Imagine transforming your multifamily business with AI so effectively that your employees are freed from the menial to engage in the meaningful.
That's what we're unpacking today—how the savvy application of AI and automation isn't just solving problems but revolutionizing multifamily operations. We delve into the nitty-gritty of identifying inefficiencies, cutting out the unnecessary, and embracing generative AI that can eradicate up to 70% of manual tasks.
This isn't about replacing human ingenuity; it's about amplifying it, keeping people at the center, and leveraging technology to bolster their capabilities.
In our candid conversation, we introduce advanced, industry-specific platforms like Multifamily GPT, inmultifamily.com, and multifamilydata.io, and discuss how they're creating a data-driven renaissance in the business.
We've put together a framework that starts with people, injects AI, centralizes data, and loops back to the human element, thus fostering a virtuous cycle of enhanced decision-making and business growth.
This episode isn't just about the 'what' and 'how' of AI integration—it's a blueprint for the future of multifamily businesses that are ready to thrive in an evolving marketplace.
Thank you for tuning in to today’s episode. If you found value in our conversation, please subscribe to our podcast on your favorite platform and leave us a rating and review.
Your feedback not only helps us improve but also helps others find us. And if today’s episode sparked a thought or provided a new insight, consider sharing it with a friend who might also benefit.
Together, we can grow our community and continue to learn and innovate. Thanks for listening, and until next time,
nectarflow™ - AI, Automations & Business Integrations
Interested in a FREE webinar on how to bring AI & Automations into your business? Join us live at our upcoming webinar https://events.multifamilyleadership.com/event-registration
Speaker 1: Alright, today I'm talking about applied AI in a
00:00:04
multifamily business, and this is a framework that I've
00:00:10
developed inside and talking with multifamily owners and
00:00:16
operators and, obviously, getting educated myself, but
00:00:21
also spending my own money developing things.
00:00:23
This is a framework that I've used after having Hundreds,
00:00:30
actually thousands, of conversations, listening for two
00:00:32
years around the current challenges, the current
00:00:35
priorities and the current current bigger and better
00:00:38
futures that multifamily owners and operators are Trying to
00:00:42
create in their organizations, both from a.
00:00:44
I'm an employee and I want to do bigger and better things, but
00:00:48
my company is so wildly successful they're familiar with
00:00:52
a process that that Isn't the best process today.
00:00:57
However, they're incredibly successful.
00:01:02
So how do I move through that change Right?
00:01:04
How do I get them to understand a new way of working that will
00:01:10
get them the similar results but also reduce risk and maybe
00:01:15
leverage some opportunities?
00:01:16
And Then there's the conversation around AI, and then
00:01:23
obviously generative AI and then the concept of automation,
00:01:31
and Now we're getting into business decisions like
00:01:34
centralization, and you know, I look at the corporate office and
00:01:38
we've been centralized forever, so a lot of companies are going
00:01:41
back to that, but it's not great for everybody and it's not
00:01:45
understood by everybody, and and they're in this framework
00:01:51
I'm going to share with you today I think it'll give you a
00:01:54
lot of pause and how you approach Just purchasing
00:01:59
something right now to fix fix a problem.
00:02:01
Now I operate around what's called first principles thinking
00:02:04
.
00:02:04
I'm going to do another episode on what that means if you want
00:02:08
to.
00:02:08
Before you listen to that, you can Just go to YouTube and learn
00:02:12
about what that means it's.
00:02:13
It's a really good thinking process that you know.
00:02:16
Elon Musk has said that oftentimes one of the best thing
00:02:19
, the best engineers in the world sometimes they Optimize
00:02:22
something that shouldn't exist and when you use first
00:02:26
principles thinking, you start to think about well, wait, what
00:02:29
are we trying to fix a problem?
00:02:30
We're putting all this resources into fixing a problem
00:02:33
that doesn't exist or shouldn't exist, maybe the step in the
00:02:37
process.
00:02:38
So my view on all this by not only developing technology, but
00:02:48
also spending time with Running these companies and then also
00:02:53
spending time with those that have run much bigger and more
00:02:55
diverse portfolios than I have, I've got a really good sort of
00:03:02
Inside look at this and what I'm going to tell you.
00:03:05
The framework that I came up with I'm calling the applied AI
00:03:09
and multifamily business.
00:03:10
I Believe that it begins and ends with people, and what that
00:03:21
means is and and I will I will be providing Webinars and some
00:03:28
other training on this framework .
00:03:30
But if we think about why we want to automate or why we want
00:03:37
AI right in our business, it's because we're looking to Do
00:03:42
something that's going to give us a competitive advantage or
00:03:45
maybe get the redundant work Away from people because they're
00:03:49
quitting, they don't want to work and do these things.
00:03:52
We're using software that requires us to copy paste, move
00:03:56
something from system A to system B, and and our employees
00:04:00
are like Wasting their time on this stuff.
00:04:04
And, by the way, most of the technology and software that
00:04:08
you're buying today Our dashboard centered.
00:04:12
In other words, they're making the assumption they built that
00:04:16
technology with technical debt that you're going to be sitting
00:04:19
in front of a computer working and, guess what?
00:04:23
Everybody's got a TV, a radio phone, computer in their pocket.
00:04:28
They're not even in the offices anymore, like they used to be,
00:04:33
right?
00:04:33
So all this technology was built with dashboards, right?
00:04:37
I don't need to see the dashboard, I need the answer to
00:04:40
the equation.
00:04:41
I need the answer to the thing so I can make the decision.
00:04:45
So this framework I'm going to share with you is going to take
00:04:49
the the idea of bringing AI, generative AI and automations
00:04:56
into your business in a way that doesn't require you to take on
00:05:00
any risks, upset anything that's already in place, and actually
00:05:07
it's going to make your business better, because You're going to
00:05:12
think about something that you may not have Thought about as
00:05:15
intentional and tell this point.
00:05:17
So I'm going to give you the stages, and the goal here is to
00:05:24
Think of.
00:05:24
I want you to just think about what takes 10 minutes of your
00:05:30
time.
00:05:31
10 minutes, all right.
00:05:34
If you had to do something for just 10 minutes and you had to
00:05:40
do it five times a week, once a day, it's 10 minutes, it's
00:05:46
nothing.
00:05:46
But you had to do it every day that you were working Monday
00:05:50
through Friday and you made every employee do that thing and
00:05:57
you had 50 employees.
00:05:59
We're talking about that thing happening 250 times in a given
00:06:05
week, with it taking 10 minutes.
00:06:09
That's 2 minutes to complete that task.
00:06:14
If you add that up over a month , that's 10 minutes.
00:06:19
That's 120 minutes a year and that's almost 167 hours a
00:06:28
month across the company.
00:06:30
And if you're paying people $60 a year, fully loaded
00:06:36
like insurance and all that stuff, that's like $29 an hour
00:06:45
for those 50 people to be doing this.
00:06:47
You're paying people a lot of money to do very silly things.
00:06:54
If you had all your employees, those 50 people at $60 a
00:07:00
year, by the way, you're paying people a lot more than that.
00:07:02
I know that that would be $1 an hour for a meeting.
00:07:10
Everybody was in a meeting at the same time.
00:07:13
So we're not doing the math right.
00:07:17
And something as simple as that over 50 employees of 10 minute
00:07:22
task is almost $60 a year to the company as an expense, some
00:07:30
$57 or something like that.
00:07:32
So imagine I can take that 10 minutes and do it in 3 minutes.
00:07:43
Would that be better?
00:07:46
That would be a 70% automation of the task.
00:07:53
And what we're doing is we're going to keep the people in
00:07:57
front of the task and at the end of the task, because we like to
00:07:59
be comfortable, we like to be involved and, by the way, that's
00:08:02
what is the differentiator, that's the magic.
00:08:04
It's not going to replace people, it's going to make
00:08:10
people smarter, and if the software that you're buying
00:08:14
today isn't making you smarter, it's not the right software.
00:08:16
So when we can automate 70% of a task a 10 minute task we can
00:08:24
take it from 10 minutes to 3 minutes.
00:08:25
You take a $57 annual expense down to $17 annual
00:08:31
expense.
00:08:32
You know that's what some $40 of found money.
00:08:39
If you're a leader, you may not be doing the math.
00:08:42
I have the schedules to help you do the math but this is the
00:08:47
framework I'm talking about Now, with generative AI paired with
00:08:53
business automation, what we're going to do is we're going to
00:08:58
accelerate our team's capabilities.
00:09:01
Now, in my last episode, I talked about that with the
00:09:04
seesaw.
00:09:05
The state of AI and how fast it's moving can feel like hype,
00:09:10
but it's not.
00:09:10
It's just the capabilities aren't there.
00:09:12
Well, with generative AI and automation, we can accelerate
00:09:16
our capabilities, reinvest in our people.
00:09:19
This is going to lead to more profitable and more efficient
00:09:24
and more effective and more creative organizations.
00:09:28
This is why we're here.
00:09:34
If you're not all in on this stuff, you're missing it.
00:09:39
You're leaving money on the table.
00:09:42
You're leaving opportunity on the table.
00:09:44
You may be leaving your hours, your time, your life on the
00:09:49
table, literally like your time, your energy, your momentum.
00:09:54
Now I'm going to take you through the phases Again.
00:10:01
People begin and end the process.
00:10:04
People, your people to be your leasing agent, investor,
00:10:09
whatever it is.
00:10:09
Your people begin and your people will end the process.
00:10:13
Now, this isn't how you have to design it.
00:10:18
I gave you a very easy thing to think about 10 minute task.
00:10:22
I did the math for you on a 50 person company.
00:10:26
I mean, if you have a 2 person company, you can really
00:10:29
start to see the impact here.
00:10:30
Even at one person, it matters.
00:10:34
I said generative AI and automation will take 70% of the
00:10:42
thing you're doing.
00:10:42
Now I'm not talking about something complicated that's
00:10:45
going to hurt the business and put you in as risk.
00:10:48
I said a 10 minute task, automating 70% of it.
00:10:52
That's what we have to think through.
00:10:55
The reason for that is because once people experience this,
00:11:02
they'll do more of it.
00:11:03
You know what your employees, once they see a 10 minute task
00:11:08
go to three minutes and they only had to do the really cool
00:11:11
stuff they will see the business differently.
00:11:17
They will be looking for opportunities for you instead of
00:11:21
threatened by them.
00:11:25
People begin in the process.
00:11:27
Let's start with the number one thing.
00:11:30
That's where people are.
00:11:31
This is your teams.
00:11:35
They are going to initiate the process.
00:11:37
They're going to define what needs to happen.
00:11:48
Then they're going to set these things in motion the
00:11:52
automations, the triggers, all these things.
00:11:55
Now that's step one People they're going to initiate the
00:12:01
process.
00:12:01
They're going to understand the task, they know what has to
00:12:05
happen in the current state of things, they're going to set
00:12:09
those automations in motion.
00:12:15
The second stage is process.
00:12:17
This is probably the most underestimated part of the
00:12:21
entire equation because it's not interesting.
00:12:23
There's no hype around it.
00:12:25
There's no SOPs, standard operating procedures.
00:12:28
How do we communicate?
00:12:30
How do we instructionally design training that people will
00:12:36
actually consume and make the business better?
00:12:38
With so much turnover, if you don't have a documented process,
00:12:43
it's going to be very taxing on you.
00:12:46
Now I just did the math on 10 minutes.
00:12:47
Imagine how much time does it take to train and retrain
00:12:50
somebody?
00:12:51
Those numbers are much greater, right?
00:12:54
So a process when we build an automation, we record a video of
00:12:59
it, we deploy it, we have a schematic, like an architectural
00:13:02
plan.
00:13:02
We know what, who's doing things, where is it going, where
00:13:08
is it stored, who has access to it right, screenshots, a
00:13:14
documentation of written scope of the process in the end, right
00:13:19
, and that allows us, like an architect when it builds an
00:13:23
apartment building, to make something great.
00:13:25
So that's the second step.
00:13:27
So the first step was people, the second step is process and
00:13:32
that's just really the sequence.
00:13:34
The process is like what are these actions that are being
00:13:37
taken to make this task happen efficiently?
00:13:41
And we're not even talking about AI or automation at this
00:13:45
point.
00:13:45
We're just like this is what has to happen, in this order.
00:13:50
Now the third thing is AI bringing generative AI and AI AI
00:13:56
applications into the business workflow.
00:14:00
Now I'm not talking about chat, gpt and prompting and prompt
00:14:03
engineering and and doing those things, because those Things are
00:14:06
happening out in the public world like toys.
00:14:09
Lots of new things are going to spin off from that, but
00:14:12
eventually, like in my last episode, it's of the hype.
00:14:15
It's like electricity everybody will have it.
00:14:17
You've already had it, had it.
00:14:19
You had Grammarly, right?
00:14:22
You stop trying to spell things .
00:14:23
It was in.
00:14:24
It's now in every application.
00:14:26
There's no longer a differentiator, right?
00:14:27
You start your emails, start self Generating suggested
00:14:33
messages on text threads, things like that.
00:14:35
It's not a differentiator, you are the differentiator.
00:14:40
But when you can bring AI and automations to your unique
00:14:46
company, your unique process, your unique people, that's the
00:14:53
third step.
00:14:54
It's going to enhance decision-making Because it
00:14:58
understands the process and understands the sequence of
00:15:00
actions and it's going to identify opportunities for
00:15:06
optimization For your business, right?
00:15:08
So that's the third one AI, so it's people process AI,
00:15:15
generative AI into your business .
00:15:15
And once you have that, next is automation, and this is where
00:15:24
we are reducing the manual effort by 70% and streamlining
00:15:31
tasks that need to be executed for your people.
00:15:33
Now think about how that's going to unlock people's world
00:15:37
life, creative thinking, and that's where we have the
00:15:43
platform that moves things through automations and
00:15:48
sequences so people can do the work that they love.
00:15:50
The next thing is data, and data drives the automation, because
00:15:58
when you're moving this, when you're using generative AI and
00:15:59
AI and you're automating it, you have to change the way the data
00:16:02
flows.
00:16:03
Integrations is only a problem because we don't have access to
00:16:10
our own data or you haven't.
00:16:12
You haven't changed the way the data flows.
00:16:13
Back to my thought around integration, or what Elon must
00:16:20
said about.
00:16:21
Sometimes we often optimize something that shouldn't exist.
00:16:22
The only reason why you have an integration problem is because
00:16:27
you don't have a lot of data.
00:16:28
The only reason why you have an integration problem is because
00:16:33
you don't have your own data.
00:16:34
So if you had your own data, you wouldn't need to you, you
00:16:40
wouldn't need to get it out.
00:16:41
You would have it before it goes in, right, and there's a
00:16:45
whole nother conversation on that but data, centralized data,
00:16:49
right.
00:16:51
Is that?
00:16:52
That other piece?
00:16:53
And then that final piece is people that come in behind,
00:16:58
right?
00:16:58
So you got people that start it with people, process, ai,
00:17:03
generative AI, automation, data, people and that's the framework
00:17:10
.
00:17:10
And that framework what's interesting is for us, we have a
00:17:14
platform that brings all that together the process, the AI,
00:17:19
the automation and the data and what you do is you sandwich that
00:17:23
, right, and with that middle piece, we're taking out 70, 80,
00:17:29
90 percent in many cases, 100 percent of the work, but it's
00:17:33
reasonable to say 70 and take a 10 minute task to three and get
00:17:37
started.
00:17:37
And once you get started, you build more confidence, you build
00:17:41
more capabilities and you start taking on more and you're more
00:17:46
familiar with it.
00:17:46
But the heart of this is this framework.
00:17:51
At first, a lot of people want to go right to automation, or
00:17:53
they want to go right to data, or they want to go right to AI,
00:17:57
and they haven't factored all these things together on how
00:17:59
they integrate together.
00:18:00
And that's why we have our platforms.
00:18:05
We have inmultifamilycom, which is the automation.
00:18:08
We have multifamily GPT, which is the generative AI, the
00:18:15
multifamily GPT, generative AI, which means it's not a race to
00:18:18
the bottom where everything else is going to be.
00:18:20
Everybody else has it, not everybody else is going to have
00:18:24
multifamily GPT In a platform that can be accessed and
00:18:32
automated through workflows that you've orchestrated with your
00:18:34
teams and then we move it into data.
00:18:39
So we also have multifamilydataio, which
00:18:41
together multifamily GPT with the generative AI automated on
00:18:47
inmultifamilycom platform so we can move the tasks around and
00:18:56
then, when it's doing the things putting that data in a place
00:19:01
that's turning like your spreadsheet into an API, putting
00:19:07
those things together multifamily GPT,
00:19:09
inmultifamilycom and multifamilydataio those things
00:19:16
together are the heart of how you bring all these things into
00:19:18
one sequence.
00:19:19
That makes the business better and the first phase of this we
00:19:25
don't our people begin and end the process.
00:19:26
The platform and those technologies happen all the way.
00:19:29
I want to lean into more of the multifamily GPT.
00:19:32
Just because why it's different from chat GPT and like a
00:19:34
co-pilot and these other things that may exist out there is
00:19:36
because are you buying a software today off the shelf
00:19:44
from a business?
00:19:45
Sometimes somebody makes a technology for many people and
00:19:48
then they try and sell it.
00:19:49
The problem with that is all these multifamily companies are
00:19:55
so unique and different.
00:19:56
It's hard to scale, it's hard to grow and it's hard to use
00:19:59
those technologies because you're trying to make it do
00:20:00
something and it won't do that and you may not have the support
00:20:06
or influence over the development of the software.
00:20:08
You're trying to make it do something and it won't do that
00:20:11
and you may not have the support or influence over the
00:20:14
development roadmap to do that.
00:20:18
And so with in multifamily and multifamily GPT, and then, of
00:20:21
course, together with multifamilydataio, you have all
00:20:24
the tools and all those things and an outside innovation team
00:20:27
to help you build the thing that you need in like a
00:20:30
microservices, micro solutions or platform approach to make
00:20:36
your business better.
00:20:37
So a lot of times we think we have to buy technology.
00:20:40
In a lot of cases you can just build it.
00:20:42
So with Multifamily GPT, you may have a portfolio of 20
00:20:51
properties and you're seeing a lot of large language models do
00:20:56
things in the public.
00:20:57
And then you're seeing big platforms bring AI to
00:21:00
applications, but they're bringing it the same thing to
00:21:04
everybody and it's not unique, it's not different.
00:21:08
They don't know your customer, they don't know your business
00:21:11
objectives, they don't have that model.
00:21:14
So Multifamily GPT allows you to retrieve company data and use
00:21:20
it all across the internet with APIs, open APIs to the online
00:21:24
database MultifamilyDataio and use it wherever else you want it
00:21:29
, but it allows you to use retrieval, which is retrieval,
00:21:35
augmented generation, which is RAG, and using embeddings and
00:21:39
things like that, leveraging different ways to access the API
00:21:43
.
00:21:43
That's not training the large language model.
00:21:47
So when Multifamily GPT is interacting with your workflow
00:21:53
or prompt or whatever you're working on, you may not even
00:21:56
need an employee to be involved in it.
00:21:57
It may be happening like an agent for you that's 70% but
00:22:04
when it does that, it responds with better outcomes and
00:22:09
responses because it knows your company avatar, it knows your
00:22:14
employees, it knows your values, it's trained on your processes,
00:22:17
it knows your loan agreements, whatever that may be.
00:22:19
It's things that is unique to you and then, paired with the
00:22:26
large language model, is what makes it magical.
00:22:28
And so with that platform, we've given you everything that
00:22:33
you need to develop your own success, and we also have a
00:22:36
support team.
00:22:36
We have AI developers on staff.
00:22:40
We have a lot of support to take on really complex projects.
00:22:46
But at the end of the day, what we're talking about here is a
00:22:51
10-minute task going to three minutes and the incremental
00:22:56
value of that over time.
00:23:00
In professional sports.
00:23:01
The difference between some of them makes a million dollars a
00:23:04
year in baseball and 10 million is one hit a week, one base hit,
00:23:09
one bunt, one extra sprint to the beat out the ground ball.
00:23:16
It's the small things.
00:23:20
Everybody's trying to hit these home runs in AI, trying to do
00:23:24
big things in AI.
00:23:25
I'm here to help you tackle the things that are going to move
00:23:30
the needle financially, that are going to allow you to do it in
00:23:36
a way that the employees don't feel like there's an overwhelm,
00:23:40
do it in a way that doesn't put anything at risk to liabilities,
00:23:43
and do it in a way where you have fractional support.
00:23:47
You have sort of an outsourced innovation arm to help guide you
00:23:52
.
00:23:52
Hopefully this podcast will bring information, insights.
00:23:54
But people to get it done for less than hiring like your
00:23:59
average employee.
00:24:00
Exciting times in multifamily.
00:24:03
I wanted to take you through our applied AI in the multifamily
00:24:06
business.
00:24:06
It's our framework People beginning in the process.
00:24:09
The goals automate about 70% of the work.
00:24:11
I know we can do 90, 100 in many cases, but goodness, 70%.
00:24:17
Making assumptions about what it takes to get the job done,
00:24:22
having better clarity around the process, being able to bring AI
00:24:26
in your business.
00:24:27
See it happen for yourself.
00:24:28
Then you unlock what's next Not a webinar.
00:24:31
You unlock ideas once you see it working and then you automate
00:24:37
it and you're enjoying your work and you're redefining what
00:24:40
happens in an employee experience.
00:24:41
You're bringing that data all into one place.
00:24:45
You have a place to see and you have perspectives on the
00:24:48
customer and your employees.
00:24:49
You're making better decisions because you have that data.
00:24:52
You can honestly say you're creating an applied AI in a
00:24:58
multifamily business strategy that starts and ends with people
00:25:02
.
00:25:02
It dismisses that whole idea that we're going to reinvise all
00:25:09
that stuff.
00:25:09
This is a great place to start.
00:25:11
I hope this was helpful.
00:25:12
If you found it helpful, please give us a like, a review,
00:25:15
subscribe rate, whatever that means to you.
00:25:17
I would love some feedback.
00:25:19
You have ways to reach out to me.
00:25:20
Multifamilyaipodcastcom is a great way to get access to us
00:25:25
and learn about what you may need.
00:25:27
If you have episode ideas, send us an email, send us a message
00:25:31
right on the website.
00:25:32
You can even do video.
00:25:33
I think you can do audio right on the website.
00:25:36
You can tell us.
00:25:36
Maybe we'll introduce, take questions and answer those
00:25:38
questions through this process.
00:25:40
Plus, we're going to be seeking out some really interesting
00:25:42
guests, really interesting experiences to help you move
00:25:46
through this.
00:25:46
Get those capabilities up, because the opportunities are
00:25:50
there.
00:25:50
We'll see you guys in the next episode.
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