April 4, 2026 • 15 mins
In this episode of "Full Tech Ahead," Amanda Razani interviews Ryan Johnson, CPO of CallRail, about how Artificial Intelligence can benefit small and medium-sized businesses (SMBs). Johnson explains CallRail's evolution into a conversation intelligence platform and advises business owners to use AI to solve long-standing "legacy problems"—such as managing after-hours calls or handling peak call volumes—rather than inventing new problems to solve.
He emphasizes the importance of starting small, setting realistic expectations, and securing leadership buy-in to avoid the high failure rate of AI projects. Finally, the discussion touches on the future of AI, including the rise of agentic AI and its potential impact on search engines and SEO.
Key Quotes
"Where can AI solve the gaps that you've probably had for many, many years?"
"The most important thing about AI is it's not this like light switch that this happens. You actually have to invest time into it from a lot of different angles."
"Start small, start somewhere, don't be afraid of it and, and just learn."
Takeaways
Target Legacy Problems: AI is highly effective at filling gaps in daily operations, such as handling peak-hour calls, answering queries after traditional business hours, and conducting initial lead qualification.
Start Small and Be Realistic: Avoid overwhelming implementations. Begin with a narrow, focused use case to get comfortable. Set realistic expectations, as AI is not magic and often requires fine-tuning to achieve high accuracy.
Leadership Buy-in is Crucial: To avoid the common pitfall of AI project failures, businesses must define clear, measurable goals and ensure full support from the executive team and business owners before implementation.
The Future is Agentic AI: The next major evolution will involve AI agents communicating with one another to execute complex tasks, which will likely redefine consumer search experiences and the future of SEO.
Find Amanda Razani on LinkedIn. https://www.linkedin.com/in/amanda-razani-990a7233/
Follow the FTA LinkedIn Page: https://www.linkedin.com/company/full-tech-ahead/
Visit the FTA website: https://fulltechahead.com/
Check out the Substack Channel: https://fulltechahead.substack.com/
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Transcript
Episode Transcript
Available transcripts are automatically generated. Complete accuracy is not guaranteed.
SPEAKER_00 (00:19):
Hello, and welcome to Full Tech Ahead.
I am Amanda Razzani, and with metoday I have Ryan Johnson.
He's the CPO at CallRail.
How are you doing?
SPEAKER_01 (00:29):
I'm doing great.
Thanks for having me.
SPEAKER_00 (00:31):
Happy to have you on the show.
Can you share with our audiencea little bit about CallRail and
what services you provide?
SPEAKER_01 (00:38):
Sure.
So CallRail is almost 15 yearsold.
It started originally as uh acall tracking company.
Um, and what that means isreally focus on tracking online
to offline conversions for smallmedium businesses that rely on
inbound phone calls as theirprimary lead source.
Um so, in simple terms, youknow, we all utilize Google and
(01:01):
now maybe OpenAI and some ofthese other searches.
Uh, we look for thosebusinesses.
Um, and as soon as uh we findthem, a lot of times we place
those calls, and that's uh whatCallRail uh uh thankfully
attributes to all that marketingspend that happens uh digitally,
you know, whether that's um onGoogle or or social or or
(01:22):
beyond.
And so that's how the companystarted.
Kind of fast forward to today,we've taken that other steps
further from a lead engagementplatform to focus on what's
actually happening during theconversation.
So conversation intelligence.
So being able to analyze umutilizing AI.
How did the conversation go?
Simple things like sentiment,summarizing it, what are the
(01:44):
next best steps, uh, helping thecompany um with like auto
generation of text message andemail follow-up.
Uh, and then most recently, wejust launched our voice AI uh
product to help our customersmake sure that they never miss a
lead.
So if it's after hours oroverflow um or lead
qualification, we can lean on umAI to basically make sure that
(02:09):
revenue gets captured and nevergets lost.
SPEAKER_00 (02:12):
Wonderful.
Well, that's a good segue intoour topic of the day, which is
how AI can benefit smallbusinesses and why it should be
top of mind this year.
So can you share a little bitabout uh you work with different
business leaders?
Where can AI most help smallbusinesses?
SPEAKER_01 (02:31):
That's a great question.
I think, first off, it can bevery overwhelming, right?
Um, for small and mediumbusinesses.
Um, they have a lot going on.
Um, a lot of the the owners wearmultiple hats.
They're the marketer, they'rethe owner, they're the person
actually doing the work.
So I think really the biggestunlock is how do you use AI to
fill those gaps?
Uh, we know hiring people isreally tough to get them uh
(02:55):
trained up and have all thecontext.
Um and so, you know, what I sayfrom a more generalized
standpoint is where can AI solvethe gaps that you've probably
had for many, many years?
I think a lot of times companiesfocus AI and solving new
problems.
Guess what?
There's a lot of like legacyproblems that small and medium
businesses have, like havingenough people to answer the
(03:16):
phone during a peak, you know,uh part of the season, or at six
o'clock at night, um, you know,uh the ability to have something
interact with customers that maynot be on traditional hours that
your mis your business may beon, or just being able to handle
things like uh triage and andand lead qualification up front.
(03:37):
We know a lot of thesebusinesses can get, you know,
spam calls and people sellingthings to them.
And so if you think of time asthat commodity that's really
important, I think AI can help,you know, multiple AIs, whether
it's front of the house withlike conversational AI helping
or even like kind of post um,you know, say analytics is, you
know, of all the things that arehappening in your business, how
(03:59):
can AI do things in a muchquicker fashion so you can get
to the data that you need uhversus spending all the time uh
you know manually doing thisstuff?
I think it's been a really bigunlock for a lot of these
businesses.
SPEAKER_00 (04:12):
So I think preparation is really important
before any sort of AIimplementation.
So what's your advice as far aswhat are the first steps when it
comes to choosing what's themost important uh problems that
they want solved and how to findthe right solution and then the
implementation phase?
Yeah.
SPEAKER_01 (04:32):
So I always say start small, right?
I think right now a lot of timesum if you you know read on a
daily basis all the newinnovation, you can kind of go
to the nth degree of like, I cansolve this, I can solve this, I
can do that.
Um, where it's just like pickpick a very narrow thing so that
you can get comfortable withthat um and learn from it.
Because the the most importantthing about AI is it's not this
(04:54):
like light switch that thishappens.
You actually have to invest timeinto it from a lot of different
angles.
Um, certainly businesses thathelp reduce that time.
That's what CallRail kind offocuses on.
We've been like a self-servicebusiness since we started
because again, we got to make iteasier for small, medium
businesses.
I think when looking to partnerwith companies is like, how can
(05:15):
they get that time to value downas quickly as possible?
Um, and some of these things canbe really complex and
overwhelming, you know, justsetting up an agent, like where
do I start and how do I makesure it does the right things
and those types of things.
So my advice is start small andalso know that you have to
invest some time to make it uh agood representation of your
(05:36):
company or do what it needs todo.
And I think the last thing Iwould tell uh businesses is um
figure out what your expectationbar is.
I think a lot of people read inthe market, hey, AI is you know
perfect and and it can do allthese things magically, and it
can, but relate that back tohuman if you're kind of
comparing it to humanperformance, even on basic
(05:57):
things like transcription orsummaries, you know, don't don't
go out of the gate and say AI isgonna be 99%, you know, accurate
and precise.
Um, you may have to fine-tune itto get there.
And I think over time it willget better as these new models
come out.
Um, but I think giving yourselfa realistic expectation is
really important too, because Ithink a lot of folks just shoot
(06:18):
way beyond that.
Uh and then they get frustratedand then they say, well, I'm not
gonna use it.
Um and so I think it's it'sreally just kind of defining
those success metrics before youdive into um implementing any
new technology or tools.
SPEAKER_00 (06:32):
Yeah, I was going to ask, um, how big a problem is AI
acceptance and adoption stillwithin businesses?
SPEAKER_01 (06:40):
I think it varies, and you'd be surprised.
And it surprises me all the timeif you look at data, especially
for um the smaller businessesand their ability to adopt it.
It varies by vertical andindustry.
And I think some of them thatyou would assume um would be
hesitant are the ones that arediving, you know, feet first.
And you kind of see it all overthe place right now.
(07:03):
I think the stats, though, everysingle month it's like SMBs or
businesses, you know, it's like,was that 30 and 40 and 50%
utilize AI in some way?
You know, I think behind thecurtain, you don't really know
what that means.
Are they just playing with youknow, Chat GPT or perplexity or
anthropic, or are they actuallytruly implementing new
(07:24):
technology into their process?
You know, on the flip side, yousee, um, especially at the
enterprise level, like all theheadlines, 90% of AI projects
fail, right?
Like these big um, you know,kind of attention-grabbing
headlines.
Uh, so I think you see it kindof all over the place right now.
It's so new, it's moving sofast.
You know, again, I think for anycompany, it's kind of focusing
(07:47):
on realistic expectations,onboarding, investing into that
to make sure that it'ssuccessful.
But it's all over the place.
And I've tried to do my ownresearch to say, well, what if
you went into rural America andthis city?
Like, there's no way like yourcustomers would interact with
AI, and then someone disprovesme, you know, the very next day,
where it's like, oh, Domino'srelease their, you know, AI
(08:08):
order taker and it performs thebest in the middle of Iowa.
And you're like, Wait, what?
That makes like no sensewhatsoever.
So I think that makes it fun andexciting, certainly where I sit
in my role, uh, but also verychallenging because we just
don't have enough data yet andand it's just moving at at
lightning speed.
SPEAKER_00 (08:25):
So, in regard to that, you know, those headlines,
90% of AI projects fail.
Um, so how do we ensure thatthat's not correct and and
doesn't play out in that way?
What advice do you have once itcomes to that AI implementation
stage to ensure that they havesuccess?
SPEAKER_01 (08:42):
Yeah, I I think setting like goal expectation
setting is really big out of thegate.
I think that's part of theproblem.
I think a lot of companies andpeople just react like, okay, I
got to implement AI.
What's truly the goal thatyou're going after?
Picking the wrong goal, like thethe wrong ROI is a big piece of
that, right?
You know, people go into thisand say, well, I want to reduce,
(09:04):
you know, increase productivityby 30%, or I want to do these
things.
Sometimes it's really hard tomeasure.
Um, and sometimes they blow outthe scope of all the different
things they're trying to measureand they implement too many
things at once.
I also think the uh the piece ofadoption is I hear a lot of
companies, it's just like if youdon't have buy-in from
leadership team, executiveleadership team, other
(09:26):
individuals, and and that evengoes down to the the smallest
companies.
Like if you're trying toimplement AI and the business
owner doesn't want to do it,like it's probably gonna fail,
right?
So I I think you know, pickingthose goals um and being
reasonable about them, alsowhile you know, making sure you
have buy-in to to what thosegoals are.
(09:46):
And you know, I don't think it'sthose ideas are not novel.
I think it's for like anytechnology project, AI or new
process or any of that type ofstuff, you have to do it.
I think again, people get tooenamored with with AI and they
think it just is the magicbutton and it solves it.
And um, just like any otherthing in the past, um, some of
those things don't go awaybecause of its AI.
(10:07):
It's actually more important totrack the progress and what your
actual goals are before you everdecide to implement it um uh in
in your business.
SPEAKER_00 (10:17):
So we see AI advancing quite rapidly.
What do you envision is thefuture?
Give some use cases that youimagine might be popular in the
next year or so.
SPEAKER_01 (10:29):
Yeah, I think 2025 was certainly, I would say, the
you know, get prototype and showwhat it can do year.
Um, and and even the smallestcompanies can do it really
quick, and that makes itexciting and it gives uh buyers
lots of optionality out there.
I think over the next couple ofyears, especially when it comes
to like agentic AI and and andAI agents, um, how they
(10:54):
communicate with each otherefficiently, I think is a is
going to be a big deal.
I think a lot of the initialimplementations were this agent
has this context that can dothis.
Uh, but now with things like MCPand and you know just other
contexts and knowledge sharing,it becomes really powerful,
right?
So another agent can talk toanother agent over here and and
(11:14):
that agent specialized.
So the you know, thearchitecture and the setup isn't
as burdensome.
So I think the interconnectivityof how these things interact
will be uh really important onthe business level, but also on
the consumer level.
If you think of, you know,comment um, you know, with
perplexity coming out with theirbrowser, and you kind of have
these agents on the side thatcan help you as you browse, I
(11:36):
think my hope is that theyreally start to pan out and help
out, right?
As us as consumers, it reallygoes to that next level where I
hear anecdotes of people that'vebeen able to do amazing things
like plan their vacation and anddo all this type of stuff.
But when you get into it, it canbe really difficult.
Like if you didn't experience itand you're like, how the heck
did these people over here dothis whole thing when I'm doing
(11:58):
this and it's not working out inthe same way?
It didn't find the best pricesand it didn't give me the the
exact uh information.
So I I think the the sense oflike a consumer co-pilot in your
browser will will change search.
Um, I think that goes to a lotof the like AEO and GEO, you
know, the next um gen of of SEO.
(12:19):
I think that will continue totake off because none of those
uh LLM search has done anythingpaid yet.
Uh but we we think it's coming.
We we we thought we saw OpenAIdo a little test and they pulled
it back.
We don't really know for sure.
But I I think those are thethings in the next year or two,
you know, search will beredefined and hopefully be
better for all of us asconsumers connecting with
(12:41):
businesses.
And I think overall, I think themodels will just continue to
dramatically get better, which Ihope because a lot of the stuff
that happens today, it's alittle bit of a black box.
A lot of this technology is allbuilt on three or four players.
And when it you knowhallucinates or has a small
issue, every time they theyupdate the model, it seems like
those get less and less umprevalent.
(13:03):
And so I also hope that just ingeneral, those kind of why did
this agent decide to say thisout of the blue um without any
prompting, like I hope thosethings will continue to go away
where you know it will just workway better than than we even
thought.
SPEAKER_00 (13:19):
It will be interesting to see what unfolds.
It's really fun to watch.
SPEAKER_01 (13:23):
Yeah, absolutely.
I think the the other one, youknow, that I go back and forth
on, but any of the AI robotstuff, um, you know, this this
whole concept of you know ithelping out either in the
workforce or in your house, um,it's kind of interesting because
I feel that's the one that'sgonna take a little bit longer,
(13:43):
you know, just the we just don'thave the data sets of like human
touch to be able to train thesethings um in different different
types of things.
Um it's also exciting one forfor me as well to say, okay,
where does this go?
Which is completely outside ofthe you know the box that you
and I are in right now, um uh onour computers.
So um I think that will beanother one.
(14:05):
How fast we go though, that'sthat's like the big question
mark for me.
SPEAKER_00 (14:08):
Yeah, I'd love to be uh selected to be a physical
trainer of uh a robot in myhouse and try to train it to do
all the different chores, washshits.
SPEAKER_01 (14:21):
Yeah, exactly.
And then you know, you have likeiRobot that just went bankrupt
with the Roomba, and you'relike, how does that happen now?
I was waiting for like the nextRoomba that would, you know, fly
around the house and be able tomop and uh vacuum and do
everything, but I guess we'llhave to wait for that.
SPEAKER_00 (14:38):
All right.
Well, if there was one keytakeaway you could leave our
audience with today, what wouldthat be?
SPEAKER_01 (14:43):
For me, the biggest thing is I think just start
small, start somewhere.
Um, don't be afraid of it and uhand just learn.
I think a lot of people um don'twant to miss the boat and and
you know, the train hasn't leftthe station, the boat hasn't
left, but it's coming.
And and so, you know, in orderfor you to be a part of the
(15:06):
change that will happen in manydifferent ways, um, just
figuring out little ways to umcontinue to understand and
utilize it um in your business,in your personal life, I think
that's the biggest thing to me.
It's just little bits all thetime.
Um, and then over time you'llget you'll get comfortable and
and be a pro as as we all gothrough this together.
SPEAKER_00 (15:26):
Yeah.
All right.
Well, thank you so much forcoming on the show and sharing
your insights with us today.
SPEAKER_01 (15:31):
Yeah, thanks for having me.
SPEAKER_00 (15:32):
And thank you to our audience.
Share what was the mostinteresting in the comments.
Where do you envision AI goingin the coming year?
All right, and until next week,have a great day.
Hello, and welcome to Full Tech Ahead.
I am Amanda Razzani, and with metoday I have Ryan Johnson.
He's the CPO at CallRail.
How are you doing?
SPEAKER_01 (00:29):
I'm doing great.
Thanks for having me.
SPEAKER_00 (00:31):
Happy to have you on the show.
Can you share with our audiencea little bit about CallRail and
what services you provide?
SPEAKER_01 (00:38):
Sure.
So CallRail is almost 15 yearsold.
It started originally as uh acall tracking company.
Um, and what that means isreally focus on tracking online
to offline conversions for smallmedium businesses that rely on
inbound phone calls as theirprimary lead source.
Um so, in simple terms, youknow, we all utilize Google and
(01:01):
now maybe OpenAI and some ofthese other searches.
Uh, we look for thosebusinesses.
Um, and as soon as uh we findthem, a lot of times we place
those calls, and that's uh whatCallRail uh uh thankfully
attributes to all that marketingspend that happens uh digitally,
you know, whether that's um onGoogle or or social or or
(01:22):
beyond.
And so that's how the companystarted.
Kind of fast forward to today,we've taken that other steps
further from a lead engagementplatform to focus on what's
actually happening during theconversation.
So conversation intelligence.
So being able to analyze umutilizing AI.
How did the conversation go?
Simple things like sentiment,summarizing it, what are the
(01:44):
next best steps, uh, helping thecompany um with like auto
generation of text message andemail follow-up.
Uh, and then most recently, wejust launched our voice AI uh
product to help our customersmake sure that they never miss a
lead.
So if it's after hours oroverflow um or lead
qualification, we can lean on umAI to basically make sure that
(02:09):
revenue gets captured and nevergets lost.
SPEAKER_00 (02:12):
Wonderful.
Well, that's a good segue intoour topic of the day, which is
how AI can benefit smallbusinesses and why it should be
top of mind this year.
So can you share a little bitabout uh you work with different
business leaders?
Where can AI most help smallbusinesses?
SPEAKER_01 (02:31):
That's a great question.
I think, first off, it can bevery overwhelming, right?
Um, for small and mediumbusinesses.
Um, they have a lot going on.
Um, a lot of the the owners wearmultiple hats.
They're the marketer, they'rethe owner, they're the person
actually doing the work.
So I think really the biggestunlock is how do you use AI to
fill those gaps?
Uh, we know hiring people isreally tough to get them uh
(02:55):
trained up and have all thecontext.
Um and so, you know, what I sayfrom a more generalized
standpoint is where can AI solvethe gaps that you've probably
had for many, many years?
I think a lot of times companiesfocus AI and solving new
problems.
Guess what?
There's a lot of like legacyproblems that small and medium
businesses have, like havingenough people to answer the
(03:16):
phone during a peak, you know,uh part of the season, or at six
o'clock at night, um, you know,uh the ability to have something
interact with customers that maynot be on traditional hours that
your mis your business may beon, or just being able to handle
things like uh triage and andand lead qualification up front.
(03:37):
We know a lot of thesebusinesses can get, you know,
spam calls and people sellingthings to them.
And so if you think of time asthat commodity that's really
important, I think AI can help,you know, multiple AIs, whether
it's front of the house withlike conversational AI helping
or even like kind of post um,you know, say analytics is, you
know, of all the things that arehappening in your business, how
(03:59):
can AI do things in a muchquicker fashion so you can get
to the data that you need uhversus spending all the time uh
you know manually doing thisstuff?
I think it's been a really bigunlock for a lot of these
businesses.
SPEAKER_00 (04:12):
So I think preparation is really important
before any sort of AIimplementation.
So what's your advice as far aswhat are the first steps when it
comes to choosing what's themost important uh problems that
they want solved and how to findthe right solution and then the
implementation phase?
Yeah.
SPEAKER_01 (04:32):
So I always say start small, right?
I think right now a lot of timesum if you you know read on a
daily basis all the newinnovation, you can kind of go
to the nth degree of like, I cansolve this, I can solve this, I
can do that.
Um, where it's just like pickpick a very narrow thing so that
you can get comfortable withthat um and learn from it.
Because the the most importantthing about AI is it's not this
(04:54):
like light switch that thishappens.
You actually have to invest timeinto it from a lot of different
angles.
Um, certainly businesses thathelp reduce that time.
That's what CallRail kind offocuses on.
We've been like a self-servicebusiness since we started
because again, we got to make iteasier for small, medium
businesses.
I think when looking to partnerwith companies is like, how can
(05:15):
they get that time to value downas quickly as possible?
Um, and some of these things canbe really complex and
overwhelming, you know, justsetting up an agent, like where
do I start and how do I makesure it does the right things
and those types of things.
So my advice is start small andalso know that you have to
invest some time to make it uh agood representation of your
(05:36):
company or do what it needs todo.
And I think the last thing Iwould tell uh businesses is um
figure out what your expectationbar is.
I think a lot of people read inthe market, hey, AI is you know
perfect and and it can do allthese things magically, and it
can, but relate that back tohuman if you're kind of
comparing it to humanperformance, even on basic
(05:57):
things like transcription orsummaries, you know, don't don't
go out of the gate and say AI isgonna be 99%, you know, accurate
and precise.
Um, you may have to fine-tune itto get there.
And I think over time it willget better as these new models
come out.
Um, but I think giving yourselfa realistic expectation is
really important too, because Ithink a lot of folks just shoot
(06:18):
way beyond that.
Uh and then they get frustratedand then they say, well, I'm not
gonna use it.
Um and so I think it's it'sreally just kind of defining
those success metrics before youdive into um implementing any
new technology or tools.
SPEAKER_00 (06:32):
Yeah, I was going to ask, um, how big a problem is AI
acceptance and adoption stillwithin businesses?
SPEAKER_01 (06:40):
I think it varies, and you'd be surprised.
And it surprises me all the timeif you look at data, especially
for um the smaller businessesand their ability to adopt it.
It varies by vertical andindustry.
And I think some of them thatyou would assume um would be
hesitant are the ones that arediving, you know, feet first.
And you kind of see it all overthe place right now.
(07:03):
I think the stats, though, everysingle month it's like SMBs or
businesses, you know, it's like,was that 30 and 40 and 50%
utilize AI in some way?
You know, I think behind thecurtain, you don't really know
what that means.
Are they just playing with youknow, Chat GPT or perplexity or
anthropic, or are they actuallytruly implementing new
(07:24):
technology into their process?
You know, on the flip side, yousee, um, especially at the
enterprise level, like all theheadlines, 90% of AI projects
fail, right?
Like these big um, you know,kind of attention-grabbing
headlines.
Uh, so I think you see it kindof all over the place right now.
It's so new, it's moving sofast.
You know, again, I think for anycompany, it's kind of focusing
(07:47):
on realistic expectations,onboarding, investing into that
to make sure that it'ssuccessful.
But it's all over the place.
And I've tried to do my ownresearch to say, well, what if
you went into rural America andthis city?
Like, there's no way like yourcustomers would interact with
AI, and then someone disprovesme, you know, the very next day,
where it's like, oh, Domino'srelease their, you know, AI
(08:08):
order taker and it performs thebest in the middle of Iowa.
And you're like, Wait, what?
That makes like no sensewhatsoever.
So I think that makes it fun andexciting, certainly where I sit
in my role, uh, but also verychallenging because we just
don't have enough data yet andand it's just moving at at
lightning speed.
SPEAKER_00 (08:25):
So, in regard to that, you know, those headlines,
90% of AI projects fail.
Um, so how do we ensure thatthat's not correct and and
doesn't play out in that way?
What advice do you have once itcomes to that AI implementation
stage to ensure that they havesuccess?
SPEAKER_01 (08:42):
Yeah, I I think setting like goal expectation
setting is really big out of thegate.
I think that's part of theproblem.
I think a lot of companies andpeople just react like, okay, I
got to implement AI.
What's truly the goal thatyou're going after?
Picking the wrong goal, like thethe wrong ROI is a big piece of
that, right?
You know, people go into thisand say, well, I want to reduce,
(09:04):
you know, increase productivityby 30%, or I want to do these
things.
Sometimes it's really hard tomeasure.
Um, and sometimes they blow outthe scope of all the different
things they're trying to measureand they implement too many
things at once.
I also think the uh the piece ofadoption is I hear a lot of
companies, it's just like if youdon't have buy-in from
leadership team, executiveleadership team, other
(09:26):
individuals, and and that evengoes down to the the smallest
companies.
Like if you're trying toimplement AI and the business
owner doesn't want to do it,like it's probably gonna fail,
right?
So I I think you know, pickingthose goals um and being
reasonable about them, alsowhile you know, making sure you
have buy-in to to what thosegoals are.
(09:46):
And you know, I don't think it'sthose ideas are not novel.
I think it's for like anytechnology project, AI or new
process or any of that type ofstuff, you have to do it.
I think again, people get tooenamored with with AI and they
think it just is the magicbutton and it solves it.
And um, just like any otherthing in the past, um, some of
those things don't go awaybecause of its AI.
(10:07):
It's actually more important totrack the progress and what your
actual goals are before you everdecide to implement it um uh in
in your business.
SPEAKER_00 (10:17):
So we see AI advancing quite rapidly.
What do you envision is thefuture?
Give some use cases that youimagine might be popular in the
next year or so.
SPEAKER_01 (10:29):
Yeah, I think 2025 was certainly, I would say, the
you know, get prototype and showwhat it can do year.
Um, and and even the smallestcompanies can do it really
quick, and that makes itexciting and it gives uh buyers
lots of optionality out there.
I think over the next couple ofyears, especially when it comes
to like agentic AI and and andAI agents, um, how they
(10:54):
communicate with each otherefficiently, I think is a is
going to be a big deal.
I think a lot of the initialimplementations were this agent
has this context that can dothis.
Uh, but now with things like MCPand and you know just other
contexts and knowledge sharing,it becomes really powerful,
right?
So another agent can talk toanother agent over here and and
(11:14):
that agent specialized.
So the you know, thearchitecture and the setup isn't
as burdensome.
So I think the interconnectivityof how these things interact
will be uh really important onthe business level, but also on
the consumer level.
If you think of, you know,comment um, you know, with
perplexity coming out with theirbrowser, and you kind of have
these agents on the side thatcan help you as you browse, I
(11:36):
think my hope is that theyreally start to pan out and help
out, right?
As us as consumers, it reallygoes to that next level where I
hear anecdotes of people that'vebeen able to do amazing things
like plan their vacation and anddo all this type of stuff.
But when you get into it, it canbe really difficult.
Like if you didn't experience itand you're like, how the heck
did these people over here dothis whole thing when I'm doing
(11:58):
this and it's not working out inthe same way?
It didn't find the best pricesand it didn't give me the the
exact uh information.
So I I think the the sense oflike a consumer co-pilot in your
browser will will change search.
Um, I think that goes to a lotof the like AEO and GEO, you
know, the next um gen of of SEO.
(12:19):
I think that will continue totake off because none of those
uh LLM search has done anythingpaid yet.
Uh but we we think it's coming.
We we we thought we saw OpenAIdo a little test and they pulled
it back.
We don't really know for sure.
But I I think those are thethings in the next year or two,
you know, search will beredefined and hopefully be
better for all of us asconsumers connecting with
(12:41):
businesses.
And I think overall, I think themodels will just continue to
dramatically get better, which Ihope because a lot of the stuff
that happens today, it's alittle bit of a black box.
A lot of this technology is allbuilt on three or four players.
And when it you knowhallucinates or has a small
issue, every time they theyupdate the model, it seems like
those get less and less umprevalent.
(13:03):
And so I also hope that just ingeneral, those kind of why did
this agent decide to say thisout of the blue um without any
prompting, like I hope thosethings will continue to go away
where you know it will just workway better than than we even
thought.
SPEAKER_00 (13:19):
It will be interesting to see what unfolds.
It's really fun to watch.
SPEAKER_01 (13:23):
Yeah, absolutely.
I think the the other one, youknow, that I go back and forth
on, but any of the AI robotstuff, um, you know, this this
whole concept of you know ithelping out either in the
workforce or in your house, um,it's kind of interesting because
I feel that's the one that'sgonna take a little bit longer,
(13:43):
you know, just the we just don'thave the data sets of like human
touch to be able to train thesethings um in different different
types of things.
Um it's also exciting one forfor me as well to say, okay,
where does this go?
Which is completely outside ofthe you know the box that you
and I are in right now, um uh onour computers.
So um I think that will beanother one.
(14:05):
How fast we go though, that'sthat's like the big question
mark for me.
SPEAKER_00 (14:08):
Yeah, I'd love to be uh selected to be a physical
trainer of uh a robot in myhouse and try to train it to do
all the different chores, washshits.
SPEAKER_01 (14:21):
Yeah, exactly.
And then you know, you have likeiRobot that just went bankrupt
with the Roomba, and you'relike, how does that happen now?
I was waiting for like the nextRoomba that would, you know, fly
around the house and be able tomop and uh vacuum and do
everything, but I guess we'llhave to wait for that.
SPEAKER_00 (14:38):
All right.
Well, if there was one keytakeaway you could leave our
audience with today, what wouldthat be?
SPEAKER_01 (14:43):
For me, the biggest thing is I think just start
small, start somewhere.
Um, don't be afraid of it and uhand just learn.
I think a lot of people um don'twant to miss the boat and and
you know, the train hasn't leftthe station, the boat hasn't
left, but it's coming.
And and so, you know, in orderfor you to be a part of the
(15:06):
change that will happen in manydifferent ways, um, just
figuring out little ways to umcontinue to understand and
utilize it um in your business,in your personal life, I think
that's the biggest thing to me.
It's just little bits all thetime.
Um, and then over time you'llget you'll get comfortable and
and be a pro as as we all gothrough this together.
SPEAKER_00 (15:26):
Yeah.
All right.
Well, thank you so much forcoming on the show and sharing
your insights with us today.
SPEAKER_01 (15:31):
Yeah, thanks for having me.
SPEAKER_00 (15:32):
And thank you to our audience.
Share what was the mostinteresting in the comments.
Where do you envision AI goingin the coming year?
All right, and until next week,have a great day.
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