lake, which allows data from various sources to be integrated into a common format.

Hawkins explains that OneLake provides a common data format, allowing data from various sources to be standardized and connected in a central repository.

Data Entry and Knowledge Management (08:47)

Hawkins discusses the benefits of using AI for data entry to create high-quality data and reduce human error. Calder highlights the opportunity for creating knowledge articles based on various data sources, such as voice recordings and technical documentation, to improve data accuracy and accessibility. She also mentions the role of autonomous agents in continuously updating data in Dataverse.

Best Practices and Lessons Learned (11:04)

Hawkins shares a lesson learned from a past project where the focus was on creating a place for all information to live, rather than just on AI modeling. Calder advises organizations to conduct assessments and proofs of concept to mitigate risk and find champions within the organization to drive adoption. Both speakers emphasize the value of starting small and finding areas within the organization that can benefit from AI and data readiness initiatives.


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