Case Study

From Curiosity to AI Readiness

SUMMARY/OVERVIEW

How a National Food Distributor Enabled Enterprise-Wide AI Adoption

Artificial intelligence has become ubiquitous, and the potential applications and efficiencies it offers seemingly grow by the day. But turning latent potential into actualized benefit can come with challenges, especially for organizations that operate across both customer-facing and operational teams.

Recognizing the positive impact AI could have on its business, one national food distributor looked to implement the technology to enhance productivity — but it also understood that without the proper foundation, AI-powered tools could create fragmentation instead of efficiency.

The company sought guidance from our team of knowledgeable professionals about ways to introduce AI that would align teams, support responsible use, and build long-term confidence throughout their organization.

Key Takeaways

90% satisfaction among the client’s Copilot users

Dozens of hours saved among users each week

Low-code AI agent creation through Copilot Studio Lite offering enhanced efficiency

AI adoption image.
The Challenge

Aligning AI Adoption Across Diverse Teams

While the client understood AI’s potential to improve efficiency, adopting the technology across the organization posed several challenges, with different teams envisioning various uses for AI-powered tools based on their needs. The company also had questions about which platform to choose, along with specific use cases that the tool could enhance. Additionally, company leadership was aware that any AI solution they introduced needed to deliver meaningful enhancements without introducing risks related to data access, security, and governance.

As part of the implementation process, the client also needed to address how to effectively train employees in using AI while managing change on a large scale. Without a cohesive deployment and enablement strategy, there was a risk that AI adoption would remain siloed — limiting its impact and creating uneven experiences across the organization.

An image of trucks parked.
The Approach

Designing AI Enablement for Coordination, Governance, and Scale

Getting Started With Copilot

After listening to the client's goals, we developed an AI enablement approach that balanced flexibility with governance, allowing adoption to scale across the organization. As part of the approach, we recommended Microsoft 365 Copilot, which the organization could easily integrate into its existing workflows.

To facilitate Copilot’s adoption and reflect how teams work across the business, we identified a pilot group of 30 users from cross-functional backgrounds, including employees from marketing, IT, human resources, and sales. Prior to the pilot’s commencement, we also moved the client’s on-premises files into a secure cloud environment, where the AI could access and use them. 

Security was another important factor we addressed from the project’s outset. We conducted an assessment that included evaluating identity and access management, cybersecurity and data protection, data governance, and compliance.

With the underlying technical aspects in place, we then met with the project's stakeholders to identify practical use cases tied to everyday work. 

Some of the use cases included using Copilot to:

  1. Create personas for consumer segmentation by using analytics

  2. Analyze the client's in-store product placement in comparison to their competitors through image analysis

  3. Perform an analysis of customer reviews on vendors’ websites to evaluate the client’s products

Facilitating AI Adoption

Next, we created a foundational training program to build confidence and promote Copilot’s adoption among different teams. We structured each training into key topic areas, starting with an overview of prompt engineering and then moving into specific uses for Copilot within individual applications. Each training session lasted three to four hours, allowing the group to ask questions and provide real-time feedback about their experiences with the tool. This also allowed us to help users explore different efficiencies that Copilot could bring to their everyday workflows.

Part of the training process also involved holding regular office hours so that users could ask questions as they spent more time with Copilot. Our team then built a center of excellence that compiled resources and frequently asked questions into a single reference location. To promote continuous improvement, we solicited additional feedback through surveys to gather insight into how Copilot was operating and the various ways it had enhanced the client’s efficiency.

An image of a man in a factory.
The Results

Establishing Confidence in Scalable AI Use

  • Increased Adoption Rate

    The client experienced a 7.5 times increase in Copilot adoption across the organization, with a self-reported 90% satisfaction rate among the tool’s users.

  • New AI Agents

    The pilot program led to the creation of two AI agents — for marketing and HR — using Copilot Studio Lite, a low-code tool built into Copilot that’s designed to be easily accessible and user friendly.

  • Hours Saved

    A quarter of the pilot program’s participants reported saving multiple hours per week by using Copilot, with another 35% saying the tool saved them at least 30 minutes or more.


Scaling AI requires more than technology — it requires coordination. Learn how BDO’s Copilot Chat QuickStart program can help empower your organization.

The client team was deeply invested in the success of Copilot from day one. With an engaged and visible sponsor, a strong cross-functional pilot group, and empowered champions across departments, they laid the foundation for a seamless and impactful company-wide adoption.
Rida Siddiqui
Change Management Lead