.png)
This NexusCon 2025 session combines a practical pilot story from Wendy’s with a much-needed reality check on what “AI” actually means in energy management. Rachel Kennedy, Solutions Engineer at KODE Labs, opens the session by breaking down the difference between machine learning, fault detection, optimization, and generative AI—setting a clear baseline before the case study begins.
From there, Thomas Grant, Global Manager of Energy and DTV Energy at Wendy’s, and Carolyn McHale, President & CSO at Facil.ai, walk through a real pilot using AI-driven HVAC optimization in company-operated restaurants. The focus is squarely on how these tools behave in fast-food kitchens with high heat loads, tight margins, and inconsistent equipment conditions.
Behind the paywall, you’ll learn why clear AI definitions matter before any vendor evaluation, and how Rachel’s framework helped Wendy’s avoid comparing apples to oranges. The speakers unpack what surprised them once the pilot started, including why roughly 20–25% of sites revealed underlying equipment problems instead of savings.
They also explain what didn’t work in kitchen-heavy spaces, how broken systems distorted results, and why narrowing the scope was critical to getting usable insights. For any FM, EM, or OT leader sorting through AI hype, pilot design, and internal buy-in, this recording offers a grounded, owner-first look at how to test AI without betting the farm.
Watch the full recording inside Nexus Pro →
This NexusCon 2025 session combines a practical pilot story from Wendy’s with a much-needed reality check on what “AI” actually means in energy management. Rachel Kennedy, Solutions Engineer at KODE Labs, opens the session by breaking down the difference between machine learning, fault detection, optimization, and generative AI—setting a clear baseline before the case study begins.
From there, Thomas Grant, Global Manager of Energy and DTV Energy at Wendy’s, and Carolyn McHale, President & CSO at Facil.ai, walk through a real pilot using AI-driven HVAC optimization in company-operated restaurants. The focus is squarely on how these tools behave in fast-food kitchens with high heat loads, tight margins, and inconsistent equipment conditions.
Behind the paywall, you’ll learn why clear AI definitions matter before any vendor evaluation, and how Rachel’s framework helped Wendy’s avoid comparing apples to oranges. The speakers unpack what surprised them once the pilot started, including why roughly 20–25% of sites revealed underlying equipment problems instead of savings.
They also explain what didn’t work in kitchen-heavy spaces, how broken systems distorted results, and why narrowing the scope was critical to getting usable insights. For any FM, EM, or OT leader sorting through AI hype, pilot design, and internal buy-in, this recording offers a grounded, owner-first look at how to test AI without betting the farm.
Watch the full recording inside Nexus Pro →
Head over to Nexus Connect and see what’s new in the community. Don’t forget to check out the latest member-only events.
Go to Nexus ConnectJoin Nexus Pro and get full access including invite-only member gatherings, access to the community chatroom Nexus Connect, networking opportunities, and deep dive essays.
Sign Up
Nexus Labs exists to move the smart buildings industry forward, without the fluff.
On Wednesday, we send out the renowned (and free) Nexus Newsletter.
This is a great piece!
I agree.