Exploring the Connection Between AI and Facilities Management : Ep 9

About the Episode

In this Quick Byte episode Brian Haines, Chief Strategy Officer at FM:Systems, defines artificial intelligence –is it mystical? Is it complicated?

  • As well, how is it connected to and used in facility management? He answers questions like:
  • How does artificial intelligence apply to building operations?
  • How can facility managers be successful using artificial intelligence?
  • What is the desired outcome of using artificial intelligence to better manage our workspace, buildings and facilities overall?

Watch the Episode

Episode Transcription

Brian Haines 0:14

In today’s quick bite, we’re talking about artificial intelligence. Artificial of intelligence is a topic that often is a bit mystical. People are often confused or think it’s something incredibly complicated. So I figured today, I would share the actual definition of what artificial intelligence is, and explain to you how it can be used in facility operations.


Brian Haines 0:40

So artificial intelligence is the intelligence of machines or software as opposed to the intelligence of humans, or animals. Really straightforward definition. So I’m going to give you some examples of artificial intelligence and how it can be successful.


Brian Haines 0:58

There’s really two components needed to make AI successful. First of all, it needs a massive amount of highly accurate, credible data to be exposed to artificial intelligence algorithms. And it really also needs to understand what your desired outcome is before it provides those results. I’ll give you an example. Let’s say I have an artificial intelligence algorithm. And I want to know about the history of the United States. All I provide to it is a spreadsheet with a list of the 50 United States and the day that they entered the Union. AI is going to give me a very simple answer. It’s basically going to list probably all of those states in the order that they became states. And that’s about all I’m going to get from it. Now, let’s flip that on its head a little bit. What if I’d asked the same question, but I gave the AI algorithm access to the entire Library of Congress of the United States. I’m going to get a very robust, very different kind of answer.


Brian Haines 2:10

So when you apply that to building operations, if I’m asking AI a question about, you know, what’s the effectiveness of my maintenance operations, and I give it very little or very inaccurate data, I’m not going to get an answer that’s really going to be helpful to me in terms of helping me optimize my operations. If I take an integrated workplace management solution, or a computerized maintenance management solution that’s incredibly robust, has years of information in it, and I asked that same question, I’m gonna get a really good answer, a very solid answer that really looks at the effectiveness of my operations over time, including all of the components that I’m tracking. So it may be labor and materials, it may be technician loading, it may be the effectiveness of one specific type of air handling unit versus another, or a chiller. And it’s really going to give me that really robust information. And that’s really the difference and what I can get out of AI.


Brian Haines 3:14

So going back to the beginning, two things we really need to remember are, you know, artificial intelligence, the definition is quite simple. It’s the intelligence of machines or software and really for it to be successful, two things need to be included. One is a highly accurate, large amount of data for it to analyze. And two, it really needs to understand the questions that you’re asking for you to get results that are going to be meaningful to you.

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