How Willow Copilot Tackles the Field Knowledge Gap

Across domains and industries—from healthcare and higher education to retail and transportation—field teams are facing a silent crisis: the risk of knowledge loss as seasoned technicians retire, taking with them decades of specialized knowledge. In fact, research shows that 70% of service organizations fear losing critical expertise in the next 5 to 10 years due to an aging workforce.

This trend has a direct impact on productivity. We hear from customers deploying Willow in busy airports, hospitals and university campuses that a shortage of skilled technicians has led to a myriad of complications, including:

• Lower first-time fix rates
• Longer times to get critical assets up and running again
• Increased costs for training and retention

Organizations attempt to solve this problem by digitizing their institutional knowledge, but most solutions are clunky, hard to maintain, or simply not user-friendly in the field. This process may involve creating management platforms or a centralized knowledge base to keep the information stored and on-hand when it’s needed. However, this method often leads to many documents that over time become tedious to maintain and keep up-to-date.

That’s where Willow Copilot comes in: our generative AI-driven agent and companion experience, powered by Azure Open AI service.

In this post, we’ll examine how Willow Copilot supports field service teams in real time, allowing them to work smarter and faster and preserve the knowledge and experience of their retiring colleagues.

A day in the life using Willow Copilot

Let’s walk through what a typical work day looks like for Terry, a technician tasked with multiple work orders across a large facility, and how Willow Copilot transforms his day-to-day.

Before the visit

Terry gets a work order to address a fault code on an Air Handling Unit (AHU) in Building 101 at Bradford Square.

Before heading out, Terry wants to be prepared. He decides he wants to learn a bit more about the affected AHU. He also wants to know upfront what tools and spare parts he should carry with him on his visit so he can save himself a second trip.

Terry opens up Willow Copilot and:

• Quickly accesses asset insights about the AHU
• Reviews common issues tied to the fault code
• Sees recommendations for tools and replacement parts
• Avoids a costly second trip

Willow Copilot helps Terry determine what he should take along on the visit.

During the visit

Once on site, Terry uses Willow Copilot to quickly look up fault codes and suggest next steps as he proceeds through diagnostics and troubleshooting.

He asks some of the following questions:

• I keep getting a fault code 12, but everything seems to be ok. What am I missing?
• We just had a major power outage and I’m getting a fault code 35.
• I just replaced the supply fan motor and I’m getting excessive whine.
• The return fan motor isn’t running at full speed and I’m getting fault code 1005.

After a couple of hours of troubleshooting, Terry resolves the issue. No need to look up O&M manuals. All instutional knowledge curated in the organization and ongoing learnings can be leveraged via Willow Copilot.

After the visit

Upon completing a repair, Terry is required to log a report on how the issue was addressed before closing out the work order. He uses Willow Copilot to instantly summarize all of the steps he followed to finally resolve the problem.

Behind the scenes: Your intelligent companion for the built world

What’s going on behind the scenes to light up this experience? Willow Copilot is an AI agent leveraging three data sources:

• The customer’s Knowledge Graph in Willow: This contains all the assets and capabilities ontologically related to physical spaces in the building.
• Documents: These range from O&M manuals provided by the AHU vendor upon installation to warranty documents and troubleshooting guides curated over time. We use Retrieval Augmented Generation (RAG) to create a vectorized index.
• Knowledge of the internet from the underlying Large Language Model (LLM) in Azure Open AI service: System prompts allow us to set guardrails and keep focus on built environments, sustainability, energy efficiency, and related areas.

A composite experience across all these sources with a conversational chat allows the end user to stay focused on their job and save time!

Why it matters: Creating team-wide intelligence

Willow Copilot turns isolated, undocumented expertise into accessible, real-time intelligence—available to every technician, no matter their experience level. This not only helps fill the knowledge gap but also boosts performance, shortens downtime, and empowers the next generation of field workers.

As workforce demographics shift and infrastructure complexity grows, tools like Copilot aren’t just helpful—they’re essential.

Summary

• Facility management is facing an aging crisis. 70% of service organizations fear losing critical technician expertise within the next 5-10 years due to an aging workforce that is rapidly approaching retirement.
• Knowledge loss hurts operations. Reduced first-time fix rates, longer asset downtie, and rising training costs are all symptoms of this growing problem.
• Traditional documentation falls short. Static knowledge bases quickly become outdated and are hard to navigate in the field.
• Willow Copilot bridges the gap and supports every stage of the job. Willow Copilot is a generative AI assistant that surfaces real-time, context-aware insights, allowing organizations to preserve their institutional knowledge and equip their facility teams with the intelligence to quickly resolve issues. This includes:
  • Recommendations on tools and parts ahead of a visit, saving secondary trips
  • Ability to decode fault codes, suggest next steps, and surface relevant documentation instantly
  • Automatically generated work order summaries, saving technicians time writing reports

How would having Willow Copilot transform your day-to-day operations? Tell us what opportunities you see.