Episode Transcript
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Emcee (00:00):
So, whether you're using it or just considering it, or you're terrified of it, a conversation
about AI and its role in the future of business is a conversation worth having, and our next segment
is a panel discussion on exactly that topic. It is presented by the Action Catalyst, the flagship
program in the Southwestern Family of Podcasts. Launched in 2013 the Action Catalyst is a premier
entrepreneurship and leadership podcast which has found its way on the best of lists from the likes
of Inc, Entrepreneur, Business Insider and many, many more names that you've definitely heard of. It
stands at nearly 500 episodes strong, with listeners in over 160 countries. It is a free podcast,
and we think you'll love it, but if you don't, we'll give you your money back. Since 2022 the show
has been hosted by Adam Outland, president of Southwestern Consulting, and in over 20 years at
Southwestern, Adam has served as an elite level coach, partner and leader, founding the Southwestern
(01:16):
Student Coaching division, helping both professionals as well as youth unlock new levels of success.And in that time since 2022 Adam has welcomed many of the guests that are now gracing the stage onto
the podcast. Anya Cheng is the founder and CEO of Taelor, a revolutionary AI based apparel platform,
and she has also served as head of product for Facebook, eBay, Target, McDonald's and more, as well
as an adjunct lecturer of Product Management, Marketing and Entrepreneurship at Northwestern
University. Hardly a company, she has not been a head of product for. Dr Amy D'Aprix is the
president and founder of Lifebridge Strategies, part of the Southwestern Family of Companies, an
internationally renowned expert on lifestyle issues relating to retirement, aging, caregiving and
family dynamics, with a PhD in Social Work, Dr Amy has provided guidance on life transitions to
individuals, professionals and organizations for over three decades. Dave Brown is a founding
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partner and executive level sales and leadership coach for Southwestern Consulting who has trainedand spoken to hundreds of 1000s of sales professionals across the globe. He has reached almost as
many people as the Action Catalyst Podcast, in addition to being a consistent top producer himself,
Dave serves as vice president of recruiting for Southwestern Coaching. He's also a guest lecturer at
Vanderbilt University and has authored two phenomenal books, Painless Prospecting and most recently,
Servant Selling the essential handbook for closing more deals and giving your customers exactly what
they need. And finally, Gayathri Krishnamurthy, otherwise known as G3, coolest name on the stage, is
a global go to market leader, musician and avid traveler. She has run global go to market strategies
and product marketing for several leading B2B Sass companies, including Ring Central, NICE,
ServiceNow and Sugar CRM, just to name a few. And she is currently the Head of Product Marketing at
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Level AI. And everyone, this talk is being recorded for a very special Live episode of the ActionCatalyst podcast, our very first, so make a whole lot of noise for the Action Catalyst panel!
Adam Outland (03:30):
Let's give one more hand of applause for our amazing MC who did a great job. Yeah,
good job. Zach. Zach puts the whole Action Catalyst together for us. So it makes my job incredibly
easy, because he does all the editing, so you don't hear the ums and the ahs, so you may hear a few
those today.
Gayathri Krishnamurthy (03:53):
A special shout out for him. My full name with 26 alphabets. He nailed it.
Gayathri Krishnamurthy.
Adam Outland (04:01):
So good. All right, so we're gonna get started. How many of you guys are excited to
learn a little bit about tech and AI? Show of hands. Okay, let's get going. So we wanted to start
with Anya today with a special question. You got a little bit of her context and background for just
a amazing variety, variety of work that she's done. You've won awards for your work on product
across a number of these different companies target, meta, eBay, meta, you helped bring the internet
to countries that didn't already have it as their Head of Product Marketing. So you also helped
build an E commerce platform that many people here should know for Facebook, right?
Anya Cheng (04:35):
Yeah, if you buy something that's useless on Instagram, sorry about that. That was my
fault.
Adam Outland (04:41):
So if you wouldn't mind, though, tell us just, just in a few words, a little bit about
Taelor, your current business that you've founded, and we'll go from there.
Anya Cheng (04:49):
I started a company in the AI space. We use AI to pick clothes for man, definitely not
you. You're too stylish. But you know, all time, people have like said. 70 have human stylists, but
now with AI, everyone can have stylist in their pocket. So tailor. Ai, we help people to pick
clothes, but we send them real clothes for them to wear for couple weeks like this time you come to
the conference from Boston, for example, if you are busy man, you change your address, you ship the
hot clothes to the hotel lobby. You wear whole weeks. Once you are done tomorrow, you put into the
return envelope of your dirty clothes. You go home without doing any laundry for the day to day, if
you are just busy. Man, every month, people can wear like 10 clothes per month in our AI, pick the
outfit for the purpose, and from there, no more shopping or laundry.
Adam Outland (05:38):
I love that. So with that context. And given that AI is the capability of being this,
we've heard a lot that AI is the next internet of things, right? It's going to layer into everything
that we do. And given the experience that you've had, what are ways that you're learning to embrace
that functionality in your business?
Anya Cheng (05:55):
I think most important thing that I'm learning still is to make sure we're solving the
right problem. As a business leader, we tend to focus on what are the right solution. We have
problem, problem, problem, but many times, solving the right problem is a lot more important. For
example, at Amazon, the things that hey, truck drivers, they don't have a hand to turn on turn off a
light in the truck, so they decide to use AI to make sure that when the AI detects someone is in the
truck, the light goes on. Perfect. Works. In a day when AI can see a human, the light goes on and
the driver doesn't need a light during the day, right? And then in the evening, the AI couldn't see
the guy, so the driver, the light wasn't go on, and the driver needs the light. It wasn't working
because it's a wrong problem to solve. The same thing at eBay, when I was at eBay, we thought people
would love to snap a picture and write all the descriptions with AI, we launch a feature. Love it
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now the customers, they are not using it because of what they found out that they actually love towrite information because they care so much the item being sold, so they don't mind spending time to
make sure it's correct, and they can sell well. So the AI writing description wasn't working at
Target, we launch a feature for mom to go to a store. You will become a store. GPS, turn right, turn
left. Amazing. You'll never forget one thing moms didn't use it. Why moms are going to a store to
get lost. They like to be back to the store. They don't like store. Gym, yes, it's a way of getting
away from the noisy kids, right? So, perfect. Oh, my God, forgotten me. I have to go back again.
Husband, can you take a look at the two kids? Thanks, right? So finding the right problem to solve
still very important before you figure out how to use the technology to solve the wrong problem.
Adam Outland (07:43):
Well said, and I think so many people identified in the audience that story. Dr Amy,
let's go over to you for a few minutes. Tell us a little bit in your words, a little bit about
Lifebridge Strategies to give some context, and we'll go from there.
Dr. Amy D'Aprix (07:56):
Sure, Lifebridge Strategies, we are working with Wealth Advisors, but will be
coming to a profession near you, so hang on. We help Wealth Advisors deepen their relationships with
clients by better understanding the life transitions they go through. And we say transitions are the
stages, changes and events that we all go through during our life, things you know as we move
through midlife and beyond, things like the death of our parents and retirement and caregiving and
health challenges, so we help advisors better understand those, learn how to communicate with their
clients better around those and then we also give them resources on the life side that they can
share with their clients and that their clients can only get through them.
Adam Outland (08:40):
We had an interesting interaction. One of my good friends in Houston leads a Houston
firm for ultra high net worth clients in the advisor space. And this gentleman and I that we had
breakfast one morning, and he told me how he he asked corporate if he could take an additional
responsibility, not something people really enjoy doing when they're very happy with what they're
doing. But he saw something he saw with the with the integration of AI, that there was a big change
potentially coming for the financial services space. And so he volunteered. They may have paid him,
but he volunteered, initially, to take on the role of client experience nationally for their firm.
And I asked him why, and he began to talk a little bit about predicting the future and wanting to
have a position where he can get ahead of the curve. So I'm sure we have a lot of folks in this
space, out here in the audience, and some folks that are obviously not in that space. But what are
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some of the larger firms doing to prepare for the progression of AI?
Dr. Amy D'Aprix (09:35):
I get the opportunity to work both with large firms and with individual advisors,
and my team does as well. And I was I was sharing with you that last week, I was actually in front
of a very large firm that wanted me to talk to their technical planners, who partner with Wealth
Advisors. And the technical planners are client facing, but almost a little bit one removed. But
what they. Realize is AI, as we all know, is starting to at least enhance what they do, if not
replace some of the planning skills. But what the firms realize that their advisors and planners
really need are the human connection skills at a deeper and deeper level. And so firms are really
working to upscale on that, and I never call them soft skills. You know, Simon Sinek calls it human
skills, which I think is so much better, because soft skills make it sound unimportant. But large
firms are really looking at, how do we deepen our connection with clients to make sure that the
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clients are sticky, and how do we convert prospects into clients? It really comes down torelationship, and firms are spending a lot more time focusing on that in the time of AI.
Adam Outland (10:49):
Thanks. Dr Amy, so it's true, right? AI can accelerate the math formula of maybe
making a stock selection, but what AI seems to struggle more with is the human relation component.
People want that human touch.
Dr. Amy D'Aprix (11:02):
And that's where the gold is really right. That is our ability to connect. I always
say, I think one of the greatest human needs is to feel seen, heard and understood, not always
agreed with, but seen, heard and understood. And advisors who do that well are the ones who are most
successful.
Adam Outland (11:18):
Love it. Dave, you can pick up on this. You're obviously founded and helped build our
coaching business, our training business, in a world where AI seems to be taking over so many
different positions, we've even seen it encroach a little into our space. We've had different
companies that Tony Robbins has Dino AI that, like, has a little voice that duplicates himself, and
the first time you hear it, it's, like, really bizarre, because it's Tony crafting a message for
you. But he's not there. It's his AI impression. And you go, Is this really going to be the norm?
So, you know, with some of these entries taking place into our coaching market, you know, are you
concerned about the implications?
Dave Brown (11:53):
Not concerned. I'm more curious. I'm getting more curious with it and but you're right.
Like it's, there's this article that came across my phone The Wall Street Journal article, and I
took notes, because I don't want to miss anything. But it says, AI is coming for the consultants.
That was the name of the article. So it was like, of course, let me click on that one, right? Don't
you love those titles? But it was about McKinsey, you know, the largest consulting firm. Something
was alarming was they went from 45,000 consultants to 40,000 the last couple of years. And what's
even cooler, again, not alarming or anything else, but what's cooler is they have 12,000 AI agents
that are now working with them. So they've created these bots to complement their projects. And
that's a place where it's like, oh my gosh. You know, job, everything else, what's going to happen
for me? But every one of their projects has got two AI agents on it, on average. So us kind of stand
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ahead of that. That's a place where we need to evolve as a business. And I think that's the questionthat all of us need to be asking, is like, how can we get more curious about this? How can we go,
how can be playing in this space? And and I have been it's, I wrote this little kind of quote down
as I was piecing things together, AI, it almost mixes the best of our instincts with the processing
power, right? It's all it is information. It's not human instinct. It's blending technology with
humanity. We can almost ensure that our decisions are not only data driven, but they're also
grounded in critical thinking. And AI doesn't replace what makes us human. It enhances it. So that's
what I'm always kind of thinking. I'm not thinking of, oh, how I'm gonna go fix this and just type
this in and give me all the answers. How can it enhance me? Yes, many of you know this name, but the
former Google CEO Eric Schmidt, said, with the pace at which AI is evolving, entirely reasonable,
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that we're gonna live in a completely different, functional world in five years, not 10, five years.So that's getting me to go, all right? I need to know about this stuff and how I can best do as much
as I can with it. So yeah, a lot of other resources that are out there, but I need to get curious,
and I need to learn as much as I can about it.
Adam Outland (13:56):
Some of that curiosity led us to pick a certain vendor that's on stage with us.
Dave Brown (14:01):
It did.
Gayathri Krishnamurthy (14:02):
I want to comment on one point he made.
Dave Brown (14:05):
Good.
Gayathri Krishnamurthy (14:06):
Which is, Hey, you are an awesome sports person. AI is never going to
replace a sports person.
Dave Brown (14:12):
It can give you some strategy though. It can give you some strategy.
Gayathri Krishnamurthy (14:15):
Exactly. There are a lot of roles which will not be wiped out.
Adam Outland (14:19):
Let's piggyback on this. So, you know, one of the things we did was we were doing some
research, and you figure out, how can we interact and engage with AI in a way that would be relevant
and supportive of the business? And that's where we came across level AI. So if you wouldn't mind g3
instead of me doing the whole preview, why don't you share a few words about what level AI seeks to
accomplish, and we'll piggyback on that.
Gayathri Krishnamurthy (14:40):
Sure. I was meeting a lot of you guys yesterday. You've been using so many
amazing tools in AI and one thing that struck me was there they are very disparate tools. What level
AI does is it brings a lot of tools, AI tools, but it's all trained. Built on a common company data,
which is important because an AI tool cannot operate in silos. So level, AI is all about getting a
lot of models together and really honing in on the domain of customer experience, building great
customer relations. And to your point, Amy, it's all about, you know, the human skills and what
level AI does is really gives you a lot of analytics and insights into customer interaction. So we
take all your customer interactions, we do two things. One is give you great insights from every
single conversation that's happened that can really surface what the big problems are. Number one.
Number two is it helps to automate a lot of processes, like taking notes, updating, automating, and
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all that stuff. And the beautiful thing about this is, when you automate, you want to see how it isgoing with the customer, meaning, what's the insight that I can get after automation? So there's
this beautiful loop of there's insights that I get, I automate, then I get insights and I automate,
I kind of course correct, so you have a human and an agent balance. So that's what, in a nutshell,
label AI does to help you with all the customer insights. Automate where possible, and keep that
continuous loop going.
Adam Outland (16:17):
And let's, let's continue on. So one of the key challenges today, and we Dave brought
this up a little bit. Isn't the collection of data. We've been able to collect data for a long time.
I was with one of our other clients in Houston, looking at his giant warehouse of paper. Right? He
was in the paper collection industry of scanning and digitizing paper. It isn't the collection of
data that's so difficult today. We've We've managed that. Tech has helped us with that, but it's how
the data is interpreted. So how does AI help us actually do correct interpretation of data? Get
there quicker, more effectively? What are ways and areas that AI data interpretation can be most
helpful?
Gayathri Krishnamurthy (16:53):
So if you look at the customer conversation, it is happening over phone,
over websites, over social media, so there's no dearth of data. So what's happened in the past is we
have had some analytics tool which is able to parse through that get some insights. And what AI is
doing is really putting literally, it's on steroids, and the reason being, 90% of the data is
unstructured data, so getting a lot of insights from an unstructured data was tougher in the older
iteration of AI. Now with the newer iteration of AI, that's the huge aperture that we're widening
up. So what happens is now you're able to make sense of data, and not just 100% of data. And again,
think about this fact, 100% of all the conversations that your customers are having is brought in,
and you're putting an AI on top of it, the kind of insights are going to be great, not just because
you had access to data, but also the type of insights. For example, you can find the sentiment, you
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can find the effort involved in resolution. You can find maybe the resolution, whether it happenedor not, maybe the agents say they resolve it, but it's not really resolved. So there are multiple
parameters that are more AI driven that you're able to get at a large scale. So every conversation
mind for sentiment and all of those. And in fact, we have inferred CSAT on every conversation that
gives you a lot of view in what's really breaking right? For example, if you look at all the 100%
conversations and you're saying, my top issue you thought was maybe billing. But then, for all you
know, it could be something else. It could be pricing that you didn't look at it. So the the idea of
just looking for certain things and watching out that era is gone. Now you have to be proactive and
listen. You have to be a listening post. So AI really helps with that. So I feel like one of the
biggest things that we look at from an AI perspective is, how can I use that insight, how can I use
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the customer issues that are bubbling up, and take that and drive your operations, really gettinginto that outside in view, because we are quick to automate stuff. Okay, let me automate Okay,
updating CRM, let me automate it, getting a summary of a call, let me automate it. That's great.
We're getting lower returns, but the biggest, larger value is gonna come when you're really looking
at the customer and pivoting your operations to align with it. That's where I feel the power of AI
is not just in the automation, but the insights connecting the two. I think that's where, you know,
I'm gonna the one thing that I would leave with you all is really getting that insight from the
customer. You know, putting that lens as like the primary lens, as you do, especially in small
business, because that's kind of. Heart of a small business, the customer relationship, that would
be one of the things I would leave with the audience here.
Adam Outland (20:06):
And it's amazing how AI can take a data set and then self optimize with that data. So
if it's listening to 100 sales calls, it can potentially learn from its own set of data, and as long
as maybe a human helps indicate what's good versus bad, initially, it can spool it can spool up its
learning and provide more accurate feedback.
Gayathri Krishnamurthy (20:25):
Exactly. And you can use that to train, you know, C player to an A player
and all that kind of stuff. So it's like, now that you've really found the insights, it's, you know,
it's easy to kind of look at the correlations and all that good stuff.
Adam Outland (20:39):
Love it. Anya back to you in what way is AI allowing you to scale your business? What
roles did you find it replacing in your industry and space to allow you to scale quicker, faster and
serve more clients?
Anya Cheng (20:51):
I think first, when you guys are using AI, first think about what's the biggest value?
Because star 8020, rule, right? So star is the biggest value. For example, we found that our
customers, they are not here just about renting clothes. They are here to buy a success, chance to
succeed. So they don't care what they wear. They care getting a job, getting a day, close a deal.
The reason they are using our AI style lists and closing rental service is that they want to achieve
that goal, and they want this become a tool to help them get their girlfriend boyfriends. So
starting with that and doing the laundry. So who say I cannot do the laundry, right? So, so the
first thing we do is like, okay, the key value is number one, styling. But styling take a lot of
people in the old time. The human style is a white celebrity have stylists, because it's expensive,
right? So we start by looking at, okay, that's biggest value for the company and for the customer.
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So we start doing AI styling. So we ask people to upload a few pictures, ask them for their high endway, which we don't always use, because our customer, for some reason, busy men, tend to think they
are thinner and taller. So data is important, but garbage in, garbage out. So when you have wrong
data, you won't get the right outfit. So we tend to ask verification question, go to your closet,
pick your favorite outfit. Oh, my God, when am I becoming extra large? So we asked some other
question to make sure the data is right? We ask them like, fit issues, all the sleeve too long,
pants too tight. We ask them to ask some questions, like, what brand inspire you? And then our
customer will say, Armani and Louis Vuitton. Where are you shopping today? Costco and unicola. Okay,
great. Now I know where you are. What kind of clothes should I send you? So we use AI stylers to do
so. But then after the most valuable part, now we come in and look at our company's workflow. Where
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are we spending time? How can we streamline each part? For example, getting customers number one,right? So we use chatgpt for SEO, so G Suite said about something very, very important. I want to
highlight one more time. She said, different from Google Chat, GPT, search optimization is including
a lot more unstructured data means. What means for you guys who are doing SEO before you need to
make sure this image has Adam's name behind it, write down the text. Otherwise Google couldn't read
nowadays, chatgpt, the AI, they can read unstructured data, the image and video and other stuff. So
the logic overall still the same, but the generating content become different. So we use it for SEO
purposes, which I can share more later. We use it for styling. No. When we send our customer
clothes, the old time, the stylist will say, pair this two top, believe or not, when we send seven
items to our customer, they still ask us, oh, there are two top which one should I pair with these
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two pens? Which one? So we write down the styling, no, using AI, and we say, okay, pair this withthese sneakers, white sneaker, make sure it's clean, and we send out to them. And then from there,
for example, we use it for customer sentiment before human styles will have okay with 1000s of a
customer who is most likely to churn. We need to have a human to write down all these guys angry. So
we probably have to give them bonus item. And now we simply use AI say, okay, read all of the text
message before and email this information and review and tell me which customers should I give bonus
item, otherwise they might be churning. So number one, looking at the value. Number two, looking at
your workflow, where you can use AI to optimize.
Adam Outland (24:38):
Wow. So there's so many different ways that you can you have data sets in a business,
and there's ways that you just shared that I didn't even think about how you can take that specific
data set and have aI help you, like you said, optimize and make better decisions, versus having a
bunch of humans with tally sheets and doing the homework themselves. You know, I might stick with
you on this next question then. What are the ways that you see AI enhancing the capacity for
marketing and driving web traffic?
Anya Cheng (25:05):
Yeah, so tap on the SEO things. We recently won American Marketing Association excellent
in marketing award and with other finalists, I including Netflix and Google Pixar. So how we do is
we got 10,000 10 million impressions for free from chatgpt. Now, if you search chatgpt For two years
old startup, if you search chatgpt 2025, men's fashion trend, the answer isn't from GPU. Is from
Taylor how? So we start looking at the same thing as the old way to do SEO. Start with a user
journey. When will user asking what questions, right? So for example, oh, I'm going out dates, and
what kind of office should I use and asking those questions? So we start with human generating some
of the outlines. Then we use AI to generating the data on the contents, and from there, most
important part here is AI human. Ai human like what productor mentions. So AI generate content. A
human stylus will add inputs from there, then you send it to a customer full of styling, no and
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customer will provide feedback because we are a subscription business, say, $100.10 codes per month.So customer tend to give feedback right away, wanting to make sure next shipment is better. So the
customer feedback come back to the content, and now we put those content on the website, so that
website generating more traffic coming to a site, and again, they come back to our loop that we send
the review to the customer, etc. So AI human, AI human, the most important thing is AI enhance your
capability, but it's human to make sure it has empathy, authenticity and relevancy, so both to
combine. That's how we were able to get 10 million impressions for free from chatgpt.
Adam Outland (26:57):
I love it. And just maybe a tag on question, do you feel that since you've started
your journey with Taelor, has AI gotten smarter at optimizing from the AI human feedback? Do you
feel like it's continuing to develop its own algorithm and getting better and better at predicting?
Anya Cheng (27:13):
For sure. And that's why nowadays, like what G3 mentioned, is extremely important that
you have your own data set. What does it mean? For example, my dog, my friend, is a doctor, is
dentist. You just have one small practice, but he has been doing that for 10 years. Means what he
has the data of the image of teeth issues that other people don't have for teeth issue for people
who live in Silicon Valley, right? And I'm sure all of you guys, even no matter how big, how small
your business, you have some unique data that no one else has. And now is your era, because this
era, different from before last generation, is algorithm, Google, this giant box, black box, you put
something, someone rent high so you need very, very, very expensive engineer in the past. So the
last era was all about big company. But nowadays everyone will use large language. Model means what
everyone use? Open AI, Elon Musk, AI, Mark Zuckerburg's AI. None of us are going to build that. But
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the goal is, you bring your own unique data set. You sit on top of that. So as they grow, you alsogrow, but you are always one step ahead. So nowadays, building AI is easy. You will need once kids
outside of a college school, out of college, in a week or two, can build something. But most
important is what problem you're solving if you have unique data that other people cannot repeat
from you.
Adam Outland (28:44):
Well said, so I saw Dr Amy's gears turning as we're talking. She's like, how can we
even adapt more to that? So, Dr Amy, I mean, let's talk about a certain data set in person that you
work with. You know, in the documentaries on Blue Zones and regional zones where there's a
heightened lifespan, we're talking about retirement, right? So one of the key factors scientists
have identified contribute to longevity is community, right? And the absence of community is a pain
point for health issues. So when we go from AI to talking about the human component, the human
touch, we're seeing there's a scarcity of community. There's a scarcity of human contact. Is that a
pain point for the retirement market that you inadvertently serve?
Dr. Amy D'Aprix (29:21):
It's a huge pain point. And first of all, I should say I love AI and I love the AI
human, AI human. So we use AI in my business, you know, we see it as something that frees people to
be able to have more of the human connection. So it's not AI or human, it's both combined, right?
That's what we're talking about. And yeah, the lack of community, we know, is a huge issue for
people as they age. You know? We know that people who have, we call it social support, who have good
social support as they get older, live longer, live healthier, both mentally and physically, are
less apt to end up in a nursing home. Heal quicker from illnesses, and the latest research shows it
has a protective factor against Alzheimer's disease. So it's huge, and we know it's a big problem.
In in the UK, they have a minister of loneliness. I don't know why they didn't call it a minister of
connection, or something a little a little happier than a minister of loneliness, but the last time
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I was over, they had in the subways, I saw these signs for have tea with the with an older person inyour neighborhood. You know, it's this idea of connection. So this, for us, who are professionals,
there's a huge opportunity here. Again, it comes back to that connection. And how do we be part of
the community, community as professionals, not just in our personal life both. You know, one of the
studies that I love was done by Vanguard a few years ago. And I quote this a lot, because I think
this applies across professions, but if you're in any work where you need to build trust with your
clients, Vanguard interviewed high net worth clients and asked them what created trust in the
advisory relationship. And there were three things, functional trust, ethical trust and emotional
trust. So I'll let you think about what was the most important in that functional Trust, which means
your ability to do your job, 17% now it doesn't mean it's not important. It's table stakes. They
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assume, if you're in this position, you're doing that the second was ethical trust. And ethicaltrust came in at 30% and the remainder, 53% was emotional trust. Now think about what that means. So
when we talk about, again, getting great data, which people, you know, advisors need this, and
helping, you know, put the plans together, that frees you to have the conversations. And this goes
across whatever industry you're sitting in here, you know what, whatever your connection is, I think
we keep saying, how do you use AI to free you to then have more time to interpret that and to apply
that to the person you know? Another thing I'll share is that if you look at who is unhappy with
financial services, it tends to be women. The studies show that about 70 to 80% of the time, if the
husband dies first, the wife finds a new advisor within one year. So I work a lot with advisors just
to close this gap, because think about the opportunity here. You know, do you want to keep
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prospecting new people, or do you want to keep the people you already have? So when we talk aboutwomen and how do you keep women clients? It's making all that data that you're getting from Ai
relevant to what's going on in people's lives. I say that every life transition has four
implications, practical, emotional, family and financial, or financial, legal. Well, as when I'm
working with advisors, obviously, their lane, their sweet spot is the financial but your client
lives in all those other areas too. Life and money go hand in hand, but it's up to the advisor to
bring that together and make it relevant for the client and be able to go to where the client is
express empathy, as you said, and I always say empathy is just I see you, I hear you, I get you,
that's all it is. I get you, and then be able to segue to the business conversation and go back and
forth between life and business. And this is where I believe AI. And again, it's not a threat to the
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business of advisors. It frees them to do what builds the relationship that keeps the clients, thatgrow the business, and that has people refer and say this advisor really got me, and they worked
with me as I moved through these different stages of my life.
Adam Outland (33:50):
Well said. And I think, just to give a little context, you know, you're a thought
leader in the space, you get asked to speak about this continuously. You know, with life bridge
strategies itself, how, like, what are some of the functions of your program that equip advisors to
do a little bit of that work?
Dr. Amy D'Aprix (34:05):
So we have two offerings. One's called trusted advisor of choice, and in that, it's
an eight module program. And we also were impacted by the pandemic, and we came out just at 2020,
and our program, we were positively impacted. I hate to say that, but we were because our training
is bite sized videos with lots of resources, and then group coaching after each of the eight
modules, and it's through the lens of life transitions and teaching advisors how to better
understand the practical, emotional family. And then we teach a trademarked process for how do you
go between the life and the business conversation? And what came out of that was we saw a gap that
once advisors got great at having the conversations, they said, Okay, so now I'm good at empathy,
and I get what's going on. I could use some resources on the life side, not just the financial. So
just this spring, we came out with life map. Which are robust resources for clients on the life side
(35:03):
of transitions that they can only get from advisors, and that we have designed it so it deepens therelationship between client advisor without taking more time for the advisor. And so we keep looking
at where's the gap that we can help advisors deepen the relationship, meet the client's needs and
grow their business. And those are the two offerings we have right now. And I'm sure in a couple
years we'll be able to tell you about another one.
Adam Outland (35:29):
I love it. Love the partnership, and we're gonna stick with this, this human
component. Dave, so there's an author and award winning journalist, Sebas younger. He wrote in his
book called tribe, that never has it been so common in human history to live in the most populated
city and yet feel so utterly alone with evolution of technology, community and the human touch. But
you know, becoming more and more scarce. How can business owners and individuals use the scarcity to
their advantage?
Dave Brown (35:55):
Yeah, just wait a second. Let me type that into chat GPT to get you an answer on that
one, I joke, but it's like there is a threat to that. There really is, like a threat to some, some
of the humanness going away. There's a connection of mine allowed his daughter to have a
conversation with one of the one of the bots, like it was grok, grok and about, and she just started
talking to it. He opened it up. Did it while they were driving home, 10 minute long conversation,
and she started telling it about her day and friends and some of the interactions. And it was, it
just kept going, and the voice got more compassionate over time to connect with her. So it was one
of those things where it was like, Whoa, like, okay. But it also opens up for him to have a
conversation with her about human connection interaction, which is great, because we need to be
ahead of this stuff. I mean, I don't know those you have smaller kids whenever you watch them play,
(36:51):
like YouTube kids or whatever. Unbelievable, how those those algorithms give them exactly what theywant when they want it, right? And so it's like, that's not the real world. We all know that, that
we're growing up, so just that, that being hypersensitive to that. And I always say this about our
industry, how important connection is. And we learned this, Emmy and I from our marriage coaching
that we do, but our Chris, our guy, said years ago, he said me, said, Dave, if you want to be the
most efficient you it's about being connected with your spouse, that's how you become the most
effective and efficient you. And that hit me, and it's really helped me in the most important
relationship I have. But I've also taken that principle and tried to apply it in like my
relationships, people that I work with, the people that I'm friends with, because I think there's
three components to the next generation of those of us that are in sales and that are trying to move
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our business forward through growing the revenue side of our business, people buy from us. We've allheard this before, because they like and trust us, right? We all know that there's a third part,
though, is connected. They like trust, and they need to feel connected to you, and that's something
we get to do. That's not anything that a computer program can enhance AI is a thought partner. It's
not a replacement of it at all. And I mean, so many pieces of the connection piece I could talk
about, but it's our job. This is the evolution of strategy, right? Our job as leaders in our company
is to stay ahead of of what's happening and whenever things are going down in the marketplace, we
almost need to protect our business from that, and protect our people from that too. And we need to
level up in this game, because it's not going to put you out of business. There's a lot of that fear
that's going around right now that's just hype. It's not but you know what it will do is it's going
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to enhance other people that are competing with you if you don't choose to embrace it, and that,that's the game that I'm trying to stay ahead of. And I mean, so in so many ways, but the thought
partner piece, like we have, one of our consultants, created an AI agent for yourself to basically
contrast your way of thinking, flux. And as we're reading through fluxes characteristics, flux knows
who he is based on all of his personality profiles he's ever taken and then we created one that was
the antithesis of his personalities. And we're reading through these characteristics because this is
going to be a thought partner of his in everything he's doing this, flux is going to allow him to be
a better coach, because it sees different angles, right? It gives them awareness of how he he
doesn't see it alone. So that allows, that enhances his human connection, that is, enhances the game
that he's playing constantly and that we all want to play. And I'm trying to encourage many of our
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people to be playing that game as well. That's something that I need to be staying ahead of, too. SoI've got many, many other examples I could do even our fantasy football draft Adam that you're a
part of, I might have used AI too. Is that why you're winning? But you can give it situations and
talking points and, of course, context and past history, but it's something that's allowed me to
kind of have more, more of a connection, and I hope to do that throughout our business.
Adam Outland (39:57):
Since this is also one of the tools we've chose and you use with Level AI, G3 can you
comment on this? Like, how can level AI and AI in general to tag on to what Dave said, help elevate
those human interactions we have?
Gayathri Krishnamurthy (40:10):
You know, Dave, you hit it on the nail. It's not the AI which is going to
take your job, right? It's the person with AI who's going to take your job, right? So, and I'm gonna
echo this panel's thoughts, just you need the human in the loop, right? So thinking about like,
maybe you know you're flying, and you know you have a co pilot, so you've got the speed, but you
need the control. So I think that's the way I look at AI. So you you get the speed, and the controls
that you put in are really the guardrails and you choose to use what you want to use. For example,
I'm not going to lie, but I put these questions in chat GPT for my panel, and I was I read through
two and then, like, no, sorry, pass. This is not going to cut it. I want to be authentic, and I know
what I'm saying, right? So really, there's this fine balance, but I always consult. So it's like you
consult and take the best out of anything that anybody has. That's a common human psychology, right?
(41:12):
So you take ideas and take the one that works, so that's going to apply for AI, too. And the thing,again, is like the speed and the insights that it gets is so invaluable. All of us here know how
fast you can do things. And there's this new Moore's Law of AI, where you know, every seven months
the tasks that an AI can do, just say, for example, right now, it's like 10 hours of tasks that a
human can do. The AI can do, it keeps going at every seven months the speed is doubling. So anyways,
non geeky side, it's all about like AI is going to be faster, more powerful, and it's up to us to
kind of leverage the power. And in our example, you know, from a coaching perspective, classic is,
as a coach, you want to spend more time coaching, not looking at data. So in our in our platform,
for example, you could score, automatically, score any call in multiple parameters, right? Empathy,
CSAT, this and that. But what it gives is like a quick way to kind of look for that specific areas,
(42:18):
versus like spending, instead of spending like 80% of your time looking for data and finding outwhat to do. You're going to flip that. You're going to use 20% or less of time to see what's going
on. Then you're going to use that 80% of time to really get things done. So that's going to be the
big change that I'm looking at. Like, how can you really, you know, drive value of your your thought
partner to me, I always view AI as that thought partner who sees, like, really, really strategic in
thinking, but it might not have the context right. So you got to kind of map it out. So that's how I
see the see the map.
Adam Outland (42:57):
So this will be a question for you G3 and Anya. So maybe toggle back to G3 for this.
What are some of the current limitations of AI? And you're already commenting a little bit on this
right and how chat GBT doesn't always help you. For the questions, what are some of the aspects that
the market has overhyped or over promised and and maybe not yet delivered on?
Anya Cheng (43:17):
I think something not yet delivered, but I think it's something that we will see is look
at your own chatgpt experience. When I run Nashville, I no longer ask Google say best restaurant in
Nashville. I say, Hey, I just first time in Nashville. I'm from San Francisco. I don't eat spicy
food. My husband is tech alone because he said he also want to help out. Where is he here? Oh, wow.
He said he also want to help out. And unfortunately, he's, unfortunately, He's a chef, and so have
to be something delicious. Well, what would you recommend, right? So you give a lot more context,
right? Give our context. The same thing for our customer. When they use our service, they are not
just give me the best outfit. They say, Oh, next week I have two meetings with the board meetings,
and then I go on a client meeting in Philadelphia. In their meeting, I want to feel fit in or in the
next meeting, when I go to meet with the CNN company, then I want to feel that I'm standing out
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right. There's a lot more context on what you want to achieve. So that's where the differencebetween now in the past, when people are searching, people are looking for people give you a lot
more information mentioned, and what it means, means for back to the previous point, it means you
need to have company, have to unique data to serve the answer for people to solve the problem. You
are no longer just trying to get best keywords there. Restaurant, Nashville. Restaurant Nashville.
No, the keyword thing is that now it's about, can you solve their problems? For example, in my
business at Taylor, we have a lot of unique data. For example, when people are. We know their true
preference, because when you go on Amazon, where Macy's to buy something, it tend to be not just
because you like it, also because the price tag, right? Oh, it's $1 perfect. I like it for sure,
right? So, but now with like Netflix, when go on Netflix, show, we watch a show isn't because the
(45:18):
show is on discount. You do like the show. The same thing with our model, we are memberships. Sothen we know customer true preference. Or AI only know the past. Ai doesn't know the future. So in
our business, we work with 300 fashion brands, marine layer, Johnson Murphy, bonobos, you name it.
So then they are designing something for the next year's collections. So we know the future. Or, for
example, we buy two company. They have 10 years of styling data led by human style. This in
Hollywood, so we they were wasn't able to scale, so we bought their data set into our AI. Or we are
rental company, so after people return a close, we know their true quality. Johnson Murphy, you say
this pen will lease 50 times. Watch, no, I can tell you 20 times you fall apart, right? And have
this unique data that no one else has, and it's on me to turn this unique data into the answer to
solve the customer's problem.
Adam Outland (46:15):
So now everybody's gonna put into chat GBT very specific requirements to know where
you're going out on Broadway tonight, and it's going to tell you the exact bar. A lot of context. G3
do you want to comment a little bit on where AI is a little over hyped, maybe where they've over
promised and have yet to deliver?
Gayathri Krishnamurthy (46:32):
Yeah, I'm going to echo anya's point, and it's all around the accuracy,
right? There's a lot of hallucinations still going on, and even the best models out there, they are
probably 80% maybe accurate, especially without the context, it'll be even less. So the more and
more that you can point all your data together, have a feedback of the data coming in continuously,
you're going to refine the models. So I feel like hallucination is so real, however much we're going
to fine tune, and there's so many variables, and it's going to, it's going to, it's going to be
evolving as the models evolve. But hallucination is real, so giving the right context, and I think
there was so many of them, which happened recently, there's an airline where somebody asked for a
refund, they gave it, and, you know, the chat bot was not supposed to give it. So really, that was
because we didn't point to the right data, right? So we didn't point to the refund policy and so on
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and so forth. So where is hype? This the hallucination part, which could be solved if we point thedata. But here's the big, big, big, interesting report that I read from MIT, 95% of AI projects
which were done are a failure, and the reason was data like, you know, not pointing the data, not
getting the right data out of multiple systems, because all the systems are talking to one another
order systems talking to pricing, is talking to CRM is talking to all of those. So really, getting
that problem solved is important, and having that common data layer and training it over and over
again, I think that's going to be so critical for the success of this. And I think we're also
inspirational, aspirational about, oh, there's a bot who's which is going to go talk to another bot
and get all my stuff done, which is still there. I mean, there's, there's a lot of research going on
on agentic, AI, where there, you know, one bot, let's say, hey, I want to go to a vacation. Can the
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bot do all sorts of planning as well as go and make those reservations? Yes, they are building thosesystems. But I think what we're again losing sight of is the strategy, the vision. Everything is is
available today, the technology is available, but then as you start implementing and putting things
together, there's going to be failure points. So I think having a good proof of concept, we have
been in some situations with our clients where they had some of the basic data and really old on
premise systems that you can't even pull that data. So these are very practical challenges that will
kind of limit what you can do. So, so I would say hallucination, you know, data limitations, the
integration part, security, is still a challenge. I think we have to, we have to, really, you know,
think about how we were reluctant to put stuff in Gmail and Google, and now we're fast forward.
We're like everything is being used by everyone, so especially the huge liability issues in people
(49:49):
who are in finance insurance. So really, having good guardrails and the advancement in terms ofsecurity, have to keep up with this. I. Because, the way, from a technology perspective, this is a
different kind of a thing that we're trying to do right, like so AI operation security is still
evolving. So those things where I'm trying to go is technology is one. There are so many other
surround elements which have to kind of AMP up to security, data integrations, all of those from
him, and also the change management that's also huge. We've had clients where we put a lot of AI
tools, but then the option is not there because we are used to doing it a certain way. So how do you
change behaviors? Right? That's a very real problem. So I think the limitation is right there. In
terms of HR, change management, technology, operations, all of them have to sing this from
Adam Outland (50:54):
Thanks, G3. Dave, back to you real quick. I know you've already mentioned flux as like
example of a use case for AI. And what other ways are you engaging with AI as a support technology
as opposed to a replacement technology?
Dave Brown (51:09):
Yes, and as I was listening to G3 talking to Anya, this was something that around AI
that I got challenged with about a year ago, and I would remis if I didn't put the same challenge
out to each one of you, because we're all business leaders. You all know it by now. Everyone's
alluded to it. AI is evolving faster than any creation ever has in history, right? Two, 50 million
books, it's already consumed. So the information out there. But where are you at in this evolution?
Like that was a question posed to me, where am I at in this evolution? We almost can't wait any
longer, because there's this learning curve that's going to happen. The learning curve keeps getting
farther and farther away from each of us. Away from each of us, doesn't it? And getting educated, we
got to start now. It's almost getting to the point, and this is something that I might have even
heard this morning. You're getting to the point where you can't just say, Oh, I'm so glad I got into
(51:55):
our industry, because it's not affected by AI or, you know, I'm glad it's never gonna replace me inthe work I do. Right? That might even be something I ran into. So if you're comfortable with status
quo and waiting for somebody to handle AI for you, I would just caution you, just jump into the
pool. I would, I'd caution you on that, because as I've jumped into the pool, it's allowed me to be
that better leader. It's allowed me to connect a little bit better with people. So one of them, flux
was one of them, another one. I know this is more of a personal one, but it's, it's real. My son,
he's got ADHD. He's got something called a ring of fire brain. If anybody's ever heard of this
concept, but I am growing as a dad, because the information that's out there on the Ring of Fire
brain and how to react to it. I mean, it's firing all the time, triggering constantly, and I'm not a
very real I'm not as compassionate. I'm more about efficiency and compliance instead of connection,
(52:53):
sometimes which I need to get better with. I've asked it to give me a perspective from a counselorpoint of view, with a certain context on how I could have reacted better in this situation, and it's
helped, and it's starting to help me in that area. A friend of mine just this some mediation. He's
going through with a fortune 100 company. He owns a nine figure great business, part of my C 12
group, and it's a logistics solutions company. He has typed in the lawyers he's in mediation with
and their personalities and the stance, the arguments that they want to make as a business, and
having them go back and forth and go at it, which has allowed him to really have some great
strategy. The nine or 10 lawsuits that he's in with his big business, all of them are still alive in
the settlement. Numbers keep getting bigger and bigger. Shocker, right? Because he's kind of playing
the game inside of his head beforehand. It can give you insights, and that thought partner piece
(53:46):
that allows you to do it and anything's available. So what I love, what you said you three, I mean,the amount of data you put in, that's what it's going to spurt back out. But also be aware of the
data that you want to be putting out there in the world. Because you all have heard of some of the
public stuff that's gone on. It's gone out about businesses. But also you can verify the
hallucinations, like, fact check this for me, that mediation example, there was a couple of times
when I was talking to the guy in mediation, he was like, I fact checked that. I just said, AI, hey,
give me your your pieces for this. And it said, Yeah, that one's made up. It'll tell you what it's
made up, or it was who's hallucinating. So just some some insight there, I would contend it can help
you in any area. And it's so customized, isn't it so cool when you get some
that's so unique about this platform, because now we can go it's almost like we listen better. When
(54:37):
it's customized to fit us in our situation, we learn quicker. So yeah, I would say those would be acouple examples, and I'm trying to look for more, too, all the time.
Adam Outland (54:45):
Dr. Amy, did you want to tag on real quick?
Dr. Amy D'Aprix (54:47):
I just think I want to make the last point that I hope we use AI as a way to do all
those things more efficiently, so that we have better human connection. Because, you know, we all
know the proverb. It takes a village to raise a child. When I do caregiving workshops, I'll say it
takes a village to care for an aging parent, but the truth is, it takes a village just to get
through life. And we are that village for each other, and the only way we can be that village is
when we work on deepening our relationships. So I see AI as a huge opportunity to free us so that we
can deepen the relationships. And I bet there's no one in this room that would argue that the world
needs more peace and better relationships. So let's use AI as a tool to free us so we can be those
people in the world.
Adam Outland (55:36):
Love it. So you've heard from four thought leaders in this space, and I think they did
a wonderful job. You know, one thing that you always look for and identify are values that you can
duplicate. And I think each of them, you'd find that they have an insatiable curiosity for this kind
of work, and it's probably a big part of what's put them
get this sense of their insatiable curiosity, and it's such a common thread, when you interview
founders and fortune 500 CEOs, is this common thread? And I think if there's any takeaway today, I
hope it is also that you can take that insatiable curiosity back and put it around technology,
instead of doing the ostrich method, which is bury your head in the sand and hope it all goes away
by doing that, I think we'll stay advanced and get ahead of the game in every industry you're in.
But thank you to all of our panelists today for sharing such wisdom with us. Let's give them a hand
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of applause.
Emcee (56:34):
Dave Brown, G3, and Amy, Anya, and Adam, A3.