WEBVTT
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Welcome to BOMA’s
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Building Excellence, a CRE podcast series.
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This episode is brought to you by Yardi.
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I'm your host, Alan Stein.
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Today we're joined by Brian Sutherland,
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the Vice President of Commercial
for Yardi.
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Brian, it's great to have you here
to help us better understand
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the massive wave
of AI hitting the industry.
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Yeah.
Glad to be a part of the conversation.
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Before we dig into the deep
tech, let's start
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with a quick game of rapid
fire to get to know you a little better.
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Are you ready?
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I am ready, let's do it.
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All right.
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Favorite way to unplug from technology
on the weekend?
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Golfing.
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Love it, love it.
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Bucket list trip.
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Tokyo, Japan.
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Okay.
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Go to karaoke song?
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Garth Brooks - Rodeo.
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Favorite movie?
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Shawshank Redemption.
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And if you could only keep one app
on your phone
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other than email and work, of course,
what would it be?
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Claude.
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All right, look, that's a great segue
into our conversation today.
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So for me, it would definitely be
Apple Music, because as Elvis Presley
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famously said, without music,
the day would never end.
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Now that you've given us a quick glimpse
into who you are.
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Let's talk about your work with Yardi.
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For those of you that might not know,
can you give us a little bit
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of an elevator pitch on who Yardi is?
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Yeah, absolutely.
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Yardi was founded in 1984,
in Santa Barbara, California,
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our owner is Anant Yardi.
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He still remains active and involved
with the company as a chairman.
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At its core, Yardi is property management
and accounting.
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And that's really where our roots are,
and that's the foundation of our platform.
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So think general ledger, AP, AR,
financial reporting, customer management, etc.
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Increasingly, we've moved into
everything really around
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real estate operations, from marketing
to construction to budgeting to leasing,
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and really invited other folks
into the Yardi platform.
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From a market share perspective,
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about 50% of real estate
in the US runs on the Yardi platform.
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So, you know, many times
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we're referred to as a 500 pound gorilla
in terms of real estate software.
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But it's a fantastic company,
very family friendly
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and just a fantastic place to work.
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That's great.
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So tell us, you've been in the industry
for quite a while.
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Walk us through your journey
within the industry
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a little bit and also your time with Yardi
and your role with Yardi.
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Yeah.
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So prior to Yardi, I had several different
startups.
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Yardi was actually one of my clients.
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We were doing employment screening
and had an employment screening business
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that I had sold eventually,
but prior to that, Yardi was my client.
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So I was familiar with Yardi and familiar
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with Yardi’s
growth from a headcount perspective,
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certainly, and being from Santa Barbara
at that point,
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small town and everyone kind of knows
the larger employers in town.
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My experience at Yardi is varied.
So it really started on the residential side
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and moved to commercial pretty quickly
and launched Yardi Elevate.
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So I was really on the product side,
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working deeply
with our clients on their workflows,
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and that product line is quite
successful now. My day to day
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is overseeing the sales organization
on the commercial real estate side.
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So that's office,
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industrial, retail, co-working,
corporate real estate, self-storage.
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So kind of a lot under my purview
from a sales perspective.
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I help out with the strategic direction
of the product line,
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and then more recently have been tasked to
bring Virtuoso, our AI brand, to market.
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So have been really focused
on artificial intelligence.
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And that seems to be the topic everywhere
I tend to go.
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So look forward to talking a little bit
about that today.
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Yeah, absolutely. Well,
you got a couple of things on your plate.
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It sounds like it for sure.
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I do.
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You know,
Yardi has really leveraged
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AI for things
like invoice processing for years.
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But something shifted about 24 months ago
with the rise of large language models.
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How has that conversation for your
customers changed since that shift?
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Yeah,
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I think the power
of artificial intelligence was recognized.
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And if you look at
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pre-LLM, it was really around
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natural language
processing, machine learning,
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chat bots that had natural language
processing in it.
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And large language models really
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change the landscape because the end users
are really seeing the benefit of it.
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And whether it was doing, you know, a
simple task at work or a question
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that your kids might ask of you,
you know, whatever it might be.
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But having the ability
to go through one of these
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AI interfaces and really interact with it
and see the power of it,
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I think just brought a lot of excitement
to, certainly to our customers,
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but I think just more broadly out there.
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And it's been an exciting time, and a lot
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certainly has changed
even since those came out.
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You know, with ChatGPT really coming out
first and the other ones after that,
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but a lot of excitement around
large language models and AI in general.
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Yeah.
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Well, that explains a lot about the really
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the genesis of our conversation today
and how- on how we got here.
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So now let's start
talking about the fact that we are here.
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So it's all been a huge evolution
in AI in every industry.
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But commercial real estate
is no exception to that.
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And we've really moved
past the hype phase into a phase where
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including AI in your service
offerings is now table stakes.
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So what are we seeing?
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Or what are you seeing more specifically
from the C-suite
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as it relates to incorporating AI
into your service offerings?
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Yeah, I think
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you're spot on in terms of
AI being table stakes.
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I think the C-suite is asking
a lot of questions,
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and typically those questions
will fall on the IT group.
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And the questions are around
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how AI is going to have an impact
on their business and where they see
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AI kind of transforming
the way they do their day to day.
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And so I think that's a good thing,
because the benefit is
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and vision is certainly there.
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And the IT groups are being tasked
with how to deliver now.
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And they have a perceived interest
or actually
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actual interest from the C-suite.
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And with that comes budgets.
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When they're-- with that comes, I think,
a lot of excitement and opportunity.
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And so I think I view that
as a really good thing, that everyone
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wants to see the power
of AI across their organization.
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Yeah. All right.
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You mentioned IT groups,
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Are you seeing any different things
from a finance standpoint
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or any other personas related
to the commercial real estate space
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into how they're leveraging
their software partners
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to help navigate this,
this new-- these new waters?
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Yeah, I think that demands are coming
from multiple different groups,
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certainly from the finance side
really looking at cost savings, right?
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And where artificial intelligence
is going to help their bottom line.
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From an IT perspective,
certainly that's part of the conversation.
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But I think the conversation
is also around security and governance.
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And, you know, the user conferences
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or industry events
that have technology folks at it.
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I can tell you every single topic
is around artificial intelligence.
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And so they are living and breathing it
whether they wanted to or not.
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And they're being asked
a lot of questions.
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I think finance groups are too.
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And I would say by and large, those are
the two largest groups that we talk to.
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Certainly there's other influencers
within the organization.
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There's executives as well,
who love to get updates
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in terms of artificial intelligence impact
on the industry.
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What we're hearing from our customers,
we have a pretty good view,
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just given that 50% of real estate
runs on our platform.
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And I think, you know,
many folks are looking to their software
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providers to answer questions
and to make sure they have
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a good foundation and understanding
of the implications of AI.
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I love that you mentioned security.
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And, you know, obviously,
when it comes to new tech,
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the biggest worries are usually around
safety and security
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and who actually controls the data.
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How has Yardi updated its systems
to make sure a company's
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private information stays protected
and doesn't end up where it shouldn't be?
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Yeah.
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So I can tell you,
our lawyers have certainly been busy
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looking at regulations
that are coming out country by country.
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You know, we have a pretty broad range
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of 80 different countries
our platform is run on.
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And so each jurisdiction and country
might have their own kind of standards.
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I will say though, to your question,
in terms of what has changed
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or evolved, maybe at Yardi,
from that standpoint,
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we're still safeguarding our clients data
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the same way we have
for the last 40 plus years.
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And you think about the clients
that might be on our platform.
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It's banking institutions,
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sovereign wealth, large REITs
that might be on it.
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And so, you know,
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we're SOX 1, SOX 2 compliant
artificial intelligence is part of that.
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And so the same sort of standards
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you have operating in our platform
from a day to day perspective
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pertains to everything we're doing
from an AI perspective as well.
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You've introduced the
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concept of model
context protocol connectors.
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How does this allow a property management
company to use tools like Copilot
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or Claude with their own data?
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Yeah.
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To me, this was kind of the holy grail
of connecting to your data.
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I think there's been a movement
across real estate companies
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to get their data
and have access to their data.
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So those projects have been underway.
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What I don't think anyone saw coming
was artificial intelligence.
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And now the power of having your data
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kind of in a single platform
or accessible
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is really mission
critical. In terms of MCP,
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What we're finding is, is more and more
people are logging in through
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AI interfaces on a daily basis,
whether it is
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Claude, ChatGPT, Gemini.
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Or Copilot, those
are kind of the big four AI interfaces.
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Our goal is to give our clients
accessibility
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to the data that they're sitting on,
and allow them to connect through the same
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AI interfaces that they're logging into
every day.
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The nice thing is, it's not just our data.
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There are connectors and MCP layers
for other tools like Outlook
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or different things
that they might be using on a daily basis.
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And so this idea of co-mingling data,
wrapping around that large language
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model,
having your data also governed and secure
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and authenticated from an end user
perspective is quite powerful.
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And I can tell you, the outputs that
our clients are seeing are meaningful.
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And they're able to get details
around their real estate operations.
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And if they're looking at leasing
and want to look at how renewing a lease
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or extending a certain tenant
is going to have an impact on their NOI,
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they can do that on the fly
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through an AI interface,
not having to go into our platform.
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And so it is resonating.
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And I think people want their data
where they work.
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And so we're trying to
to make that part of our roadmap as well.
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Yeah that's great.
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It reminds me of something
that I always preach
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around the 3 Ds,
which is data driven decisions.
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So let the data tell you
what your decision should be
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and what direction
you should be taking something.
00:12:31.133 --> 00:12:35.133
So it's awesome to hear that
that you guys have really embraced in
00:12:35.133 --> 00:12:39.433
and have-- are starting to
to figure out how to, to better arm
00:12:39.533 --> 00:12:42.533
the property management world with that
data.
00:12:43.566 --> 00:12:47.333
Yardi is the single connected platform
that gives commercial real estate
00:12:47.333 --> 00:12:52.833
owners, managers and investors real time
visibility across their entire portfolio,
00:12:52.833 --> 00:12:57.200
from leasing and accounting to tenant
experience and asset performance.
00:12:57.433 --> 00:13:02.400
We've spent over 40 years building
software exclusively for this industry,
00:13:02.400 --> 00:13:06.566
and today some of the world's
largest CRE firms run on Yardi.
00:13:06.833 --> 00:13:11.000
Connect with us online or in person
at the upcoming BOMA International Expo
00:13:11.000 --> 00:13:12.466
in Long Beach, California.
00:13:12.466 --> 00:13:17.233
And let us show you what this looks like
for your property portfolio.
00:13:18.033 --> 00:13:20.600
The 2026 BOMA International Conference
00:13:20.600 --> 00:13:24.500
and Expo is where teams
get stronger and problems get solved.
00:13:24.533 --> 00:13:26.533
Experience the power of connection,
00:13:26.533 --> 00:13:30.633
learning and innovation,
plus the best expo in the industry.
00:13:30.666 --> 00:13:34.466
Learn more at 2026.bomaconvention.org.
00:13:35.466 --> 00:13:36.866
We look forward to seeing you
00:13:36.866 --> 00:13:39.866
this June in Long Beach, California.
00:13:40.733 --> 00:13:42.600
So okay, now let's
00:13:42.600 --> 00:13:45.800
transition into agents
in the future of workflow.
00:13:45.833 --> 00:13:48.900
So how do you see the future of
AI playing out
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and helping property managers
with daily tasks?
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You touched on that a little bit,
but maybe a little more specific.
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Yeah, absolutely.
00:13:58.900 --> 00:14:03.633
When you're looking at real estate
companies, I think one kind of use case
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is residential fee managers
and large residential fee managers.
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And if you look at the way
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their organizations are laid out,
there's certainly segregation of duties.
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And they'll have people that are,
you know, on site and interacting
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with their customers
or prospective customers one on one.
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You'll have people that are managing
AP approvals and vendor relationships or,
00:14:26.133 --> 00:14:28.866
or individuals that are doing AR.
00:14:28.866 --> 00:14:34.133
And so I think if you look at
the organizations that way and understand
00:14:34.400 --> 00:14:38.200
where these agentic flows can create
00:14:38.233 --> 00:14:42.600
time savings or more efficiencies
or cost savings in many cases,
00:14:42.833 --> 00:14:45.700
really think of it
in terms of having agent coworkers
00:14:45.700 --> 00:14:50.233
next to each one of those individuals
and making them more efficient.
00:14:50.233 --> 00:14:53.666
And so, you know,
horizontally across the organization,
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all these different users, them
doing different tasks and having agents
00:14:57.900 --> 00:15:03.100
augmenting that kind of day to day is,
is, I think is a good way to look at it.
00:15:03.100 --> 00:15:06.700
And I think the way
we're certainly looking at it as well,
00:15:06.800 --> 00:15:09.433
working with our clients,
really understanding
00:15:09.433 --> 00:15:13.900
their kind of workflows,
and then where these agentic workflows
00:15:13.900 --> 00:15:17.433
are going to be improved
by this technology that's there.
00:15:18.133 --> 00:15:18.666
Yeah.
00:15:18.666 --> 00:15:23.100
You talk about agents at scale
or agent coworkers.
00:15:23.100 --> 00:15:25.000
Can you paint for us--
00:15:25.000 --> 00:15:27.233
Give us a couple examples
maybe, or paint for us
00:15:27.233 --> 00:15:30.866
a little better picture
of how those agents might better help
00:15:30.866 --> 00:15:34.633
with daily tasks like AP, AR,
or even customer interactions?
00:15:35.900 --> 00:15:36.700
Yeah,
00:15:36.700 --> 00:15:40.400
just
a little view into our payment processing.
00:15:40.433 --> 00:15:43.800
And this is for an example,
75 million invoices go through it
00:15:43.800 --> 00:15:46.300
on a-- on an annual basis.
00:15:46.300 --> 00:15:47.000
Each invoice
00:15:47.000 --> 00:15:50.933
in terms of getting approved for payment
goes through about four workflow steps.
00:15:50.966 --> 00:15:54.600
And so that's about 300 million
00:15:54.600 --> 00:15:57.633
steps across our client base.
00:15:57.800 --> 00:16:01.133
Each one of those ste--, steps,
excuse me, takes about two minutes.
00:16:01.133 --> 00:16:05.600
So that's about 600 million minutes,
which equates to about 10 million hours
00:16:05.600 --> 00:16:08.333
that our clients spend approving invoices.
00:16:08.333 --> 00:16:10.233
So quite a bit of time.
00:16:10.233 --> 00:16:15.000
So if you can automate that process,
if you can have logic that goes through
00:16:15.500 --> 00:16:19.900
the system and sees
what invoices have been approved
00:16:19.900 --> 00:16:24.600
and sets up rules over the say based upon
the last 12 months of processing,
00:16:24.900 --> 00:16:29.200
it is a huge benefit to our clients
from a time savings perspective,
00:16:29.200 --> 00:16:33.133
not to have a human going in there
and approving these invoices.
00:16:33.133 --> 00:16:37.200
It might be lower dollar amounts
and gaining trust over time that this
00:16:37.200 --> 00:16:41.000
AI model is working,
that the auditability of it
00:16:41.000 --> 00:16:44.066
is more than you can audit
when a human approves invoices.
00:16:44.066 --> 00:16:49.833
So that's like a very kind of narrow
use case of where an agentic flow
00:16:49.966 --> 00:16:53.100
can really benefit our clients,
because just the sheer
00:16:53.133 --> 00:16:57.666
volume of invoices
that go through real estate organizations
00:16:57.666 --> 00:17:02.066
and you approve that process
and it can have a material impact.
00:17:02.500 --> 00:17:03.800
Oh, yeah. Absolutely.
00:17:03.800 --> 00:17:04.733
I mean, you can just
00:17:04.733 --> 00:17:08.466
you can just, you know, hear the
the dollar signs ringing up there.
00:17:08.466 --> 00:17:11.566
And, you know, as
far as the savings from a, from a time
00:17:11.566 --> 00:17:14.933
and money standpoint,
I mean, that's incredible.
00:17:15.133 --> 00:17:15.800
Yeah. Yeah.
00:17:15.800 --> 00:17:20.800
And you know, on those invoices, a lot of
vendors have payment terms as well.
00:17:20.800 --> 00:17:25.000
And if you look at the vendors that are
servicing these real estate properties,
00:17:25.033 --> 00:17:27.900
a lot of them have cash flow issues
and they're looking for early payments.
00:17:27.900 --> 00:17:31.033
So these invoices will indicate
if there's, you know, there
00:17:31.033 --> 00:17:34.533
could be a discount
based upon early payment.
00:17:34.566 --> 00:17:38.333
And, you know, if you're able
to process those invoices, figure out
00:17:38.333 --> 00:17:42.200
which vendors have payment terms at scale.
00:17:42.333 --> 00:17:44.433
Roll that out across all of your vendors.
00:17:44.433 --> 00:17:47.500
That's a serious cost savings that you can have
00:17:47.533 --> 00:17:51.133
in terms of your vendor MRO spend.
00:17:51.200 --> 00:17:53.666
And so that's
just another little example.
00:17:53.666 --> 00:17:56.666
So kind of taking that invoice
and what's something else that we can
00:17:56.666 --> 00:17:58.666
potentially do with it
with an agent.
00:17:58.666 --> 00:18:03.300
And so just a lot of opportunity
across real estate operations.
00:18:03.933 --> 00:18:04.733
Yeah.
00:18:04.733 --> 00:18:10.300
So I say this quite often
that a property manager wears so many hats
00:18:10.333 --> 00:18:12.100
and they have to rely
00:18:12.100 --> 00:18:16.666
so heavily on their vendor partners
to be the experts in these areas.
00:18:16.666 --> 00:18:22.800
So for the property manager on the ground,
how does an AI forward software
00:18:22.933 --> 00:18:28.033
really translate
maybe to some cost or time savings,
00:18:28.033 --> 00:18:31.466
specifically in the operational side
of what
00:18:31.466 --> 00:18:34.833
they are responsible
for doing on a day to day basis?
00:18:35.700 --> 00:18:37.466
Yeah, and you're absolutely right.
00:18:37.466 --> 00:18:41.300
There is a ton of responsibilities
and a lot has to come with,
00:18:41.333 --> 00:18:45.633
you know, the interactions that they're
having with prospective residents
00:18:45.633 --> 00:18:50.933
at a property, for example, or demand
from existing tenants that are there.
00:18:50.933 --> 00:18:54.800
And so if we can think about, again,
those roles
00:18:54.800 --> 00:18:58.033
and kind of the work streams that they're
dealing with on a daily basis.
00:18:58.033 --> 00:19:02.400
And so I think a good example of that
is prospects coming into a property
00:19:02.400 --> 00:19:06.900
and interacting with a chat agent,
as opposed to a live agent,
00:19:06.900 --> 00:19:10.866
and doing things like setting up a tour
and automating that process
00:19:10.866 --> 00:19:13.866
and giving that resident--
prospective resident the ability
00:19:13.866 --> 00:19:16.933
to schedule a tour, give them a code
to actually get in the door.
00:19:17.033 --> 00:19:17.233
You know,
00:19:17.233 --> 00:19:20.933
those sort of things that are really taking
the burden from that property manager and
00:19:20.933 --> 00:19:24.866
allowing them to focus on the customers
that they have already at the property
00:19:24.866 --> 00:19:28.100
and really automating the prospect
workflow instead.
00:19:28.100 --> 00:19:30.533
And so that would just be like
another example.
00:19:30.533 --> 00:19:35.900
But, you know, across
any specific individual, I think within
00:19:35.933 --> 00:19:41.133
these real estate companies that we serve,
there are benefits of rolling out AI.
00:19:41.233 --> 00:19:44.200
There are material impacts of it
00:19:44.200 --> 00:19:47.400
from a risk perspective, time savings
perspective, cost perspective.
00:19:47.400 --> 00:19:50.466
And those kind of three areas
are the three pillars
00:19:50.466 --> 00:19:54.400
that we kind of focus in on
when we're thinking about our next kind
00:19:54.400 --> 00:19:57.633
of initiative around
artificial intelligence.
00:19:59.233 --> 00:20:00.733
That's great.
00:20:00.733 --> 00:20:04.333
Only the tip of the iceberg
as it relates to, I think, the power
00:20:04.333 --> 00:20:08.633
that we're going to be seeing from AI
and the commercial real estate space.
00:20:08.633 --> 00:20:14.400
So a couple more questions as
we look to wrap up our conversation around
00:20:14.433 --> 00:20:18.866
AI and what leaders in the industry
should be thinking as far as next steps.
00:20:18.900 --> 00:20:23.066
So, you know, you're very involved in the
AI sections of CRE.
00:20:23.066 --> 00:20:27.233
What would you say
is the biggest misconception
00:20:27.233 --> 00:20:31.433
that leaders currently
have about AI's impact on their business?
00:20:32.300 --> 00:20:38.666
Yeah, I think there is a misconception or,
you know, a look at AI
00:20:38.700 --> 00:20:42.666
where it's a reduction of headcount
is a potential option.
00:20:42.666 --> 00:20:46.466
And I think we like to view it
as it's
00:20:46.466 --> 00:20:49.933
an opportunity
for expansion of current roles.
00:20:49.933 --> 00:20:54.333
And, you know, the way we're looking at it
internally, if our workers,
00:20:54.400 --> 00:20:58.233
if our Yardi employees, for example,
have more capacity,
00:20:58.333 --> 00:21:01.266
we can increase the live support
that we have with our clients.
00:21:01.266 --> 00:21:05.200
So improving our customer service,
and I think with real estate
00:21:05.200 --> 00:21:07.233
operations, it's very similar.
00:21:07.233 --> 00:21:11.200
And I mentioned the example earlier
of the property manager
00:21:11.200 --> 00:21:14.866
and that prospect kind of workload
and interaction coming through.
00:21:15.066 --> 00:21:17.200
That gives them more capacity.
00:21:17.200 --> 00:21:21.733
Now they can focus on improving customer
service, retaining their residents, etc..
00:21:21.733 --> 00:21:26.266
And so I think it's just--
it opens up a lot more opportunities
00:21:26.266 --> 00:21:29.600
within your organizations.
00:21:29.600 --> 00:21:33.600
These real estate companies, organizations
and the folks that are interacting
00:21:33.633 --> 00:21:38.200
with their customers with the finance
group, whatever it might be.
00:21:39.300 --> 00:21:40.000
Right.
00:21:40.000 --> 00:21:41.666
Makes lot of sense.
00:21:41.666 --> 00:21:46.100
So looking at the broader landscape
of property technology integration,
00:21:46.533 --> 00:21:50.033
what should companies be doing right now
00:21:50.066 --> 00:21:54.666
to prepare for their data
for an AI driven 2026?
00:21:55.333 --> 00:21:58.266
Yeah, well, I think data can live in
00:21:58.266 --> 00:22:01.600
silos and data can be unstructured.
00:22:01.800 --> 00:22:05.100
And so there are those
00:22:05.300 --> 00:22:08.133
foundational views of data
00:22:08.133 --> 00:22:12.433
that I think
need to be addressed for impactful AI.
00:22:12.433 --> 00:22:15.466
I would also say
00:22:16.100 --> 00:22:20.700
to not look at it, having to do everything
for you out of the gate.
00:22:20.700 --> 00:22:24.466
And I think there needs to be trust
that's built out
00:22:24.466 --> 00:22:26.066
around artificial intelligence.
00:22:26.066 --> 00:22:29.733
I think there needs to be wins
out of the gate.
00:22:29.866 --> 00:22:32.300
Many AI projects fail as well.
00:22:32.300 --> 00:22:33.800
So start narrow.
00:22:33.800 --> 00:22:35.900
Start with something very specific.
00:22:35.900 --> 00:22:40.500
Start with a, hopefully a win,
and then iterate and build upon that.
00:22:40.500 --> 00:22:42.466
And that's going to keep the C-suite
00:22:42.466 --> 00:22:45.400
wanting to continue to invest
in artificial intelligence.
00:22:45.400 --> 00:22:48.633
It's going to keep the IT groups wanting,
you know, giving them
00:22:48.633 --> 00:22:51.833
the ability to continue to innovate
and see where AI can have an impact.
00:22:51.833 --> 00:22:54.533
But don't try to solve everything
all at once.
00:22:54.533 --> 00:22:58.400
Let's take it in stride and get some wins
for your organization.
00:22:59.133 --> 00:23:00.200
Great.
00:23:00.200 --> 00:23:04.266
In closing, if there's one thing
you want listeners to take away
00:23:04.266 --> 00:23:08.833
about the future of AI and machine
learning and CRE, what would it be?
00:23:11.900 --> 00:23:14.900
That it is ever changing and
00:23:14.900 --> 00:23:19.000
the speed at
which advancements are coming are
00:23:19.666 --> 00:23:24.733
almost make it very challenging to
to stay on top of it,
00:23:24.733 --> 00:23:31.133
and I think have trusted partners,
have trusted consultants, and really,
00:23:31.200 --> 00:23:35.033
you know, lean on the larger organizations
that are out in the front lines.
00:23:35.066 --> 00:23:40.066
You know, dealing with rolling out
artificial intelligence at scale.
00:23:40.100 --> 00:23:43.066
You know, I can tell you
as an organization, we're leaning
00:23:43.066 --> 00:23:46.900
on Microsoft in many ways
and things that they're rolling out.
00:23:46.900 --> 00:23:50.666
And I think many of our clients are
leaning on us or other software vendors.
00:23:50.666 --> 00:23:54.933
And I think, you know, I would just
00:23:56.033 --> 00:24:00.866
really encourage that just because
the speed at which stuff's coming out,
00:24:00.866 --> 00:24:04.033
it's really tough for any one individual
to stay on top of it.
00:24:04.066 --> 00:24:06.933
It really takes a large group.
00:24:06.933 --> 00:24:08.033
Yeah.
00:24:08.033 --> 00:24:12.700
Brian, thank you so much for sharing
your insights on this very relevant topic.
00:24:12.800 --> 00:24:14.500
I've really enjoyed our conversation.
00:24:14.500 --> 00:24:19.066
If anyone wants to learn
more about how Yardi is embracing AI,
00:24:19.200 --> 00:24:20.700
what's the best way
00:24:20.700 --> 00:24:24.400
that you would recommend them connecting
with you or someone from your team?
00:24:24.433 --> 00:24:25.300
Yeah. No, absolutely.
00:24:25.300 --> 00:24:27.733
Yardi.com is always a great place to start.
00:24:27.733 --> 00:24:29.266
There's a lot of information
00:24:29.266 --> 00:24:32.300
on artificial intelligence
and white papers on there as well.
00:24:32.400 --> 00:24:34.900
Feel free to reach out to me directly.
00:24:34.900 --> 00:24:37.933
I keep a clean inbox
and try to respond to all emails
00:24:37.933 --> 00:24:39.633
that come through on a daily basis.
00:24:39.633 --> 00:24:40.400
It's part of my mission.
00:24:40.400 --> 00:24:43.700
It's really tough to do at times
with the volume of emails that I receive,
00:24:43.733 --> 00:24:46.733
but that's Brian.Sutherland@yardi.com
00:24:47.000 --> 00:24:52.466
and happy to help direct you and
hopefully get you to the right person
00:24:52.466 --> 00:24:55.500
within the Yardi organization,
knowing that it's sometimes
00:24:55.500 --> 00:24:58.500
tough to start on Yardi.com to get there.
00:24:58.533 --> 00:25:02.833
Do you mind if I reach out to you
on how to better keep a clean inbox?
00:25:02.900 --> 00:25:04.566
Hey, anytime.
00:25:05.633 --> 00:25:06.500
It's not an easy one.
00:25:06.500 --> 00:25:09.100
I got to tell you.
00:25:09.100 --> 00:25:11.533
A big thank you to our sponsor
for the month, Yardi.
00:25:11.533 --> 00:25:15.300
And thank you, everyone for listening
to BOMA’s Building Excellence,
00:25:15.333 --> 00:25:19.266
a CRE podcast series.
Where the conversation doesn't stop
00:25:19.266 --> 00:25:22.866
and the industry
keeps moving forward. Until next time,
00:25:22.866 --> 00:25:25.433
this is Alan Stein signing off.
00:00:08.633 --> 00:00:09.700
Welcome to BOMA’s
00:00:09.700 --> 00:00:12.700
Building Excellence, a CRE podcast series.
00:00:12.733 --> 00:00:15.133
This episode is brought to you by Yardi.
00:00:15.133 --> 00:00:17.533
I'm your host, Alan Stein.
00:00:17.533 --> 00:00:19.633
Today we're joined by Brian Sutherland,
00:00:19.633 --> 00:00:22.000
the Vice President of Commercial
for Yardi.
00:00:22.000 --> 00:00:24.933
Brian, it's great to have you here
to help us better understand
00:00:24.933 --> 00:00:28.000
the massive wave
of AI hitting the industry.
00:00:28.700 --> 00:00:31.633
Yeah.
Glad to be a part of the conversation.
00:00:31.633 --> 00:00:34.000
Before we dig into the deep
tech, let's start
00:00:34.000 --> 00:00:37.066
with a quick game of rapid
fire to get to know you a little better.
00:00:37.100 --> 00:00:39.000
Are you ready?
00:00:39.000 --> 00:00:41.000
I am ready, let's do it.
00:00:41.000 --> 00:00:41.933
All right.
00:00:41.933 --> 00:00:45.233
Favorite way to unplug from technology
on the weekend?
00:00:47.100 --> 00:00:48.800
Golfing.
00:00:48.800 --> 00:00:50.233
Love it, love it.
00:00:50.233 --> 00:00:53.233
Bucket list trip.
00:00:54.233 --> 00:00:56.700
Tokyo, Japan.
00:00:56.700 --> 00:00:57.500
Okay.
00:00:57.500 --> 00:01:00.500
Go to karaoke song?
00:01:02.900 --> 00:01:05.433
Garth Brooks - Rodeo.
00:01:07.200 --> 00:01:10.200
Favorite movie?
00:01:10.733 --> 00:01:13.200
Shawshank Redemption.
00:01:13.200 --> 00:01:16.733
And if you could only keep one app
on your phone
00:01:16.800 --> 00:01:20.133
other than email and work, of course,
what would it be?
00:01:22.500 --> 00:01:24.400
Claude.
00:01:24.400 --> 00:01:27.666
All right, look, that's a great segue
into our conversation today.
00:01:27.733 --> 00:01:31.833
So for me, it would definitely be
Apple Music, because as Elvis Presley
00:01:31.833 --> 00:01:35.466
famously said, without music,
the day would never end.
00:01:36.300 --> 00:01:39.300
Now that you've given us a quick glimpse
into who you are.
00:01:39.300 --> 00:01:41.600
Let's talk about your work with Yardi.
00:01:41.600 --> 00:01:45.433
For those of you that might not know,
can you give us a little bit
00:01:45.433 --> 00:01:48.433
of an elevator pitch on who Yardi is?
00:01:49.666 --> 00:01:51.233
Yeah, absolutely.
00:01:51.233 --> 00:01:55.700
Yardi was founded in 1984,
in Santa Barbara, California,
00:01:55.700 --> 00:01:57.666
our owner is Anant Yardi.
00:01:57.666 --> 00:02:02.133
He still remains active and involved
with the company as a chairman.
00:02:02.366 --> 00:02:06.466
At its core, Yardi is property management
and accounting.
00:02:06.466 --> 00:02:10.666
And that's really where our roots are,
and that's the foundation of our platform.
00:02:10.700 --> 00:02:16.866
So think general ledger, AP, AR,
financial reporting, customer management, etc.
00:02:16.866 --> 00:02:20.400
Increasingly, we've moved into
everything really around
00:02:20.433 --> 00:02:25.433
real estate operations, from marketing
to construction to budgeting to leasing,
00:02:25.433 --> 00:02:29.600
and really invited other folks
into the Yardi platform.
00:02:30.066 --> 00:02:31.900
From a market share perspective,
00:02:31.900 --> 00:02:36.400
about 50% of real estate
in the US runs on the Yardi platform.
00:02:36.400 --> 00:02:38.600
So, you know, many times
00:02:38.600 --> 00:02:42.600
we're referred to as a 500 pound gorilla
in terms of real estate software.
00:02:42.600 --> 00:02:46.466
But it's a fantastic company,
very family friendly
00:02:46.466 --> 00:02:49.466
and just a fantastic place to work.
00:02:49.600 --> 00:02:50.600
That's great.
00:02:50.600 --> 00:02:53.600
So tell us, you've been in the industry
for quite a while.
00:02:53.700 --> 00:02:55.833
Walk us through your journey
within the industry
00:02:55.833 --> 00:02:59.633
a little bit and also your time with Yardi
and your role with Yardi.
00:03:01.000 --> 00:03:01.466
Yeah.
00:03:01.466 --> 00:03:04.900
So prior to Yardi, I had several different
startups.
00:03:04.933 --> 00:03:07.000
Yardi was actually one of my clients.
00:03:07.000 --> 00:03:10.533
We were doing employment screening
and had an employment screening business
00:03:10.533 --> 00:03:14.466
that I had sold eventually,
but prior to that, Yardi was my client.
00:03:14.466 --> 00:03:16.233
So I was familiar with Yardi and familiar
00:03:16.233 --> 00:03:18.266
with Yardi’s
growth from a headcount perspective,
00:03:18.266 --> 00:03:21.333
certainly, and being from Santa Barbara
at that point,
00:03:21.400 --> 00:03:25.733
small town and everyone kind of knows
the larger employers in town.
00:03:25.866 --> 00:03:30.466
My experience at Yardi is varied.
So it really started on the residential side
00:03:30.466 --> 00:03:36.400
and moved to commercial pretty quickly
and launched Yardi Elevate.
00:03:36.400 --> 00:03:37.733
So I was really on the product side,
00:03:37.733 --> 00:03:41.500
working deeply
with our clients on their workflows,
00:03:41.666 --> 00:03:46.500
and that product line is quite
successful now. My day to day
00:03:46.500 --> 00:03:50.400
is overseeing the sales organization
on the commercial real estate side.
00:03:50.400 --> 00:03:51.333
So that's office,
00:03:51.333 --> 00:03:55.233
industrial, retail, co-working,
corporate real estate, self-storage.
00:03:55.400 --> 00:04:00.133
So kind of a lot under my purview
from a sales perspective.
00:04:00.200 --> 00:04:02.633
I help out with the strategic direction
of the product line,
00:04:02.633 --> 00:04:07.200
and then more recently have been tasked to
bring Virtuoso, our AI brand, to market.
00:04:07.200 --> 00:04:11.333
So have been really focused
on artificial intelligence.
00:04:11.333 --> 00:04:15.066
And that seems to be the topic everywhere
I tend to go.
00:04:15.066 --> 00:04:18.233
So look forward to talking a little bit
about that today.
00:04:18.600 --> 00:04:20.933
Yeah, absolutely. Well,
you got a couple of things on your plate.
00:04:20.933 --> 00:04:23.333
It sounds like it for sure.
00:04:23.333 --> 00:04:25.100
I do.
00:04:25.100 --> 00:04:27.600
You know,
Yardi has really leveraged
00:04:27.600 --> 00:04:31.133
AI for things
like invoice processing for years.
00:04:31.133 --> 00:04:36.333
But something shifted about 24 months ago
with the rise of large language models.
00:04:36.366 --> 00:04:41.400
How has that conversation for your
customers changed since that shift?
00:04:43.700 --> 00:04:44.100
Yeah,
00:04:44.100 --> 00:04:47.933
I think the power
of artificial intelligence was recognized.
00:04:47.933 --> 00:04:50.666
And if you look at
00:04:50.666 --> 00:04:54.400
pre-LLM, it was really around
00:04:54.533 --> 00:04:58.800
natural language
processing, machine learning,
00:04:59.166 --> 00:05:03.033
chat bots that had natural language
processing in it.
00:05:03.033 --> 00:05:06.233
And large language models really
00:05:06.233 --> 00:05:10.133
change the landscape because the end users
are really seeing the benefit of it.
00:05:10.133 --> 00:05:13.933
And whether it was doing, you know, a
simple task at work or a question
00:05:13.933 --> 00:05:17.600
that your kids might ask of you,
you know, whatever it might be.
00:05:17.600 --> 00:05:19.833
But having the ability
to go through one of these
00:05:19.833 --> 00:05:22.866
AI interfaces and really interact with it
and see the power of it,
00:05:22.900 --> 00:05:26.533
I think just brought a lot of excitement
to, certainly to our customers,
00:05:26.533 --> 00:05:29.066
but I think just more broadly out there.
00:05:29.066 --> 00:05:32.433
And it's been an exciting time, and a lot
00:05:32.466 --> 00:05:35.433
certainly has changed
even since those came out.
00:05:35.433 --> 00:05:38.733
You know, with ChatGPT really coming out
first and the other ones after that,
00:05:38.733 --> 00:05:42.233
but a lot of excitement around
large language models and AI in general.
00:05:42.700 --> 00:05:43.233
Yeah.
00:05:43.233 --> 00:05:46.466
Well, that explains a lot about the really
00:05:46.466 --> 00:05:50.100
the genesis of our conversation today
and how- on how we got here.
00:05:50.100 --> 00:05:53.500
So now let's start
talking about the fact that we are here.
00:05:53.500 --> 00:05:58.800
So it's all been a huge evolution
in AI in every industry.
00:05:58.800 --> 00:06:01.666
But commercial real estate
is no exception to that.
00:06:01.666 --> 00:06:06.466
And we've really moved
past the hype phase into a phase where
00:06:06.500 --> 00:06:10.866
including AI in your service
offerings is now table stakes.
00:06:10.900 --> 00:06:12.866
So what are we seeing?
00:06:12.866 --> 00:06:16.400
Or what are you seeing more specifically
from the C-suite
00:06:16.400 --> 00:06:20.400
as it relates to incorporating AI
into your service offerings?
00:06:22.133 --> 00:06:22.733
Yeah, I think
00:06:22.733 --> 00:06:26.300
you're spot on in terms of
AI being table stakes.
00:06:26.666 --> 00:06:30.000
I think the C-suite is asking
a lot of questions,
00:06:30.033 --> 00:06:32.933
and typically those questions
will fall on the IT group.
00:06:32.933 --> 00:06:34.300
And the questions are around
00:06:34.300 --> 00:06:38.533
how AI is going to have an impact
on their business and where they see
00:06:38.733 --> 00:06:41.866
AI kind of transforming
the way they do their day to day.
00:06:42.066 --> 00:06:47.466
And so I think that's a good thing,
because the benefit is
00:06:47.633 --> 00:06:49.133
and vision is certainly there.
00:06:49.133 --> 00:06:53.266
And the IT groups are being tasked
with how to deliver now.
00:06:53.266 --> 00:06:57.800
And they have a perceived interest
or actually
00:06:57.800 --> 00:06:59.700
actual interest from the C-suite.
00:06:59.700 --> 00:07:01.633
And with that comes budgets.
00:07:01.633 --> 00:07:04.700
When they're-- with that comes, I think,
a lot of excitement and opportunity.
00:07:04.700 --> 00:07:08.433
And so I think I view that
as a really good thing, that everyone
00:07:08.433 --> 00:07:12.666
wants to see the power
of AI across their organization.
00:07:12.933 --> 00:07:13.666
Yeah. All right.
00:07:13.666 --> 00:07:15.666
You mentioned IT groups,
00:07:15.666 --> 00:07:20.800
Are you seeing any different things
from a finance standpoint
00:07:20.800 --> 00:07:24.066
or any other personas related
to the commercial real estate space
00:07:24.066 --> 00:07:27.100
into how they're leveraging
their software partners
00:07:27.100 --> 00:07:30.233
to help navigate this,
this new-- these new waters?
00:07:30.900 --> 00:07:35.233
Yeah, I think that demands are coming
from multiple different groups,
00:07:35.266 --> 00:07:40.100
certainly from the finance side
really looking at cost savings, right?
00:07:40.100 --> 00:07:45.466
And where artificial intelligence
is going to help their bottom line.
00:07:45.700 --> 00:07:49.466
From an IT perspective,
certainly that's part of the conversation.
00:07:49.466 --> 00:07:53.300
But I think the conversation
is also around security and governance.
00:07:53.300 --> 00:07:57.100
And, you know, the user conferences
00:07:57.100 --> 00:08:00.833
or industry events
that have technology folks at it.
00:08:00.833 --> 00:08:04.933
I can tell you every single topic
is around artificial intelligence.
00:08:04.933 --> 00:08:08.500
And so they are living and breathing it
whether they wanted to or not.
00:08:08.500 --> 00:08:10.666
And they're being asked
a lot of questions.
00:08:10.666 --> 00:08:12.600
I think finance groups are too.
00:08:12.600 --> 00:08:15.933
And I would say by and large, those are
the two largest groups that we talk to.
00:08:16.000 --> 00:08:18.900
Certainly there's other influencers
within the organization.
00:08:18.900 --> 00:08:21.933
There's executives as well,
who love to get updates
00:08:21.933 --> 00:08:25.466
in terms of artificial intelligence impact
on the industry.
00:08:25.500 --> 00:08:28.900
What we're hearing from our customers,
we have a pretty good view,
00:08:28.900 --> 00:08:33.100
just given that 50% of real estate
runs on our platform.
00:08:33.166 --> 00:08:38.233
And I think, you know,
many folks are looking to their software
00:08:38.233 --> 00:08:42.400
providers to answer questions
and to make sure they have
00:08:42.400 --> 00:08:45.700
a good foundation and understanding
of the implications of AI.
00:08:48.100 --> 00:08:50.866
I love that you mentioned security.
00:08:50.866 --> 00:08:54.466
And, you know, obviously,
when it comes to new tech,
00:08:54.666 --> 00:08:58.233
the biggest worries are usually around
safety and security
00:08:58.233 --> 00:09:00.433
and who actually controls the data.
00:09:00.433 --> 00:09:04.433
How has Yardi updated its systems
to make sure a company's
00:09:04.433 --> 00:09:08.933
private information stays protected
and doesn't end up where it shouldn't be?
00:09:10.400 --> 00:09:10.733
Yeah.
00:09:10.733 --> 00:09:13.700
So I can tell you,
our lawyers have certainly been busy
00:09:13.700 --> 00:09:16.700
looking at regulations
that are coming out country by country.
00:09:16.700 --> 00:09:18.533
You know, we have a pretty broad range
00:09:18.533 --> 00:09:21.000
of 80 different countries
our platform is run on.
00:09:21.000 --> 00:09:25.700
And so each jurisdiction and country
might have their own kind of standards.
00:09:25.766 --> 00:09:30.033
I will say though, to your question,
in terms of what has changed
00:09:30.066 --> 00:09:34.466
or evolved, maybe at Yardi,
from that standpoint,
00:09:34.466 --> 00:09:36.500
we're still safeguarding our clients data
00:09:36.500 --> 00:09:39.500
the same way we have
for the last 40 plus years.
00:09:39.533 --> 00:09:42.933
And you think about the clients
that might be on our platform.
00:09:42.933 --> 00:09:45.066
It's banking institutions,
00:09:45.066 --> 00:09:49.100
sovereign wealth, large REITs
that might be on it.
00:09:49.100 --> 00:09:51.233
And so, you know,
00:09:51.233 --> 00:09:55.300
we're SOX 1, SOX 2 compliant
artificial intelligence is part of that.
00:09:55.300 --> 00:09:56.600
And so the same sort of standards
00:09:56.600 --> 00:09:59.900
you have operating in our platform
from a day to day perspective
00:09:59.900 --> 00:10:03.200
pertains to everything we're doing
from an AI perspective as well.
00:10:06.000 --> 00:10:06.733
You've introduced the
00:10:06.733 --> 00:10:10.666
concept of model
context protocol connectors.
00:10:10.900 --> 00:10:15.000
How does this allow a property management
company to use tools like Copilot
00:10:15.000 --> 00:10:18.000
or Claude with their own data?
00:10:19.300 --> 00:10:20.066
Yeah.
00:10:20.066 --> 00:10:25.033
To me, this was kind of the holy grail
of connecting to your data.
00:10:25.066 --> 00:10:30.133
I think there's been a movement
across real estate companies
00:10:30.200 --> 00:10:33.933
to get their data
and have access to their data.
00:10:33.933 --> 00:10:36.166
So those projects have been underway.
00:10:36.166 --> 00:10:40.033
What I don't think anyone saw coming
was artificial intelligence.
00:10:40.033 --> 00:10:43.066
And now the power of having your data
00:10:43.233 --> 00:10:47.833
kind of in a single platform
or accessible
00:10:47.966 --> 00:10:51.633
is really mission
critical. In terms of MCP,
00:10:52.400 --> 00:10:56.266
What we're finding is, is more and more
people are logging in through
00:10:56.300 --> 00:10:59.300
AI interfaces on a daily basis,
whether it is
00:10:59.633 --> 00:11:03.166
Claude, ChatGPT, Gemini.
00:11:05.533 --> 00:11:09.900
Or Copilot, those
are kind of the big four AI interfaces.
00:11:09.966 --> 00:11:14.600
Our goal is to give our clients
accessibility
00:11:14.600 --> 00:11:18.133
to the data that they're sitting on,
and allow them to connect through the same
00:11:18.200 --> 00:11:21.933
AI interfaces that they're logging into
every day.
00:11:22.000 --> 00:11:24.066
The nice thing is, it's not just our data.
00:11:24.066 --> 00:11:27.933
There are connectors and MCP layers
for other tools like Outlook
00:11:27.933 --> 00:11:30.333
or different things
that they might be using on a daily basis.
00:11:30.333 --> 00:11:35.433
And so this idea of co-mingling data,
wrapping around that large language
00:11:35.433 --> 00:11:38.433
model,
having your data also governed and secure
00:11:38.433 --> 00:11:42.100
and authenticated from an end user
perspective is quite powerful.
00:11:42.133 --> 00:11:46.933
And I can tell you, the outputs that
our clients are seeing are meaningful.
00:11:46.933 --> 00:11:52.800
And they're able to get details
around their real estate operations.
00:11:52.800 --> 00:11:57.666
And if they're looking at leasing
and want to look at how renewing a lease
00:11:58.000 --> 00:12:01.933
or extending a certain tenant
is going to have an impact on their NOI,
00:12:02.000 --> 00:12:03.933
they can do that on the fly
00:12:03.933 --> 00:12:08.300
through an AI interface,
not having to go into our platform.
00:12:08.300 --> 00:12:10.300
And so it is resonating.
00:12:10.300 --> 00:12:13.566
And I think people want their data
where they work.
00:12:13.600 --> 00:12:16.533
And so we're trying to
to make that part of our roadmap as well.
00:12:17.733 --> 00:12:18.933
Yeah that's great.
00:12:18.933 --> 00:12:22.400
It reminds me of something
that I always preach
00:12:22.400 --> 00:12:26.066
around the 3 Ds,
which is data driven decisions.
00:12:26.066 --> 00:12:29.233
So let the data tell you
what your decision should be
00:12:29.266 --> 00:12:31.133
and what direction
you should be taking something.
00:12:31.133 --> 00:12:35.133
So it's awesome to hear that
that you guys have really embraced in
00:12:35.133 --> 00:12:39.433
and have-- are starting to
to figure out how to, to better arm
00:12:39.533 --> 00:12:42.533
the property management world with that
data.
00:12:43.566 --> 00:12:47.333
Yardi is the single connected platform
that gives commercial real estate
00:12:47.333 --> 00:12:52.833
owners, managers and investors real time
visibility across their entire portfolio,
00:12:52.833 --> 00:12:57.200
from leasing and accounting to tenant
experience and asset performance.
00:12:57.433 --> 00:13:02.400
We've spent over 40 years building
software exclusively for this industry,
00:13:02.400 --> 00:13:06.566
and today some of the world's
largest CRE firms run on Yardi.
00:13:06.833 --> 00:13:11.000
Connect with us online or in person
at the upcoming BOMA International Expo
00:13:11.000 --> 00:13:12.466
in Long Beach, California.
00:13:12.466 --> 00:13:17.233
And let us show you what this looks like
for your property portfolio.
00:13:18.033 --> 00:13:20.600
The 2026 BOMA International Conference
00:13:20.600 --> 00:13:24.500
and Expo is where teams
get stronger and problems get solved.
00:13:24.533 --> 00:13:26.533
Experience the power of connection,
00:13:26.533 --> 00:13:30.633
learning and innovation,
plus the best expo in the industry.
00:13:30.666 --> 00:13:34.466
Learn more at 2026.bomaconvention.org.
00:13:35.466 --> 00:13:36.866
We look forward to seeing you
00:13:36.866 --> 00:13:39.866
this June in Long Beach, California.
00:13:40.733 --> 00:13:42.600
So okay, now let's
00:13:42.600 --> 00:13:45.800
transition into agents
in the future of workflow.
00:13:45.833 --> 00:13:48.900
So how do you see the future of
AI playing out
00:13:48.900 --> 00:13:51.333
and helping property managers
with daily tasks?
00:13:51.333 --> 00:13:54.833
You touched on that a little bit,
but maybe a little more specific.
00:13:57.033 --> 00:13:58.900
Yeah, absolutely.
00:13:58.900 --> 00:14:03.633
When you're looking at real estate
companies, I think one kind of use case
00:14:03.633 --> 00:14:07.733
is residential fee managers
and large residential fee managers.
00:14:07.733 --> 00:14:08.666
And if you look at the way
00:14:08.666 --> 00:14:12.666
their organizations are laid out,
there's certainly segregation of duties.
00:14:12.666 --> 00:14:17.733
And they'll have people that are,
you know, on site and interacting
00:14:17.733 --> 00:14:21.000
with their customers
or prospective customers one on one.
00:14:21.033 --> 00:14:25.533
You'll have people that are managing
AP approvals and vendor relationships or,
00:14:26.133 --> 00:14:28.866
or individuals that are doing AR.
00:14:28.866 --> 00:14:34.133
And so I think if you look at
the organizations that way and understand
00:14:34.400 --> 00:14:38.200
where these agentic flows can create
00:14:38.233 --> 00:14:42.600
time savings or more efficiencies
or cost savings in many cases,
00:14:42.833 --> 00:14:45.700
really think of it
in terms of having agent coworkers
00:14:45.700 --> 00:14:50.233
next to each one of those individuals
and making them more efficient.
00:14:50.233 --> 00:14:53.666
And so, you know,
horizontally across the organization,
00:14:53.666 --> 00:14:57.866
all these different users, them
doing different tasks and having agents
00:14:57.900 --> 00:15:03.100
augmenting that kind of day to day is,
is, I think is a good way to look at it.
00:15:03.100 --> 00:15:06.700
And I think the way
we're certainly looking at it as well,
00:15:06.800 --> 00:15:09.433
working with our clients,
really understanding
00:15:09.433 --> 00:15:13.900
their kind of workflows,
and then where these agentic workflows
00:15:13.900 --> 00:15:17.433
are going to be improved
by this technology that's there.
00:15:18.133 --> 00:15:18.666
Yeah.
00:15:18.666 --> 00:15:23.100
You talk about agents at scale
or agent coworkers.
00:15:23.100 --> 00:15:25.000
Can you paint for us--
00:15:25.000 --> 00:15:27.233
Give us a couple examples
maybe, or paint for us
00:15:27.233 --> 00:15:30.866
a little better picture
of how those agents might better help
00:15:30.866 --> 00:15:34.633
with daily tasks like AP, AR,
or even customer interactions?
00:15:35.900 --> 00:15:36.700
Yeah,
00:15:36.700 --> 00:15:40.400
just
a little view into our payment processing.
00:15:40.433 --> 00:15:43.800
And this is for an example,
75 million invoices go through it
00:15:43.800 --> 00:15:46.300
on a-- on an annual basis.
00:15:46.300 --> 00:15:47.000
Each invoice
00:15:47.000 --> 00:15:50.933
in terms of getting approved for payment
goes through about four workflow steps.
00:15:50.966 --> 00:15:54.600
And so that's about 300 million
00:15:54.600 --> 00:15:57.633
steps across our client base.
00:15:57.800 --> 00:16:01.133
Each one of those ste--, steps,
excuse me, takes about two minutes.
00:16:01.133 --> 00:16:05.600
So that's about 600 million minutes,
which equates to about 10 million hours
00:16:05.600 --> 00:16:08.333
that our clients spend approving invoices.
00:16:08.333 --> 00:16:10.233
So quite a bit of time.
00:16:10.233 --> 00:16:15.000
So if you can automate that process,
if you can have logic that goes through
00:16:15.500 --> 00:16:19.900
the system and sees
what invoices have been approved
00:16:19.900 --> 00:16:24.600
and sets up rules over the say based upon
the last 12 months of processing,
00:16:24.900 --> 00:16:29.200
it is a huge benefit to our clients
from a time savings perspective,
00:16:29.200 --> 00:16:33.133
not to have a human going in there
and approving these invoices.
00:16:33.133 --> 00:16:37.200
It might be lower dollar amounts
and gaining trust over time that this
00:16:37.200 --> 00:16:41.000
AI model is working,
that the auditability of it
00:16:41.000 --> 00:16:44.066
is more than you can audit
when a human approves invoices.
00:16:44.066 --> 00:16:49.833
So that's like a very kind of narrow
use case of where an agentic flow
00:16:49.966 --> 00:16:53.100
can really benefit our clients,
because just the sheer
00:16:53.133 --> 00:16:57.666
volume of invoices
that go through real estate organizations
00:16:57.666 --> 00:17:02.066
and you approve that process
and it can have a material impact.
00:17:02.500 --> 00:17:03.800
Oh, yeah. Absolutely.
00:17:03.800 --> 00:17:04.733
I mean, you can just
00:17:04.733 --> 00:17:08.466
you can just, you know, hear the
the dollar signs ringing up there.
00:17:08.466 --> 00:17:11.566
And, you know, as
far as the savings from a, from a time
00:17:11.566 --> 00:17:14.933
and money standpoint,
I mean, that's incredible.
00:17:15.133 --> 00:17:15.800
Yeah. Yeah.
00:17:15.800 --> 00:17:20.800
And you know, on those invoices, a lot of
vendors have payment terms as well.
00:17:20.800 --> 00:17:25.000
And if you look at the vendors that are
servicing these real estate properties,
00:17:25.033 --> 00:17:27.900
a lot of them have cash flow issues
and they're looking for early payments.
00:17:27.900 --> 00:17:31.033
So these invoices will indicate
if there's, you know, there
00:17:31.033 --> 00:17:34.533
could be a discount
based upon early payment.
00:17:34.566 --> 00:17:38.333
And, you know, if you're able
to process those invoices, figure out
00:17:38.333 --> 00:17:42.200
which vendors have payment terms at scale.
00:17:42.333 --> 00:17:44.433
Roll that out across all of your vendors.
00:17:44.433 --> 00:17:47.500
That's a serious cost savings that you can have
00:17:47.533 --> 00:17:51.133
in terms of your vendor MRO spend.
00:17:51.200 --> 00:17:53.666
And so that's
just another little example.
00:17:53.666 --> 00:17:56.666
So kind of taking that invoice
and what's something else that we can
00:17:56.666 --> 00:17:58.666
potentially do with it
with an agent.
00:17:58.666 --> 00:18:03.300
And so just a lot of opportunity
across real estate operations.
00:18:03.933 --> 00:18:04.733
Yeah.
00:18:04.733 --> 00:18:10.300
So I say this quite often
that a property manager wears so many hats
00:18:10.333 --> 00:18:12.100
and they have to rely
00:18:12.100 --> 00:18:16.666
so heavily on their vendor partners
to be the experts in these areas.
00:18:16.666 --> 00:18:22.800
So for the property manager on the ground,
how does an AI forward software
00:18:22.933 --> 00:18:28.033
really translate
maybe to some cost or time savings,
00:18:28.033 --> 00:18:31.466
specifically in the operational side
of what
00:18:31.466 --> 00:18:34.833
they are responsible
for doing on a day to day basis?
00:18:35.700 --> 00:18:37.466
Yeah, and you're absolutely right.
00:18:37.466 --> 00:18:41.300
There is a ton of responsibilities
and a lot has to come with,
00:18:41.333 --> 00:18:45.633
you know, the interactions that they're
having with prospective residents
00:18:45.633 --> 00:18:50.933
at a property, for example, or demand
from existing tenants that are there.
00:18:50.933 --> 00:18:54.800
And so if we can think about, again,
those roles
00:18:54.800 --> 00:18:58.033
and kind of the work streams that they're
dealing with on a daily basis.
00:18:58.033 --> 00:19:02.400
And so I think a good example of that
is prospects coming into a property
00:19:02.400 --> 00:19:06.900
and interacting with a chat agent,
as opposed to a live agent,
00:19:06.900 --> 00:19:10.866
and doing things like setting up a tour
and automating that process
00:19:10.866 --> 00:19:13.866
and giving that resident--
prospective resident the ability
00:19:13.866 --> 00:19:16.933
to schedule a tour, give them a code
to actually get in the door.
00:19:17.033 --> 00:19:17.233
You know,
00:19:17.233 --> 00:19:20.933
those sort of things that are really taking
the burden from that property manager and
00:19:20.933 --> 00:19:24.866
allowing them to focus on the customers
that they have already at the property
00:19:24.866 --> 00:19:28.100
and really automating the prospect
workflow instead.
00:19:28.100 --> 00:19:30.533
And so that would just be like
another example.
00:19:30.533 --> 00:19:35.900
But, you know, across
any specific individual, I think within
00:19:35.933 --> 00:19:41.133
these real estate companies that we serve,
there are benefits of rolling out AI.
00:19:41.233 --> 00:19:44.200
There are material impacts of it
00:19:44.200 --> 00:19:47.400
from a risk perspective, time savings
perspective, cost perspective.
00:19:47.400 --> 00:19:50.466
And those kind of three areas
are the three pillars
00:19:50.466 --> 00:19:54.400
that we kind of focus in on
when we're thinking about our next kind
00:19:54.400 --> 00:19:57.633
of initiative around
artificial intelligence.
00:19:59.233 --> 00:20:00.733
That's great.
00:20:00.733 --> 00:20:04.333
Only the tip of the iceberg
as it relates to, I think, the power
00:20:04.333 --> 00:20:08.633
that we're going to be seeing from AI
and the commercial real estate space.
00:20:08.633 --> 00:20:14.400
So a couple more questions as
we look to wrap up our conversation around
00:20:14.433 --> 00:20:18.866
AI and what leaders in the industry
should be thinking as far as next steps.
00:20:18.900 --> 00:20:23.066
So, you know, you're very involved in the
AI sections of CRE.
00:20:23.066 --> 00:20:27.233
What would you say
is the biggest misconception
00:20:27.233 --> 00:20:31.433
that leaders currently
have about AI's impact on their business?
00:20:32.300 --> 00:20:38.666
Yeah, I think there is a misconception or,
you know, a look at AI
00:20:38.700 --> 00:20:42.666
where it's a reduction of headcount
is a potential option.
00:20:42.666 --> 00:20:46.466
And I think we like to view it
as it's
00:20:46.466 --> 00:20:49.933
an opportunity
for expansion of current roles.
00:20:49.933 --> 00:20:54.333
And, you know, the way we're looking at it
internally, if our workers,
00:20:54.400 --> 00:20:58.233
if our Yardi employees, for example,
have more capacity,
00:20:58.333 --> 00:21:01.266
we can increase the live support
that we have with our clients.
00:21:01.266 --> 00:21:05.200
So improving our customer service,
and I think with real estate
00:21:05.200 --> 00:21:07.233
operations, it's very similar.
00:21:07.233 --> 00:21:11.200
And I mentioned the example earlier
of the property manager
00:21:11.200 --> 00:21:14.866
and that prospect kind of workload
and interaction coming through.
00:21:15.066 --> 00:21:17.200
That gives them more capacity.
00:21:17.200 --> 00:21:21.733
Now they can focus on improving customer
service, retaining their residents, etc..
00:21:21.733 --> 00:21:26.266
And so I think it's just--
it opens up a lot more opportunities
00:21:26.266 --> 00:21:29.600
within your organizations.
00:21:29.600 --> 00:21:33.600
These real estate companies, organizations
and the folks that are interacting
00:21:33.633 --> 00:21:38.200
with their customers with the finance
group, whatever it might be.
00:21:39.300 --> 00:21:40.000
Right.
00:21:40.000 --> 00:21:41.666
Makes lot of sense.
00:21:41.666 --> 00:21:46.100
So looking at the broader landscape
of property technology integration,
00:21:46.533 --> 00:21:50.033
what should companies be doing right now
00:21:50.066 --> 00:21:54.666
to prepare for their data
for an AI driven 2026?
00:21:55.333 --> 00:21:58.266
Yeah, well, I think data can live in
00:21:58.266 --> 00:22:01.600
silos and data can be unstructured.
00:22:01.800 --> 00:22:05.100
And so there are those
00:22:05.300 --> 00:22:08.133
foundational views of data
00:22:08.133 --> 00:22:12.433
that I think
need to be addressed for impactful AI.
00:22:12.433 --> 00:22:15.466
I would also say
00:22:16.100 --> 00:22:20.700
to not look at it, having to do everything
for you out of the gate.
00:22:20.700 --> 00:22:24.466
And I think there needs to be trust
that's built out
00:22:24.466 --> 00:22:26.066
around artificial intelligence.
00:22:26.066 --> 00:22:29.733
I think there needs to be wins
out of the gate.
00:22:29.866 --> 00:22:32.300
Many AI projects fail as well.
00:22:32.300 --> 00:22:33.800
So start narrow.
00:22:33.800 --> 00:22:35.900
Start with something very specific.
00:22:35.900 --> 00:22:40.500
Start with a, hopefully a win,
and then iterate and build upon that.
00:22:40.500 --> 00:22:42.466
And that's going to keep the C-suite
00:22:42.466 --> 00:22:45.400
wanting to continue to invest
in artificial intelligence.
00:22:45.400 --> 00:22:48.633
It's going to keep the IT groups wanting,
you know, giving them
00:22:48.633 --> 00:22:51.833
the ability to continue to innovate
and see where AI can have an impact.
00:22:51.833 --> 00:22:54.533
But don't try to solve everything
all at once.
00:22:54.533 --> 00:22:58.400
Let's take it in stride and get some wins
for your organization.
00:22:59.133 --> 00:23:00.200
Great.
00:23:00.200 --> 00:23:04.266
In closing, if there's one thing
you want listeners to take away
00:23:04.266 --> 00:23:08.833
about the future of AI and machine
learning and CRE, what would it be?
00:23:11.900 --> 00:23:14.900
That it is ever changing and
00:23:14.900 --> 00:23:19.000
the speed at
which advancements are coming are
00:23:19.666 --> 00:23:24.733
almost make it very challenging to
to stay on top of it,
00:23:24.733 --> 00:23:31.133
and I think have trusted partners,
have trusted consultants, and really,
00:23:31.200 --> 00:23:35.033
you know, lean on the larger organizations
that are out in the front lines.
00:23:35.066 --> 00:23:40.066
You know, dealing with rolling out
artificial intelligence at scale.
00:23:40.100 --> 00:23:43.066
You know, I can tell you
as an organization, we're leaning
00:23:43.066 --> 00:23:46.900
on Microsoft in many ways
and things that they're rolling out.
00:23:46.900 --> 00:23:50.666
And I think many of our clients are
leaning on us or other software vendors.
00:23:50.666 --> 00:23:54.933
And I think, you know, I would just
00:23:56.033 --> 00:24:00.866
really encourage that just because
the speed at which stuff's coming out,
00:24:00.866 --> 00:24:04.033
it's really tough for any one individual
to stay on top of it.
00:24:04.066 --> 00:24:06.933
It really takes a large group.
00:24:06.933 --> 00:24:08.033
Yeah.
00:24:08.033 --> 00:24:12.700
Brian, thank you so much for sharing
your insights on this very relevant topic.
00:24:12.800 --> 00:24:14.500
I've really enjoyed our conversation.
00:24:14.500 --> 00:24:19.066
If anyone wants to learn
more about how Yardi is embracing AI,
00:24:19.200 --> 00:24:20.700
what's the best way
00:24:20.700 --> 00:24:24.400
that you would recommend them connecting
with you or someone from your team?
00:24:24.433 --> 00:24:25.300
Yeah. No, absolutely.
00:24:25.300 --> 00:24:27.733
Yardi.com is always a great place to start.
00:24:27.733 --> 00:24:29.266
There's a lot of information
00:24:29.266 --> 00:24:32.300
on artificial intelligence
and white papers on there as well.
00:24:32.400 --> 00:24:34.900
Feel free to reach out to me directly.
00:24:34.900 --> 00:24:37.933
I keep a clean inbox
and try to respond to all emails
00:24:37.933 --> 00:24:39.633
that come through on a daily basis.
00:24:39.633 --> 00:24:40.400
It's part of my mission.
00:24:40.400 --> 00:24:43.700
It's really tough to do at times
with the volume of emails that I receive,
00:24:43.733 --> 00:24:46.733
but that's Brian.Sutherland@yardi.com
00:24:47.000 --> 00:24:52.466
and happy to help direct you and
hopefully get you to the right person
00:24:52.466 --> 00:24:55.500
within the Yardi organization,
knowing that it's sometimes
00:24:55.500 --> 00:24:58.500
tough to start on Yardi.com to get there.
00:24:58.533 --> 00:25:02.833
Do you mind if I reach out to you
on how to better keep a clean inbox?
00:25:02.900 --> 00:25:04.566
Hey, anytime.
00:25:05.633 --> 00:25:06.500
It's not an easy one.
00:25:06.500 --> 00:25:09.100
I got to tell you.
00:25:09.100 --> 00:25:11.533
A big thank you to our sponsor
for the month, Yardi.
00:25:11.533 --> 00:25:15.300
And thank you, everyone for listening
to BOMA’s Building Excellence,
00:25:15.333 --> 00:25:19.266
a CRE podcast series.
Where the conversation doesn't stop
00:25:19.266 --> 00:25:22.866
and the industry
keeps moving forward. Until next time,
00:25:22.866 --> 00:25:25.433
this is Alan Stein signing off.
