October 3, 2024 • 29 mins
Welcome to Camp Content! In this episode, Kyle Murphy, a digital transformation and AI expert discusses government communication, AI's business impact, and an AI maturity assessment tool. Kyle shares insights, favorite reads, and tech tools like ChatGPT and Claude. The episode covers AI in CPA firms, automation, anomaly detection, and stresses human oversight in AI.
Tune in for valuable insights on AI efficiency. Subscribe, rate, and review us on Spotify, iTunes, and YouTube. Let's dive in!
Connect with Kyle: https://www.linkedin.com/in/kyle-murphy-ccxp/
Website: https://alphaadvisors.com
Episode Timestamps:
00:00 - Intro
02:09 - AI Development Progress: Companies' Adaptation
04:42 - Prioritize AI Training to Address User Concerns0
7:46 - Task Automation and Financial Analysis
10:52 - Importance of Human Review in Process Design
17:00 - Crafting AI for Back Office Functions
19:33 - AI Maturity Assessment via Quick Survey
24:29 - Tools: Power Automate, Python, Claude, Chat GPT
27:13 - Exploring AI for Task Automation
27:55 - Outro
Quote of the Episode: "Feedback is helpful, guiding attention and adding value without costs, leading to a premium service as they sought solutions."
For more insights and to book a call with Molly Ruland, visit Molly’s Calendly.
Host: Molly Ruland, CEO & Founder
Operations Manager: Matt Billman
Powered by: Heartcast Media,http://www.heartcastmedia.com
Tune in for valuable insights on AI efficiency. Subscribe, rate, and review us on Spotify, iTunes, and YouTube. Let's dive in!
Connect with Kyle: https://www.linkedin.com/in/kyle-murphy-ccxp/
Website: https://alphaadvisors.com
Episode Timestamps:
00:00 - Intro
02:09 - AI Development Progress: Companies' Adaptation
04:42 - Prioritize AI Training to Address User Concerns0
7:46 - Task Automation and Financial Analysis
10:52 - Importance of Human Review in Process Design
17:00 - Crafting AI for Back Office Functions
19:33 - AI Maturity Assessment via Quick Survey
24:29 - Tools: Power Automate, Python, Claude, Chat GPT
27:13 - Exploring AI for Task Automation
27:55 - Outro
Quote of the Episode: "Feedback is helpful, guiding attention and adding value without costs, leading to a premium service as they sought solutions."
For more insights and to book a call with Molly Ruland, visit Molly’s Calendly.
Host: Molly Ruland, CEO & Founder
Operations Manager: Matt Billman
Powered by: Heartcast Media,http://www.heartcastmedia.com
Mark as Played
Transcript
Episode Transcript
Available transcripts are automatically generated. Complete accuracy is not guaranteed.
Speaker 1 (00:17):
Ladies and gentlemen, Welcome back to Camp Content, where we
dive into the nexus of content marketing and the revenue
stream shaping twenty and twenty four. Today we're joined by
a leader and innovator in digital transformation, Kyle Murphy. Kyle
spent over fifteen years guiding organizations like Grant Thornton, the USPTO,
(00:38):
and Newmark Group. There's significant technological shifts. He's particularly focused
on the applications of artificial intelligence, Web three and data analytics.
Kyle's the founder of Alpha Advisor, a consultancy culture that's
a hard word, a consultancy that distinctively combines data and
emerging tech expertise to serve small and medium sized businesses,
(01:01):
including sectors like finance and healthcare. They are pioneers and
employing AI to drive business growth and improvement. So today
we're going to explore topics such as integrating AI into
your business, utilizing tools like chat, GPT, and understanding the
pivotal role of data and AI. So without further ado,
we're going to get right into it. And so thanks
for coming on the show today, Kyle.
Speaker 2 (01:23):
Thanks for having me. Molly really excited to be here today.
Speaker 3 (01:26):
Yeah, man, I am too.
Speaker 2 (01:28):
Thank you awesome, thanks for the very warm intro and
looking forward to the conversation.
Speaker 1 (01:34):
Yeah man, well yeah, well the audience doesn't know this,
but we have known each other for a couple of
years now, I guess if you.
Speaker 3 (01:41):
Can believe that.
Speaker 1 (01:42):
So, so it's always nice to see you back and
to get to spend some time with you.
Speaker 2 (01:46):
So very excited.
Speaker 3 (01:49):
Right on, So everybody's talking a lot about AI.
Speaker 1 (01:52):
So we're gonna we're gonna get into like a little
bit more niche in how you're serving some of your clients.
Speaker 3 (01:57):
But before we get into.
Speaker 1 (01:58):
All of that, let's do like a shark tank style
snapshot of your business. Can you tell me like how
many employees, how many clients? Where you located? That kind
of thing?
Speaker 2 (02:08):
Yep, So alphab Visors I'm based out of Washington, d C.
But we have partners in Atlanta and West Palm Beach, Florida.
We're about six people right now, but have a network
of about twelve that we use across our projects. Our clients,
as we mentioned, small to medium sized businesses with a
(02:32):
few larger clients. We have about eight to ten clients
at the moment that we're serving across all different aspects
about of AI, like you're talking about, So we are
fully remote and we'll travel to where those clients are,
so we're kind of spread out. But it's been a fastic,
fantastic journey and growing the company over the last two
(02:55):
almost two years.
Speaker 3 (02:56):
Now, yeah, it's a pretty new company.
Speaker 1 (03:00):
But you know, you're coming with fifteen years of experience
in digital transformation. So how are you seeing kind of
the similarities and the work that you were doing ten
years ago to the work now?
Speaker 3 (03:10):
Is it moving faster?
Speaker 2 (03:11):
You know?
Speaker 3 (03:12):
To me? I would imagine so.
Speaker 2 (03:13):
But so you know, when I started my career, you know,
everything was around you know, cloud transformation. Then we got
into intelligent automation right and ran huge groups and deployed
automation bots and all those fun stuff and building products.
And now with the emergence of AI or generative AI specifically,
(03:36):
everyone is talking asking about it and see where they
need to be to stay competitive in the environment. So
I'd say things are moving quickly in the sense that
AI or generative AI is developing comically fast. However, a
lot of companies are still trying to understand how to
(03:57):
leverage it, how to use it, and how to do it. See,
so while the technology is rapidly advancing, companies are still
trying to figure out like what makes the most sense
for them on the back half of knowing that we
need to use it in some way, shape or form.
So where intelligent automation kind of took away those jobs
(04:20):
that were monotonous and repetitive and standardized, right jen AI
is a much different animal in that it's writing things,
it's predicting these things, it's it's pseudo making conclusions for people.
So companies are not only wanting to adopt it, but
they're also very wary of it at the same exact time.
Speaker 1 (04:42):
I mean rightfully, So, I mean AI has definitely sent
me down.
Speaker 3 (04:45):
Like right off of some clips.
Speaker 1 (04:47):
It's like Apple Maps, you know what I mean, It's like,
what what just happened?
Speaker 3 (04:51):
Where am I?
Speaker 2 (04:51):
You know?
Speaker 1 (04:53):
So I can I you know, it's it needs so
much quality control and you really have to train it right.
And I have very limited experience with AI, but the
more pedestrian platforms, if you will, are even harder to manipulate.
You know, I couldn't help it laugh at myself, but
I was getting legitimately irritated at my AI tool because
it kept putting emojis and I'm like, in all caps
(05:16):
but no emojis, And I said, oh, it's like when
I'm getting mad at my roomba, you know what I mean,
I'm like, who, it's the real idiot here?
Speaker 3 (05:21):
You know it's me.
Speaker 1 (05:22):
But but it can be really frustrating, and so it
would be hard to just assume that your team is
going to be able to use it the right way
if they're not also constantly maintaining it. So is that
is that something that you're doing to help keeping abstracted?
Speaker 2 (05:37):
Absolutely? So one of the big things we found is
is there's a big opportunity for training as you move forward,
right how to use you know, one company we're working
with wanted to use enterprise chat GBT for example, So
with that that keeps your data protected, you get your
own instants, all that good stuff. So they felt comfortable
doing that in a in a certain way. However, for
(06:02):
folks out there, never put like your social Security number
or addresses and like stuff in there, just like don't
do it, Like come on, but I digress. So teaching
them prompt engineering, right, what are the actual capabilities of it? Right?
Can I put a massive spreadsheet in there, and it
gives me charts and graphs, how to identify if it's hallucinating,
(06:26):
how to make sure they're asking for sources in references
when they get a response, because a lot of times
Chat Gibt, all it wants to do is answer you.
It's predicting the next word that's coming up. And so
we asked it for quotes about AI just as a test,
and it gave us references to websites it pulled it from.
(06:46):
Out of the five quotes it gave us, two of
the websites didn't exist, just made it up. Yeah, right,
So adding custom instructions, like to your point, Molly, if
like you don't want emojis in the back end, you
can give it instructions to never use emojis. Give it writing.
I gave it writing samples that I like that were
(07:08):
in my tone of voice, so it then can write
in my tone of voice. So training and putting those
guardrails around it is a big part of what we're
doing and working with companies on how to strategize the
best way to do that.
Speaker 1 (07:24):
So out of the companies that you're working with, what
is your like sweet spot? I know we were just
talking about CPAs, like, how how would a CPA benefit
from from these types of models. I would imagine there's
a lot of repetitive tasks and redundancy, you know, all
of that.
Speaker 3 (07:42):
So how how would you what would you build for
a CPA.
Speaker 2 (07:46):
Exactly, So two parts to it, right, there's a lot
of things that AI is good at, but there's a
lot of software and things out there that exist today
that is better than AI current. So for CPA firms
when we talk to them, you know, month end clothes
using automation, like the power Automate suite where we automate
(08:08):
those repetitive tasks. Right, that's one side of it. Then
on the other side, for a CPA firm, for example,
we built an AI tool that could analyze all their
QuickBooks data and find anomalies that get highlighted to you know,
either the team lead or someone that is looking at
(08:30):
the financials of a company. Meaning let's say this month,
like on average over the last two years, this line
item was always within this range. This month, for some reason,
it's higher. Here's a you know, we market read and
then you can ask the AI tool questions, well, are
(08:51):
there assumptions or something in the underlying data that turned
it read well, this person was late on payments or
they overdrafted account. So you can start interacting with that
data and asking it questions in that closed loop that's very, very.
Speaker 3 (09:07):
Focused, fascinating.
Speaker 1 (09:11):
So I would imagine the better the CPA and the
more organized they are, and the more experience they are
so they know what to look for, the more effective
these tools will be. And then I would imagine you're
probably building up quite the arsenal of knowing some of
those things that maybe the CPAs don't even realize that
they could at automating.
Speaker 2 (09:30):
Yeah, so we have you know, accelerators specifically towards them, right,
we can ingest thousands of documents and hours and understand
their tone of voice. Let's say they do a month
in summary report for their clients, train the AI on
here's the salient points for this type of business and
(09:50):
this site of it, so they can get much faster
to that first draft or that first output to allow
them to move into thinking mode instead of starting from
a blank screen or doing some of the monotonous stuff
which then eats up their time and they can't be
doing the value added activities.
Speaker 1 (10:11):
Yeah, because I would imagine there's so much redundancy in
CBA businesses. I mean just the bookkeeping and yeah, just
a lot of repetitive tasks.
Speaker 3 (10:21):
Pretty interesting.
Speaker 1 (10:22):
So you know, you know, I've been working on this
project that like involves a lot of AI, but it
also has like a human component to it. How do
you think these things are going to merge? You know,
you know, where's the line between going too far into
the AI world and making sure that quality control is there?
Speaker 3 (10:40):
Like, how do you build that?
Speaker 1 (10:41):
Because I would imagine, right, because sometimes you know, it's
like the self driving Tesla cars, right, Like a lot
of people would probably be hesitant to take their hands
off the wheel. So how do you build in fail
safes for those kinds of things?
Speaker 2 (10:52):
So we design everything with humans in the loop, meaning
each stage of a process or step, right, a human
being still needs to review, understand, and bring their years
of expertise to whatever that output is. Right. Another company
we're working with, we're designing a tool to respond to
(11:16):
RFPs right, and that takes a lot of thought, a
lot of knowledge based from historical things what your service
offerings are. So we're building a tool that actually walks
them through the process, can take their entire data set
and makes suggestions for the first draft with different options,
(11:37):
different pieces. So then you get to understand, Okay, this
one makes sense. It thinks this one doesn't make sense,
or it thinks this one makes sense, but I know
that's not correct because I actually know the client. Then
you get to eliminate it from the basis of writing
that proposal. So everything has that human check the loop,
(12:01):
and then that allows you to accelerate everything that you're doing.
So we're not a proponent of set it and forget
it like AI, like run this, here's my answer, paste
it and off right, like the guy that got in
trouble the lawyer in New York's the classic example who
cited a legal case that didn't exist because he just
(12:22):
used chet GPT to say, give me some legal briefs
or whatever. I'm not a lawyer, I don't you know.
I'm not. But he just made something up using AI
and then lost the case or got disbarred.
Speaker 3 (12:35):
I don't know what happened to him, but hopefully both.
Speaker 2 (12:38):
Yeah, but you don't want to do that. So human
in the loop right now is really really important. Maybe
we'll get there in the future, right, which would be great,
but today that's that's just not not it.
Speaker 1 (12:51):
What do you think the biggest hurdle is in people
wanting to create something like this? Is it a lack
of knowledge? Is it lack of funding? Like where do
you think? Where do you think the hesitancy or the
you know, I'm not hesitancy? A should say, but like,
you know, why are more people doing this?
Speaker 2 (13:09):
I guess so? So what I've heard and seen from clients.
The most important thing to understand is why you want
to do it right. There needs to be a business
case and an understanding, and it needs to solve a problem,
just like any tool that's come across the market in forever.
Right it's the shiny key factor. Right now, AI is
(13:32):
the shiny keys which it's it's better and can do
a lot of things. But if you don't understand the
problem it's trying to solve, you're going to waste a
bunch of time and money. So right now, there's a
big study on it. Ninety percent of AI proof of
concepts aren't making it to production ninety percent because they're
(13:55):
not thinking about the why and the strategy and what
problem it's trying to solve. And when you really dig
into that problem a lot of times. It may not
be the best use case for AI right now, but
you have to identify what that is. And then the
long term costs are getting cheaper by the day, but
it's not cheap frankly, to build a custom product. It's
(14:19):
cheaper to use something off the shelf.
Speaker 3 (14:24):
Makes sense.
Speaker 1 (14:25):
I mean, I feel like there's a big knowledge gap too, right,
Like people of a certain generation are going to know
less about these kind of tools and availability of them.
Can you give me, like a case study of a
client that you've worked with and you created something for them.
Speaker 2 (14:42):
Yes, So the RFP tool, for example, we're working on.
We've built what we call an AI accounting assistant. So
what the tool does for a you know, three hundred
person CPA firm is every month they do let's say
outsourced accounting, which is fairly simplistic. They do this, this
(15:05):
and this, but they wanted to be able to send
them summaries and value added things and things we notice.
But they don't have time to write three hundred things
from scratch, right and at the associate level, senior associate level,
they don't have let's say, the experience to write some
of those things. So what the tool can do is
(15:29):
it absorbs all the historical information from this company ABC
when we built this model, that one is completely secure,
the data is not going anywhere doing any of that stuff,
and then examples from their CFO of how some of
these things need to be written, what are the important
(15:49):
data points, maybe this expense is trending the wrong way,
all of that stuff. So as they finish their monthly
outsourced accounting, it can actually make that first draft of
a tube pager to the client, which they've gotten feedback.
Has been really really helpful because then they can read
that know what I need to go look at and
(16:12):
it became a value added activity that didn't create much overhead,
but then turned into a more expensive subscription model for
them because they're like, hey, help me fix this.
Speaker 3 (16:24):
Right, that's amazing, that's amazing. All right.
Speaker 1 (16:28):
I have a a wild card question for you.
Speaker 3 (16:31):
If you had on i know, get hang on to
your hat.
Speaker 1 (16:33):
If you had unlimited resources and technological capabilities at your disposal,
what dream project would you initiate to revolution revolution, revolutionalize.
Why can't I say this small and medium sized businesses
that's actually born? What would you create to make the
world a better place with emerging technology.
Speaker 3 (16:54):
That's a better.
Speaker 2 (16:55):
Question, man, That's a loaded question, Huh.
Speaker 3 (16:57):
I know, I know.
Speaker 2 (17:00):
What would I do? So from my I guess it
draws a lot of my background in things that I've done,
So I think I would create the ultimate back office
AI persona right, and my experience from an entrepreneur, like
(17:22):
dealing with ADMIN accounting all like I wear like I
spin my like I'll spin my chair around, and now
I have to deal with setting up a new tax
id in Montana and like all those wild things like
I think I would create like the ultimate AI thing
that would have that knowledge base where I could say, hey,
(17:45):
I'm getting a new employee in New York and I
don't have a tax id, Like what do I do?
And it tells me what to do? Hey, can you
run my accounting this year? Make the fund transfers and
all of that where I could have like this awesome
I'm like, you know, call her, you know Steve or
WAI where I go, hey, Debbie, here's what we need
(18:06):
to accomplish today, and they they just do it. It
would save me and I'm sure so many people in
small medium so that so many hours of monotonous things
that we hate.
Speaker 1 (18:18):
Doing well, and like, you know, all these things that
you're supposed to pay and do that you don't know about.
And then states and different governments aren't the best at
telling you when they're due.
Speaker 3 (18:29):
And then you're like, wait, what was late? What clean hands?
Speaker 1 (18:32):
What?
Speaker 3 (18:33):
Like who?
Speaker 1 (18:34):
And they're like, well, we told you that on the
website on this tab that you never even read, and
so things like that notifying it hey it's time fire
taxes or sign file an extension or like you know
that's obvious.
Speaker 2 (18:46):
But yeah, like I live in d C. But I'm
not an employee of the company right because I'm the owner.
But DC every quoter sends me a letter saying I
didn't file my you know, employment, employment taxes or whatever.
The weird thing is I go and then every quarter
I call them and say I'm not an employee. They're like,
(19:07):
oh okay, and then they wave it and it's happened
for eighteen months, which is how many quarters like. Having
someone to know to do that or could file something
so they just stop would be like an amazing thing
for me to help run my business that takes care
of the noise. I think would be the most ultimate thing.
Speaker 1 (19:28):
For me, man, you should build that like little bit
by bit and then put it together later, because I
think we.
Speaker 2 (19:34):
Eat our own dog food. Like, we just rolled out
this cool our first campaign around AI Maturity Assessment, right,
So it's this cool thing that you can click on.
It's in my LinkedIn bio, but it's like fifteen questions
and it, you know, asks you you know, where do
you think you are with AI? Blah blah, and you
just click really fast. But we used a combination of
(19:57):
tools and AI, so AI we trained to write the
responses to the survey based on where the rankings are,
our knowledge of where other companies are in the industry,
and you get it writes this really cool summary of Hey,
here's kind of you know, are you an introductory level
to AI. Here's some suggestions of how to move forward
(20:21):
things like that. So so we leverage it wherever we can.
Speaker 3 (20:25):
I love it. That's great.
Speaker 1 (20:28):
Yeah, Well, we'll make sure that we have all your
links and stuff. You're at the bottom of this show,
so people can check out that assessment tool and everything else.
Speaker 3 (20:37):
We'll make sure to include that.
Speaker 2 (20:38):
Yeah, very cool.
Speaker 1 (20:40):
All right, So now we're moving on to our realer
fake segment of the show.
Speaker 2 (20:43):
All right, let's do it.
Speaker 3 (20:44):
Get ready realer fake. We even have a little cool graphic.
Speaker 1 (20:49):
All right, so I'm gonna list off some podcast names
and you're gonna tell me if you think they are
real or fake.
Speaker 2 (20:55):
All right, all right, we'll google it, google it or anything.
Speaker 1 (20:58):
No, No, you have no time to google it. This
is This is a speed round. Yeah. You gotta keep
your hands in the air at all times so I
know you're not Google.
Speaker 3 (21:05):
All right. The first one smart passive income.
Speaker 2 (21:11):
God. With all the stuff that's sucked on my Instagram feed,
that's gotta be real.
Speaker 3 (21:16):
It is.
Speaker 1 (21:17):
It doesn't sound very fake either. I should have picked
a better one. AI Horizon The Future of Tech.
Speaker 2 (21:26):
That could be any of fifty podcasts.
Speaker 3 (21:30):
There's probably one hundred of them.
Speaker 2 (21:32):
There's one hundred of them. I'm gonna say real.
Speaker 3 (21:34):
It's fake. Shockingly enough. Okay, hurry slowly.
Speaker 2 (21:44):
I don't want to keep saying real. But that definitely
sounds like a very podcasting name. But I'm gonna go
fake it's real.
Speaker 1 (21:54):
Yes, I love it when I I love it when
I win this game. Because the last couple of guests
got everyone right, and I was like, man, I think
I need to anty up a little bit, okay, and
then I have a couple more questions for you.
Speaker 3 (22:06):
Number one, what's the most influential book that you've.
Speaker 1 (22:08):
Read in your life that impacted like your business career
or your ethos as a leader, or whatever had the
most impact.
Speaker 2 (22:15):
I'm gonna cop out. I'm gonna say two because they're
two different things. One Atomic Habits Good one and Leaders
Eat Last by Simon sinek Uh.
Speaker 3 (22:26):
You know, I can't stand that guy. I try to.
Speaker 1 (22:28):
I try to listen to the the Why one, and
I couldn't listen to his voice.
Speaker 3 (22:35):
I wanted to run out of the room. But I'll
give it a shot.
Speaker 2 (22:38):
Start with why is unbelievable. I love that one. And
an old one that I always loved was The ten
Minute Uh the ten minute Monkey the Manager. Oh, okay,
that one's fantastic about how you as a leader. Your
employees have a monkey on their back, have a problem,
(23:01):
and if you agree to help them, the monkey moves
to your back, right because they feel like they no
longer have the responsibility. So it's how to deal with
that as a leader. Yeah, it's like seventy pages and
it's old, but it's awesome.
Speaker 1 (23:16):
You know. I read the one Page Marketing Plan by
Alan Dibb like once a year and it's like and
also a very old book, but and it's short, but
it's like every time I listen to it, I'm.
Speaker 3 (23:27):
Like, yeah, I'm glad I did that. It's like some
things are tried and true.
Speaker 1 (23:31):
You know.
Speaker 2 (23:32):
It's so good. And I unfortunately used the monkey analogy
with my wife one day and that did not work.
I lost what Yeah, I tried and I didn't do
it very well, and yeah I lost all my husband
points for that.
Speaker 1 (23:51):
Yeah, you're like, she's like, I'm a monkey now, Yeah, esus,
that's hilarious. And then last question is what is your
favorite like tech in your tech stack?
Speaker 3 (24:01):
What's your favorite?
Speaker 1 (24:02):
Oh?
Speaker 2 (24:02):
I use chat GPT every day all the time.
Speaker 1 (24:06):
Really, so you don't, you know, you're not using like
Bard or whatever the other like options are.
Speaker 3 (24:11):
You're you're a GPT dude.
Speaker 2 (24:13):
I'm a GPT guy. I will use Claude if I need. Like.
The writing styles are wildly different, so okay, so GPT
I use a lot for very business centric writing or
if I'm programming something power Automate or Python or something,
(24:36):
it can help me in some ways with code to me,
in my opinion, a lot a lot more efficiently, like here,
you know, I suggest setting this up this way versus
this way. You know, I'm starting to build an app
just for fun because I wanted to build something, and
it like knows the Swift programming language, which I forgot
(24:59):
eight years ago when I build my Laft app. So
I like it for that. But Claud can be very
more conversational and sounds a little more human. So if
you're writing a LinkedIn post, I'll go to Claud. If
I'm doing presentations or very formal readouts or using code,
(25:20):
I use chat GPT.
Speaker 3 (25:22):
That's really helpful. I haven't checked out Claude.
Speaker 1 (25:24):
I use team GPT because I can share it with
my team and then we can.
Speaker 3 (25:27):
Have reads and stuff.
Speaker 2 (25:28):
That's what we have.
Speaker 1 (25:29):
Yeah, and I find that to be pretty helpful, and
then I can go back and build upon it and stuff.
Although it still puts emojis in everything I do, which
I'm like.
Speaker 2 (25:37):
I'll tell you go into the in the options, I
forget where it is under your profile. There's something called
custom instructions. Oh yeah, and so really put if you
don't want emojis. Put it in there, and it will
never use emojis again.
Speaker 1 (25:53):
Thank god, because I was getting so irritated last week
and I was like half irritated at chat GBT and
like half irritated at myself for being irritated at a because.
Speaker 2 (26:02):
Yeah, you know, and you can tell now if someone
uses chat GVT to write something because they love the
the boat the highlighted word colon and then two sentences
and it just does that over and over again. So
I put all like, don't do that.
Speaker 1 (26:19):
Yeah, there's a bunch of things I repeat all the time.
Speaker 3 (26:22):
So I thank you for that tip.
Speaker 1 (26:23):
I'm going to go in there and adjust that because
then I won't have to get mad at my computer anymore.
But exactly, well, listen, I'm excited to keep chatting with
you about some stuff to do some stuff with hardcast
media because I see a real opportunity there. And thank
you for coming on the show. And before we go,
where can people find you? We're gonna have all your
links and stuff, but where can people find you if
(26:43):
they want to get connected?
Speaker 2 (26:45):
Yeah, find me on LinkedIn, email me, you know, mainly LinkedIn.
I'm on there all the time. We have Kaitlin helps me.
We have social media. I'm not a social media guy,
but we have Twitter, all those fun things. But yeah,
reach out on LinkedIn, emails, just Kyle at Alphadvisors dot com.
(27:08):
Any questions, just want to learn more about AI, please
reach out.
Speaker 1 (27:13):
Awesome, that's fantastic, So thank you all for tuning in today.
I think you know high level takeaways is if you're
a CPO, CPO, CPA, I was like, that doesn't sound right,
or you're in the healthcare business, or you have a
business where you are finding yourself doing a lot of
redundant tasks and even thinking to yourself, I bet you
(27:35):
there's a way to AI, to get AI.
Speaker 3 (27:37):
To do this.
Speaker 1 (27:38):
Sounds like you need to call Kyle, get on that call,
take one of those assessment tools, see where you're at,
see what he can create for you. Because whatever you've
imagined up, he could actually do it and do it
ten times better. So I think it's always good to
arm yourself with the knowledge on how to move forward
with your business. And what Kyle is doing is one
hundred percent the future of business as we know it,
(28:01):
and so I think it's good to get on board
sooner than later, especially over the summertime you got some time,
get ready for the fall and come out swinging. So
on that note, thank you for tuning in to Camp Content. Kyle,
thanks for coming on the show, and until next time,
be excellent to each other. Thanks everybody, thank you, all right,
(28:26):
all right, thank you so much for tuning in to
another episode of camp Content. This is Molly and this
is Matt and we are heartcas Media aka camp Content,
and we appreciate all of your support. If you found
this content valuable, please comment on social media LinkedIn wherever
you find us and we will make sure to comment back.
Speaker 2 (28:43):
And be sure to go on and subscribe and like
on your favorite platform Spotify, iTunes, YouTube, you name it,
and leave us that subscription, leave us that good review.
Speaker 3 (28:52):
Well, love you forever.
Speaker 1 (28:53):
So until next time, be excellent to each other and
we'll see you next week.
Speaker 2 (28:58):
Produced by heartcast Media.
Speaker 1 (29:03):
Thank you for tuning into camp Content hosted by Hardcast Media.
We are a digital content agency focused on content marketing
for businesses and brands. If you're looking to save time
and be more consistent with your marketing and need a
little guidance on what to say and how to say
it and where to say it. We got your back
book a discovery call today and let's talk
Ladies and gentlemen, Welcome back to Camp Content, where we
dive into the nexus of content marketing and the revenue
stream shaping twenty and twenty four. Today we're joined by
a leader and innovator in digital transformation, Kyle Murphy. Kyle
spent over fifteen years guiding organizations like Grant Thornton, the USPTO,
(00:38):
and Newmark Group. There's significant technological shifts. He's particularly focused
on the applications of artificial intelligence, Web three and data analytics.
Kyle's the founder of Alpha Advisor, a consultancy culture that's
a hard word, a consultancy that distinctively combines data and
emerging tech expertise to serve small and medium sized businesses,
(01:01):
including sectors like finance and healthcare. They are pioneers and
employing AI to drive business growth and improvement. So today
we're going to explore topics such as integrating AI into
your business, utilizing tools like chat, GPT, and understanding the
pivotal role of data and AI. So without further ado,
we're going to get right into it. And so thanks
for coming on the show today, Kyle.
Speaker 2 (01:23):
Thanks for having me. Molly really excited to be here today.
Speaker 3 (01:26):
Yeah, man, I am too.
Speaker 2 (01:28):
Thank you awesome, thanks for the very warm intro and
looking forward to the conversation.
Speaker 1 (01:34):
Yeah man, well yeah, well the audience doesn't know this,
but we have known each other for a couple of
years now, I guess if you.
Speaker 3 (01:41):
Can believe that.
Speaker 1 (01:42):
So, so it's always nice to see you back and
to get to spend some time with you.
Speaker 2 (01:46):
So very excited.
Speaker 3 (01:49):
Right on, So everybody's talking a lot about AI.
Speaker 1 (01:52):
So we're gonna we're gonna get into like a little
bit more niche in how you're serving some of your clients.
Speaker 3 (01:57):
But before we get into.
Speaker 1 (01:58):
All of that, let's do like a shark tank style
snapshot of your business. Can you tell me like how
many employees, how many clients? Where you located? That kind
of thing?
Speaker 2 (02:08):
Yep, So alphab Visors I'm based out of Washington, d C.
But we have partners in Atlanta and West Palm Beach, Florida.
We're about six people right now, but have a network
of about twelve that we use across our projects. Our clients,
as we mentioned, small to medium sized businesses with a
(02:32):
few larger clients. We have about eight to ten clients
at the moment that we're serving across all different aspects
about of AI, like you're talking about, So we are
fully remote and we'll travel to where those clients are,
so we're kind of spread out. But it's been a fastic,
fantastic journey and growing the company over the last two
(02:55):
almost two years.
Speaker 3 (02:56):
Now, yeah, it's a pretty new company.
Speaker 1 (03:00):
But you know, you're coming with fifteen years of experience
in digital transformation. So how are you seeing kind of
the similarities and the work that you were doing ten
years ago to the work now?
Speaker 3 (03:10):
Is it moving faster?
Speaker 2 (03:11):
You know?
Speaker 3 (03:12):
To me? I would imagine so.
Speaker 2 (03:13):
But so you know, when I started my career, you know,
everything was around you know, cloud transformation. Then we got
into intelligent automation right and ran huge groups and deployed
automation bots and all those fun stuff and building products.
And now with the emergence of AI or generative AI specifically,
(03:36):
everyone is talking asking about it and see where they
need to be to stay competitive in the environment. So
I'd say things are moving quickly in the sense that
AI or generative AI is developing comically fast. However, a
lot of companies are still trying to understand how to
(03:57):
leverage it, how to use it, and how to do it. See,
so while the technology is rapidly advancing, companies are still
trying to figure out like what makes the most sense
for them on the back half of knowing that we
need to use it in some way, shape or form.
So where intelligent automation kind of took away those jobs
(04:20):
that were monotonous and repetitive and standardized, right jen AI
is a much different animal in that it's writing things,
it's predicting these things, it's it's pseudo making conclusions for people.
So companies are not only wanting to adopt it, but
they're also very wary of it at the same exact time.
Speaker 1 (04:42):
I mean rightfully, So, I mean AI has definitely sent
me down.
Speaker 3 (04:45):
Like right off of some clips.
Speaker 1 (04:47):
It's like Apple Maps, you know what I mean, It's like,
what what just happened?
Speaker 3 (04:51):
Where am I?
Speaker 2 (04:51):
You know?
Speaker 1 (04:53):
So I can I you know, it's it needs so
much quality control and you really have to train it right.
And I have very limited experience with AI, but the
more pedestrian platforms, if you will, are even harder to manipulate.
You know, I couldn't help it laugh at myself, but
I was getting legitimately irritated at my AI tool because
it kept putting emojis and I'm like, in all caps
(05:16):
but no emojis, And I said, oh, it's like when
I'm getting mad at my roomba, you know what I mean,
I'm like, who, it's the real idiot here?
Speaker 3 (05:21):
You know it's me.
Speaker 1 (05:22):
But but it can be really frustrating, and so it
would be hard to just assume that your team is
going to be able to use it the right way
if they're not also constantly maintaining it. So is that
is that something that you're doing to help keeping abstracted?
Speaker 2 (05:37):
Absolutely? So one of the big things we found is
is there's a big opportunity for training as you move forward,
right how to use you know, one company we're working
with wanted to use enterprise chat GBT for example, So
with that that keeps your data protected, you get your
own instants, all that good stuff. So they felt comfortable
doing that in a in a certain way. However, for
(06:02):
folks out there, never put like your social Security number
or addresses and like stuff in there, just like don't
do it, Like come on, but I digress. So teaching
them prompt engineering, right, what are the actual capabilities of it? Right?
Can I put a massive spreadsheet in there, and it
gives me charts and graphs, how to identify if it's hallucinating,
(06:26):
how to make sure they're asking for sources in references
when they get a response, because a lot of times
Chat Gibt, all it wants to do is answer you.
It's predicting the next word that's coming up. And so
we asked it for quotes about AI just as a test,
and it gave us references to websites it pulled it from.
(06:46):
Out of the five quotes it gave us, two of
the websites didn't exist, just made it up. Yeah, right,
So adding custom instructions, like to your point, Molly, if
like you don't want emojis in the back end, you
can give it instructions to never use emojis. Give it writing.
I gave it writing samples that I like that were
(07:08):
in my tone of voice, so it then can write
in my tone of voice. So training and putting those
guardrails around it is a big part of what we're
doing and working with companies on how to strategize the
best way to do that.
Speaker 1 (07:24):
So out of the companies that you're working with, what
is your like sweet spot? I know we were just
talking about CPAs, like, how how would a CPA benefit
from from these types of models. I would imagine there's
a lot of repetitive tasks and redundancy, you know, all
of that.
Speaker 3 (07:42):
So how how would you what would you build for
a CPA.
Speaker 2 (07:46):
Exactly, So two parts to it, right, there's a lot
of things that AI is good at, but there's a
lot of software and things out there that exist today
that is better than AI current. So for CPA firms
when we talk to them, you know, month end clothes
using automation, like the power Automate suite where we automate
(08:08):
those repetitive tasks. Right, that's one side of it. Then
on the other side, for a CPA firm, for example,
we built an AI tool that could analyze all their
QuickBooks data and find anomalies that get highlighted to you know,
either the team lead or someone that is looking at
(08:30):
the financials of a company. Meaning let's say this month,
like on average over the last two years, this line
item was always within this range. This month, for some reason,
it's higher. Here's a you know, we market read and
then you can ask the AI tool questions, well, are
(08:51):
there assumptions or something in the underlying data that turned
it read well, this person was late on payments or
they overdrafted account. So you can start interacting with that
data and asking it questions in that closed loop that's very, very.
Speaker 3 (09:07):
Focused, fascinating.
Speaker 1 (09:11):
So I would imagine the better the CPA and the
more organized they are, and the more experience they are
so they know what to look for, the more effective
these tools will be. And then I would imagine you're
probably building up quite the arsenal of knowing some of
those things that maybe the CPAs don't even realize that
they could at automating.
Speaker 2 (09:30):
Yeah, so we have you know, accelerators specifically towards them, right,
we can ingest thousands of documents and hours and understand
their tone of voice. Let's say they do a month
in summary report for their clients, train the AI on
here's the salient points for this type of business and
(09:50):
this site of it, so they can get much faster
to that first draft or that first output to allow
them to move into thinking mode instead of starting from
a blank screen or doing some of the monotonous stuff
which then eats up their time and they can't be
doing the value added activities.
Speaker 1 (10:11):
Yeah, because I would imagine there's so much redundancy in
CBA businesses. I mean just the bookkeeping and yeah, just
a lot of repetitive tasks.
Speaker 3 (10:21):
Pretty interesting.
Speaker 1 (10:22):
So you know, you know, I've been working on this
project that like involves a lot of AI, but it
also has like a human component to it. How do
you think these things are going to merge? You know,
you know, where's the line between going too far into
the AI world and making sure that quality control is there?
Speaker 3 (10:40):
Like, how do you build that?
Speaker 1 (10:41):
Because I would imagine, right, because sometimes you know, it's
like the self driving Tesla cars, right, Like a lot
of people would probably be hesitant to take their hands
off the wheel. So how do you build in fail
safes for those kinds of things?
Speaker 2 (10:52):
So we design everything with humans in the loop, meaning
each stage of a process or step, right, a human
being still needs to review, understand, and bring their years
of expertise to whatever that output is. Right. Another company
we're working with, we're designing a tool to respond to
(11:16):
RFPs right, and that takes a lot of thought, a
lot of knowledge based from historical things what your service
offerings are. So we're building a tool that actually walks
them through the process, can take their entire data set
and makes suggestions for the first draft with different options,
(11:37):
different pieces. So then you get to understand, Okay, this
one makes sense. It thinks this one doesn't make sense,
or it thinks this one makes sense, but I know
that's not correct because I actually know the client. Then
you get to eliminate it from the basis of writing
that proposal. So everything has that human check the loop,
(12:01):
and then that allows you to accelerate everything that you're doing.
So we're not a proponent of set it and forget
it like AI, like run this, here's my answer, paste
it and off right, like the guy that got in
trouble the lawyer in New York's the classic example who
cited a legal case that didn't exist because he just
(12:22):
used chet GPT to say, give me some legal briefs
or whatever. I'm not a lawyer, I don't you know.
I'm not. But he just made something up using AI
and then lost the case or got disbarred.
Speaker 3 (12:35):
I don't know what happened to him, but hopefully both.
Speaker 2 (12:38):
Yeah, but you don't want to do that. So human
in the loop right now is really really important. Maybe
we'll get there in the future, right, which would be great,
but today that's that's just not not it.
Speaker 1 (12:51):
What do you think the biggest hurdle is in people
wanting to create something like this? Is it a lack
of knowledge? Is it lack of funding? Like where do
you think? Where do you think the hesitancy or the
you know, I'm not hesitancy? A should say, but like,
you know, why are more people doing this?
Speaker 2 (13:09):
I guess so? So what I've heard and seen from clients.
The most important thing to understand is why you want
to do it right. There needs to be a business
case and an understanding, and it needs to solve a problem,
just like any tool that's come across the market in forever.
Right it's the shiny key factor. Right now, AI is
(13:32):
the shiny keys which it's it's better and can do
a lot of things. But if you don't understand the
problem it's trying to solve, you're going to waste a
bunch of time and money. So right now, there's a
big study on it. Ninety percent of AI proof of
concepts aren't making it to production ninety percent because they're
(13:55):
not thinking about the why and the strategy and what
problem it's trying to solve. And when you really dig
into that problem a lot of times. It may not
be the best use case for AI right now, but
you have to identify what that is. And then the
long term costs are getting cheaper by the day, but
it's not cheap frankly, to build a custom product. It's
(14:19):
cheaper to use something off the shelf.
Speaker 3 (14:24):
Makes sense.
Speaker 1 (14:25):
I mean, I feel like there's a big knowledge gap too, right,
Like people of a certain generation are going to know
less about these kind of tools and availability of them.
Can you give me, like a case study of a
client that you've worked with and you created something for them.
Speaker 2 (14:42):
Yes, So the RFP tool, for example, we're working on.
We've built what we call an AI accounting assistant. So
what the tool does for a you know, three hundred
person CPA firm is every month they do let's say
outsourced accounting, which is fairly simplistic. They do this, this
(15:05):
and this, but they wanted to be able to send
them summaries and value added things and things we notice.
But they don't have time to write three hundred things
from scratch, right and at the associate level, senior associate level,
they don't have let's say, the experience to write some
of those things. So what the tool can do is
(15:29):
it absorbs all the historical information from this company ABC
when we built this model, that one is completely secure,
the data is not going anywhere doing any of that stuff,
and then examples from their CFO of how some of
these things need to be written, what are the important
(15:49):
data points, maybe this expense is trending the wrong way,
all of that stuff. So as they finish their monthly
outsourced accounting, it can actually make that first draft of
a tube pager to the client, which they've gotten feedback.
Has been really really helpful because then they can read
that know what I need to go look at and
(16:12):
it became a value added activity that didn't create much overhead,
but then turned into a more expensive subscription model for
them because they're like, hey, help me fix this.
Speaker 3 (16:24):
Right, that's amazing, that's amazing. All right.
Speaker 1 (16:28):
I have a a wild card question for you.
Speaker 3 (16:31):
If you had on i know, get hang on to
your hat.
Speaker 1 (16:33):
If you had unlimited resources and technological capabilities at your disposal,
what dream project would you initiate to revolution revolution, revolutionalize.
Why can't I say this small and medium sized businesses
that's actually born? What would you create to make the
world a better place with emerging technology.
Speaker 3 (16:54):
That's a better.
Speaker 2 (16:55):
Question, man, That's a loaded question, Huh.
Speaker 3 (16:57):
I know, I know.
Speaker 2 (17:00):
What would I do? So from my I guess it
draws a lot of my background in things that I've done,
So I think I would create the ultimate back office
AI persona right, and my experience from an entrepreneur, like
(17:22):
dealing with ADMIN accounting all like I wear like I
spin my like I'll spin my chair around, and now
I have to deal with setting up a new tax
id in Montana and like all those wild things like
I think I would create like the ultimate AI thing
that would have that knowledge base where I could say, hey,
(17:45):
I'm getting a new employee in New York and I
don't have a tax id, Like what do I do?
And it tells me what to do? Hey, can you
run my accounting this year? Make the fund transfers and
all of that where I could have like this awesome
I'm like, you know, call her, you know Steve or
WAI where I go, hey, Debbie, here's what we need
(18:06):
to accomplish today, and they they just do it. It
would save me and I'm sure so many people in
small medium so that so many hours of monotonous things
that we hate.
Speaker 1 (18:18):
Doing well, and like, you know, all these things that
you're supposed to pay and do that you don't know about.
And then states and different governments aren't the best at
telling you when they're due.
Speaker 3 (18:29):
And then you're like, wait, what was late? What clean hands?
Speaker 1 (18:32):
What?
Speaker 3 (18:33):
Like who?
Speaker 1 (18:34):
And they're like, well, we told you that on the
website on this tab that you never even read, and
so things like that notifying it hey it's time fire
taxes or sign file an extension or like you know
that's obvious.
Speaker 2 (18:46):
But yeah, like I live in d C. But I'm
not an employee of the company right because I'm the owner.
But DC every quoter sends me a letter saying I
didn't file my you know, employment, employment taxes or whatever.
The weird thing is I go and then every quarter
I call them and say I'm not an employee. They're like,
(19:07):
oh okay, and then they wave it and it's happened
for eighteen months, which is how many quarters like. Having
someone to know to do that or could file something
so they just stop would be like an amazing thing
for me to help run my business that takes care
of the noise. I think would be the most ultimate thing.
Speaker 1 (19:28):
For me, man, you should build that like little bit
by bit and then put it together later, because I
think we.
Speaker 2 (19:34):
Eat our own dog food. Like, we just rolled out
this cool our first campaign around AI Maturity Assessment, right,
So it's this cool thing that you can click on.
It's in my LinkedIn bio, but it's like fifteen questions
and it, you know, asks you you know, where do
you think you are with AI? Blah blah, and you
just click really fast. But we used a combination of
(19:57):
tools and AI, so AI we trained to write the
responses to the survey based on where the rankings are,
our knowledge of where other companies are in the industry,
and you get it writes this really cool summary of Hey,
here's kind of you know, are you an introductory level
to AI. Here's some suggestions of how to move forward
(20:21):
things like that. So so we leverage it wherever we can.
Speaker 3 (20:25):
I love it. That's great.
Speaker 1 (20:28):
Yeah, Well, we'll make sure that we have all your
links and stuff. You're at the bottom of this show,
so people can check out that assessment tool and everything else.
Speaker 3 (20:37):
We'll make sure to include that.
Speaker 2 (20:38):
Yeah, very cool.
Speaker 1 (20:40):
All right, So now we're moving on to our realer
fake segment of the show.
Speaker 2 (20:43):
All right, let's do it.
Speaker 3 (20:44):
Get ready realer fake. We even have a little cool graphic.
Speaker 1 (20:49):
All right, so I'm gonna list off some podcast names
and you're gonna tell me if you think they are
real or fake.
Speaker 2 (20:55):
All right, all right, we'll google it, google it or anything.
Speaker 1 (20:58):
No, No, you have no time to google it. This
is This is a speed round. Yeah. You gotta keep
your hands in the air at all times so I
know you're not Google.
Speaker 3 (21:05):
All right. The first one smart passive income.
Speaker 2 (21:11):
God. With all the stuff that's sucked on my Instagram feed,
that's gotta be real.
Speaker 3 (21:16):
It is.
Speaker 1 (21:17):
It doesn't sound very fake either. I should have picked
a better one. AI Horizon The Future of Tech.
Speaker 2 (21:26):
That could be any of fifty podcasts.
Speaker 3 (21:30):
There's probably one hundred of them.
Speaker 2 (21:32):
There's one hundred of them. I'm gonna say real.
Speaker 3 (21:34):
It's fake. Shockingly enough. Okay, hurry slowly.
Speaker 2 (21:44):
I don't want to keep saying real. But that definitely
sounds like a very podcasting name. But I'm gonna go
fake it's real.
Speaker 1 (21:54):
Yes, I love it when I I love it when
I win this game. Because the last couple of guests
got everyone right, and I was like, man, I think
I need to anty up a little bit, okay, and
then I have a couple more questions for you.
Speaker 3 (22:06):
Number one, what's the most influential book that you've.
Speaker 1 (22:08):
Read in your life that impacted like your business career
or your ethos as a leader, or whatever had the
most impact.
Speaker 2 (22:15):
I'm gonna cop out. I'm gonna say two because they're
two different things. One Atomic Habits Good one and Leaders
Eat Last by Simon sinek Uh.
Speaker 3 (22:26):
You know, I can't stand that guy. I try to.
Speaker 1 (22:28):
I try to listen to the the Why one, and
I couldn't listen to his voice.
Speaker 3 (22:35):
I wanted to run out of the room. But I'll
give it a shot.
Speaker 2 (22:38):
Start with why is unbelievable. I love that one. And
an old one that I always loved was The ten
Minute Uh the ten minute Monkey the Manager. Oh, okay,
that one's fantastic about how you as a leader. Your
employees have a monkey on their back, have a problem,
(23:01):
and if you agree to help them, the monkey moves
to your back, right because they feel like they no
longer have the responsibility. So it's how to deal with
that as a leader. Yeah, it's like seventy pages and
it's old, but it's awesome.
Speaker 1 (23:16):
You know. I read the one Page Marketing Plan by
Alan Dibb like once a year and it's like and
also a very old book, but and it's short, but
it's like every time I listen to it, I'm.
Speaker 3 (23:27):
Like, yeah, I'm glad I did that. It's like some
things are tried and true.
Speaker 1 (23:31):
You know.
Speaker 2 (23:32):
It's so good. And I unfortunately used the monkey analogy
with my wife one day and that did not work.
I lost what Yeah, I tried and I didn't do
it very well, and yeah I lost all my husband
points for that.
Speaker 1 (23:51):
Yeah, you're like, she's like, I'm a monkey now, Yeah, esus,
that's hilarious. And then last question is what is your
favorite like tech in your tech stack?
Speaker 3 (24:01):
What's your favorite?
Speaker 1 (24:02):
Oh?
Speaker 2 (24:02):
I use chat GPT every day all the time.
Speaker 1 (24:06):
Really, so you don't, you know, you're not using like
Bard or whatever the other like options are.
Speaker 3 (24:11):
You're you're a GPT dude.
Speaker 2 (24:13):
I'm a GPT guy. I will use Claude if I need. Like.
The writing styles are wildly different, so okay, so GPT
I use a lot for very business centric writing or
if I'm programming something power Automate or Python or something,
(24:36):
it can help me in some ways with code to me,
in my opinion, a lot a lot more efficiently, like here,
you know, I suggest setting this up this way versus
this way. You know, I'm starting to build an app
just for fun because I wanted to build something, and
it like knows the Swift programming language, which I forgot
(24:59):
eight years ago when I build my Laft app. So
I like it for that. But Claud can be very
more conversational and sounds a little more human. So if
you're writing a LinkedIn post, I'll go to Claud. If
I'm doing presentations or very formal readouts or using code,
(25:20):
I use chat GPT.
Speaker 3 (25:22):
That's really helpful. I haven't checked out Claude.
Speaker 1 (25:24):
I use team GPT because I can share it with
my team and then we can.
Speaker 3 (25:27):
Have reads and stuff.
Speaker 2 (25:28):
That's what we have.
Speaker 1 (25:29):
Yeah, and I find that to be pretty helpful, and
then I can go back and build upon it and stuff.
Although it still puts emojis in everything I do, which
I'm like.
Speaker 2 (25:37):
I'll tell you go into the in the options, I
forget where it is under your profile. There's something called
custom instructions. Oh yeah, and so really put if you
don't want emojis. Put it in there, and it will
never use emojis again.
Speaker 1 (25:53):
Thank god, because I was getting so irritated last week
and I was like half irritated at chat GBT and
like half irritated at myself for being irritated at a because.
Speaker 2 (26:02):
Yeah, you know, and you can tell now if someone
uses chat GVT to write something because they love the
the boat the highlighted word colon and then two sentences
and it just does that over and over again. So
I put all like, don't do that.
Speaker 1 (26:19):
Yeah, there's a bunch of things I repeat all the time.
Speaker 3 (26:22):
So I thank you for that tip.
Speaker 1 (26:23):
I'm going to go in there and adjust that because
then I won't have to get mad at my computer anymore.
But exactly, well, listen, I'm excited to keep chatting with
you about some stuff to do some stuff with hardcast
media because I see a real opportunity there. And thank
you for coming on the show. And before we go,
where can people find you? We're gonna have all your
links and stuff, but where can people find you if
(26:43):
they want to get connected?
Speaker 2 (26:45):
Yeah, find me on LinkedIn, email me, you know, mainly LinkedIn.
I'm on there all the time. We have Kaitlin helps me.
We have social media. I'm not a social media guy,
but we have Twitter, all those fun things. But yeah,
reach out on LinkedIn, emails, just Kyle at Alphadvisors dot com.
(27:08):
Any questions, just want to learn more about AI, please
reach out.
Speaker 1 (27:13):
Awesome, that's fantastic, So thank you all for tuning in today.
I think you know high level takeaways is if you're
a CPO, CPO, CPA, I was like, that doesn't sound right,
or you're in the healthcare business, or you have a
business where you are finding yourself doing a lot of
redundant tasks and even thinking to yourself, I bet you
(27:35):
there's a way to AI, to get AI.
Speaker 3 (27:37):
To do this.
Speaker 1 (27:38):
Sounds like you need to call Kyle, get on that call,
take one of those assessment tools, see where you're at,
see what he can create for you. Because whatever you've
imagined up, he could actually do it and do it
ten times better. So I think it's always good to
arm yourself with the knowledge on how to move forward
with your business. And what Kyle is doing is one
hundred percent the future of business as we know it,
(28:01):
and so I think it's good to get on board
sooner than later, especially over the summertime you got some time,
get ready for the fall and come out swinging. So
on that note, thank you for tuning in to Camp Content. Kyle,
thanks for coming on the show, and until next time,
be excellent to each other. Thanks everybody, thank you, all right,
(28:26):
all right, thank you so much for tuning in to
another episode of camp Content. This is Molly and this
is Matt and we are heartcas Media aka camp Content,
and we appreciate all of your support. If you found
this content valuable, please comment on social media LinkedIn wherever
you find us and we will make sure to comment back.
Speaker 2 (28:43):
And be sure to go on and subscribe and like
on your favorite platform Spotify, iTunes, YouTube, you name it,
and leave us that subscription, leave us that good review.
Speaker 3 (28:52):
Well, love you forever.
Speaker 1 (28:53):
So until next time, be excellent to each other and
we'll see you next week.
Speaker 2 (28:58):
Produced by heartcast Media.
Speaker 1 (29:03):
Thank you for tuning into camp Content hosted by Hardcast Media.
We are a digital content agency focused on content marketing
for businesses and brands. If you're looking to save time
and be more consistent with your marketing and need a
little guidance on what to say and how to say
it and where to say it. We got your back
book a discovery call today and let's talk
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