Latest / Networking Unleashed: Building Profitable Connections / Networking Unleashed: An Interview with Saurabh Kakkar and Michael A Forman, Professional Speaker

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Networking Unleashed: An Interview with Saurabh Kakkar and Michael A Forman, Professional Speaker · Networking Unleashed: Building Profitable Connections

0:14
Welcome to Networking Unleashed, Building Profitable
0:18
Connections. I'm your host, Michael Foreman.
0:21
AI is changing banking, credit decisions, and
0:25
how organizations operate. But here's the bigger
0:28
question. Just because AI can make the decision,
0:32
should we always let it? Today's guest is taking
0:36
us inside the move from AI experimentation to
0:40
real -world implementation. where trust, transparency,
0:45
judgment, and accountability matter just as much
0:49
as the technology. Because the future of AI isn't
0:53
only about what machines can do, it's about what
0:56
leaders are willing to be responsible for. So
0:59
I would like to introduce to the podcast, first
1:01
of all, welcome. And second, I'd like to welcome
1:04
Sonny to the podcast. And if you could just give
1:08
me a brief, a cliff note version of how you got
1:12
where you are today. Absolutely. First of all,
1:15
thank you so much, Michael, for giving me this
1:17
opportunity. This is wonderful and a very nice
1:20
setup. So I really appreciate that. Just to give
1:22
you a very brief intro about myself, I can call
1:25
myself somebody who is lived through the banking
1:28
space. I'm part of financial services for almost
1:31
20 years now. I've worked with almost all the
1:34
big banks across the world. Very fortunate about
1:37
it. In fact, my start of my career started with
1:40
a lot of banking consulting business. So that
1:42
allowed me to see various aspects of almost all
1:46
the banking network. What we have realized till
1:49
now is that from an entire banking space, data
1:53
is the key element here. And as we have always
1:55
progressed through our start of our year Y2K,
1:59
when the computers came in and there was a paradigm
2:01
shift in how we saw data, we are now experiencing
2:05
something really big, which is the AI paradigm
2:08
shift. And that's where I'm here to give my experience.
2:11
I myself lead the AI space within my space, within
2:14
my corporation. What's happening right now is
2:17
nothing new. We always saw elements of it in
2:21
the past as well. If I take you back from how
2:24
it all started, it literally started in 1960.
2:27
There are instances and theories and research
2:30
that can literally tell you that AI is not a
2:32
buzzword or a new word. It was always existing.
2:36
It's just when we work, there are new mindsets
2:40
around that. And today's mindset is AI. But in
2:43
my personal opinion. A lot of people don't understand
2:47
AI the way it should be. So just to give you
2:50
a little bit of my background here, that I have
2:53
gone through those aspects of banking data, wherein
2:57
it was literally more like a manual way of working,
3:01
then came the computers, then came the analysis
3:04
on the part of us getting more and more into
3:06
depth of data. But today... the depth of data,
3:10
the amount of data that we deal with has tremendously
3:13
increased. So I'm here to basically share my
3:15
experiences and my analysis and my judgment around
3:19
how things are placed today versus how they're
3:22
going to be progressing in a near future. Hey,
3:25
great. That was a great segue into my questions
3:29
because I'm going to be all about you, all about
3:31
banking and AI, and we'll see where it goes.
3:34
AI can analyze someone's financial history in
3:38
seconds. but it can't truly know that person.
3:42
As AI plays a larger role in banking and credit
3:46
decisions, how do we make sure we don't lose
3:50
the human being behind the data? That's a very
3:54
good question. And the way I say it is in our
3:57
space, in the space of analytics, I'll say even,
4:01
and I'm not going to even restrict it to banking
4:03
space. It's basically across the board. Data
4:07
is as good as what you put in versus what's coming
4:10
out, right? So it's basically garbage in, garbage
4:12
out. If you don't have control over your data...
4:15
the outputs will be absolutely non -trustworthy,
4:18
right? To address your question, yes, there is
4:21
a huge element of human intervention. We call
4:23
it HITL, which is human intervention aspect of
4:26
the data. What we really need to understand is
4:29
we need to use AI to automate things. And there
4:32
is an element of efficiency here. That's where
4:35
I was like trying to mention in the beginning
4:37
of my call as well, that a lot of people see
4:39
AI as just a magic word. It is not. It's basically
4:43
something that's allowing you to do your work
4:46
more efficiently at this point of time it is
4:48
giving you more dimensions around your work it's
4:51
allowing you to have more thought process which
4:54
you could not do or even if you could do you
4:56
knew that it would take you a lot of time and
4:58
an effort but right now with ai those things
5:01
have become much more achievable and they are
5:04
at your service that basically available to you
5:06
now from a human intervention point of view absolutely
5:10
true there is an element of deciding what data
5:14
is how is the quality of the data i will further
5:17
elaborate in my discussion later on this podcast
5:19
there's a concept of data hallucination which
5:22
really means what is data looking like is the
5:26
data appropriate have you vetted the data is
5:28
it a standardized format of data or not so there
5:30
is there's a lot of element where a human needs
5:33
to participate and understand how data is looking
5:36
before we even start using it i hope that addresses
5:39
your question Yes, it does. And you've answered
5:42
actually a lot of questions on my podcast. I've
5:46
had a lot of AI developers, AI, people who use
5:50
AI, and you just really put it all in a nutshell.
5:54
And you explained AI is a tool, but you need
5:58
to put in the human element to get the right
6:01
answers. It's very important what you had just
6:06
said. I hope everybody is listening because what
6:09
he just said is so powerful, so impactful that
6:14
this is the way you truly should use AI. Okay.
6:19
AI in banking, trust can take years to build
6:24
and seconds to lose. Does AI change how leaders
6:28
earn trust or does it simply raise the standard?
6:33
Again, this is very correct when you're asking
6:36
that question. ROI is, in my opinion, and a lot
6:40
of research actually also validate that, is again,
6:43
even beyond automation. It's basically something
6:46
that needs to be addressed from how does it make
6:49
your bottom line grow? It's a concept of ROI.
6:52
And this is, again, my research is basically
6:55
making it more elaborate. Just to digress a little,
6:58
I have currently published a book. Specifically
7:01
on details of this analysis, there are two patents
7:04
as well that I filed in Germany, wherein I spoke
7:07
more about how AI is shifting the paradigm shift
7:10
for our AI leaders. Basically, what's going on
7:13
is, from a leadership point of view, we want
7:18
to create efficiencies here. But at the same
7:20
time, efficiency doesn't mean we just automate
7:23
a task which was always never impacting our profit
7:27
situation or reduction of cost. What we are right
7:30
now understanding is we need to first perform
7:33
a thorough audit of any organization or maybe
7:36
like a department and understand how the process
7:39
is laid out currently and what are the areas
7:42
that can actually be highlighted through AI and
7:45
potentially improved. If that potential improvement
7:48
creates an ROI impact, that's a leadership proposition.
7:52
That's where leaders are interested. That's where
7:54
they are trying to invest. I'm seeing that a
7:57
lot of people... are not really doing it and
8:00
they're jumping the ladder and they're basically
8:01
trying to copy somebody and say, oh, somebody
8:04
did this. Let me also adopt that technology.
8:06
It's really not in that mindset. It's a very
8:09
organizational niche kind of a mindset. We need
8:11
to understand how an existing organization is
8:14
set up currently and if I those areas where AI
8:17
brings in more value proposition. do a thorough
8:20
testing around it, create POCs around it. And
8:23
then once something is successfully giving you
8:26
a value proposition, then you see it from an
8:28
organizational point of view. There are a lot
8:30
of aspects that I've also mentioned in my book
8:32
and also I try to explain in my patents as well,
8:36
that a thorough analysis is needed. Reason being,
8:40
you will come across a lot of areas wherein...
8:43
Something which was being created like a cost
8:45
preposition suddenly now looks like a profit
8:48
preposition for that organization. And they can
8:50
absolutely show that impact in their ROI analysis.
8:53
Very good. Very good. We're moving from experimenting
8:57
with AI to putting it into real business decisions.
9:02
At what point does AI stop being a technology
9:08
decision and become a leadership and values decision?
9:15
I think my discussion just now touches that aspect.
9:18
It did. Anything you want to add to that, though?
9:21
Anything? Because you really covered it. But
9:24
just give me a shorter version of what I just
9:28
asked. Absolutely. See, the answer lies in not
9:31
just identifying an automation aspect. The answer
9:34
lies in unifying aspects which can be automated
9:37
and create an ROI increase proposition. It could
9:40
result in increase in profits or a reduction
9:42
in cost or an ability to increase your business
9:47
scope. That's how I will put it. If that's not
9:49
happening with your AI initiative, you have literally
9:52
just converted a process into an automated process
9:55
without any impact. Very good. Very good. If
10:00
an AI system makes a decision that is technically
10:03
defensible, but feels fundamentally unfair, who
10:09
should have the courage and authority to challenge
10:12
it? Absolutely. So again, this whole question
10:17
lies on... how this process was implemented from
10:21
an AI point of view, what were the objectives
10:23
they were trying to achieve. All those things
10:25
should be set up before this initiation needs
10:27
to happen. So we compare the output of our process.
10:30
Again, we created a more efficient process, but
10:33
the expectations around that process needs to
10:35
be already laid out. It needs to be organizationally
10:38
validated. And if they are not meeting that purpose
10:41
and it's only showing efficiency, in my opinion,
10:44
that is a wrong move. Yeah, absolutely. And by
10:48
you preparing to input into the AI, it's not
10:55
going to be the first time out, right? You put
10:57
a prompt in and you say, no, that's not what
10:59
I wanted. You put another prompt in and you tailor
11:01
the prompt to what you get to the results and
11:05
you say, okay, that's what I'm looking for. And
11:08
then you can put it in. But it takes that human
11:11
touch, the leader, the manager of that. To know
11:16
that and to implement that. That's correct. That's
11:20
correct. And that's where the concept of AI modeling
11:22
comes in. And we can always talk about it. As
11:27
AI leaders access, as AI gives leaders access
11:33
to more information, could it actually make curiosity
11:36
and listening more valuable? And are we at risk
11:41
of knowing more about people while understanding
11:44
them less? Great question. Risk is always a subjective
11:51
area, in my opinion. I see it in a more positive
11:54
way. AI has literally allowed us to create absolutely
11:59
different level of dimensions. In my opinion,
12:02
that calls out for being able to provide more.
12:05
In my opinion, that calls out for being able
12:07
to... create more value prepositions for our
12:10
audience, for our clients, for our stakeholders.
12:13
I am seeing it in that aspect. Like I said, I
12:16
was mentioning in my earlier part of my discussion
12:19
as well, AI has allowed us to do things which
12:22
needed months into days or even minutes. That
12:27
has allowed us to now start focusing on greater
12:30
aspects. trying to create products and values
12:34
which were never thought of or were never like
12:37
the priority because of the cost preposition.
12:39
Everything at the end of the day is a cost -benefit
12:41
analysis. AI, one aspect, and that's why I'm
12:44
touching the concept of ROI again and again,
12:46
is the tool that you can use to create that cost
12:51
-benefit analysis much more faster, efficient,
12:54
and more dynamic ever before. As you said, AI
12:58
is a tool that you can use. It's a quiver in
13:01
your arrow. It just helps you get rid of the
13:04
minutia, take care of all the little stuff that
13:07
would take months to achieve, and then you can
13:11
automatically go to the next step, right? Absolutely.
13:14
So it saved you all that time. Okay. What happens
13:18
to organizational culture when employees begin
13:22
wondering whether they're working with AI? or
13:25
quietly being evaluated and replaced by it, what
13:30
responsibility do leaders have in that conversation?
13:34
That's a problem that we're facing currently.
13:37
The way I see it, AI is not replacing jobs. It's
13:41
replacing people who are not adopting AI. And
13:43
that's where people are getting confused. If
13:46
your work can be expanded and you can make yourself
13:51
visible as somebody who can do more because now
13:53
you have AI, you're very much a... absolutely
13:56
important portion to the entity. Reason being,
13:59
the entity has already invested in you. You know
14:02
the data, you know the environment, you know
14:04
the culture. See, AI is not a magic word. Everything
14:08
also needs to be implemented. It still needs
14:10
to be adopted. It needs to be absorbed in an
14:12
organization system. It still comes up with own
14:15
technologies, which are still products that needs
14:18
to be adopted and implemented within a particular
14:21
organization. And for that, they need people
14:24
who are most familiar with it. So if you are
14:26
somebody who is absolutely interested in adopting
14:30
AI technology, interested in learning that space,
14:33
you become an ideal candidate for that matter.
14:35
What I'm seeing is people are, again, seeing
14:38
it from a point of view of a job reduction, in
14:41
my opinion. And there is a lot of studies here
14:44
also. There's a study from McKinsey that actually
14:46
already explained that these many jobs will be
14:50
gone, but these many will be created. Because
14:52
like I said in my earlier pitch, We are seeing
14:55
new dimensions. New dimensions will result in
14:58
additional products and they will need more people
15:01
to build those products. So in my opinion, from
15:05
a leadership point of view also, my encouragement
15:07
to my team is learn AI, understand how it can
15:11
benefit our current process. We should not be
15:13
shying away from showing it to the world. And
15:16
then we basically establish ourselves as a more
15:18
mature organization. Yes. And everybody who...
15:23
embraces that AI in the workforce, they can say,
15:29
okay, this is doing my job. It will do your job,
15:32
but then you expand your job. You expand the
15:35
description of your job, say, okay, I can do
15:37
this with AI, but I can also do all of this and
15:42
keep the job. Way back when with the industrial
15:46
revolution, when cars first came in, and they
15:51
replaced all the horse and buggy and all the
15:54
iron the black iron smiths and everything else
15:57
they lost their jobs but the auto market created
16:00
all sorts of new ones correct it's pretty much
16:04
the same thing but you have to adapt and you
16:07
have to learn how to adapt and i think just to
16:09
complement to that wonderfully explained by the
16:11
way Beautiful. And that's a very good analogy
16:14
there. Another great analogy is Y2K. When things
16:17
were being done manually by writing stuff on
16:21
the books, look what happened. Computers came
16:23
in and you were like, oh, now we don't need these
16:25
many people. Have we really seen that? No. I
16:28
think the jobs have expanded tremendously. The
16:30
economies have literally grown from there. Absolutely.
16:34
And actually, that's good. I'm going to have
16:37
to use that one in my next, I run a networking
16:40
meeting every week for businesses to all come
16:44
and exchange ideas. I'm going to use that. Okay.
16:47
So I'm going to steal that from you. Okay. The
16:50
people around the leader influence how they think
16:53
and what they question. How important. Is it
16:57
for executives implementing AI to build relationships
17:01
with people willing to disagree with them? The
17:06
answer lies in analysis. It's not about disagreement.
17:10
It's about answering the next step. If AI has
17:13
allowed leaders to see more, people who are working
17:17
for them needs to also have that thing addressed
17:20
in using AI, right? So basically at the end of
17:23
the day, and this is a very, very simple discussion
17:26
here. are not changing the infrastructure. We
17:30
are not changing an organization. What we are
17:32
changing is way of doing our work. What that
17:35
really means is the questions and the data and
17:38
everything that we were working on still remains
17:41
the same. But the analysis around it, the aspects
17:44
of that has increased. So from that point of
17:46
view, if a leader is asking questions in a more
17:50
dynamic and a deeper mindset, the organization
17:52
should have the same technology and same mindset
17:55
adopted through because at the end of the day,
17:57
an organization is a reflection of our leadership
17:59
mindset, right? So if we know that our leadership
18:02
is going to into this mindset, our processes
18:05
should also reflect it. So again, that's exactly
18:07
what I'm doing in my world as well. Already anticipating
18:11
that there will be more questions and more like
18:13
different aspects of our data will be addressed
18:15
from a leadership point of view. How are we getting
18:18
ourselves? And that's also combines and ties
18:20
down to the fact that people need to adopt technology.
18:23
They cannot challenge it because that's not how
18:25
the world moves. We really need to ride the wagon
18:28
as the way it is moving and rather be part of
18:31
it, contribute to it and make it even better.
18:35
Absolutely. You can't have a circle of your senior
18:39
staff and let's say there are seven people and
18:42
you can't have six of the people using AI and
18:45
the seventh person saying, I don't want to touch
18:47
it. He's going to fall way behind and probably
18:50
not keep his job because he's falling behind.
18:54
So you just have to keep going. Absolutely. That
18:58
reminds me of this aspect of our mindset that.
19:02
Today, I'm able to produce something, let's say,
19:05
in two seconds. But that product looks so good
19:07
and satisfying that a lot of people are like,
19:10
oh, it's going to tell everybody that AI did
19:13
it. Yes, but AI is my tool right now. I am going
19:17
to market as a tool. In fact, that's what the
19:20
accomplishment is. And that's what the expectation
19:22
is, that now you have done your job faster, efficiently,
19:26
more analytical, deeper than ever, because you
19:29
have a tool that you utilized. Absolutely. I
19:33
can't agree with him more. Absolutely. When speed,
19:36
profit, and efficiency conflict with fairness,
19:40
transparency, or human judgment, what should
19:44
determine which one wins? That's one of the biggest
19:49
questions we're trying to answer now. Everything
19:52
that comes up new is hyped. We see only the positives.
19:57
But then when we start settling with it, start
20:00
living with it, we see... Everything has a pro
20:03
and a con attached to it. So does AI. AI is much
20:07
faster. There's a concept of deep learning here.
20:10
What that really means is we have way, way more
20:13
data and the ability to analyze that data. So
20:16
data was always there, but we never was able
20:19
to capture it or analyze it because we did not
20:21
have the mechanism or the tools. Now we do. What
20:24
does that mean? That means there is a lot of
20:27
issues that were never addressed. I'll give you
20:30
an example from a banking space. From a point
20:32
of view of risk, and I also manage that area,
20:35
so I understand this very deeply, the aspects
20:38
of risk were predefined. We have already known
20:41
because banks have been existing for years, they
20:44
know what they were dealing with. But things
20:47
have changed. With AI, the ability of our threat
20:50
mechanism has tremendously changed from what
20:53
we saw earlier. And hence, there is a huge need
20:56
of understanding that there is a lot of things
20:59
that we might not have seen earlier. And there's
21:01
an aspect of analyzing it and including it in
21:04
our models. Just to give you a little bit of
21:05
more technical answer here. And I was telling
21:07
earlier also, AI is not a verbal discussion.
21:11
It still needs to be implemented through technology.
21:13
What it means is with this new paradigm shift,
21:17
our whole infrastructure, the AI infrastructure
21:20
needs to now adopt the new threats that are coming
21:23
in. There is a huge discussions around cybersecurity
21:26
risks. Just last year, there was increase in
21:29
type of by one million in banking space. So we
21:34
now have so much more to be worried about from
21:37
that point of view. But again, for me, it's not
21:39
a worry. It's about the challenge that we are
21:41
trying to adopt with the new technology. And
21:44
there will be absolutely maturity around it.
21:46
And again, it will continue to be a cat and mouse
21:48
game that will always keep increasing and we
21:51
will always start maturing ourselves. Yeah, I
21:54
suppose that's human nature or the American way.
21:58
As soon as we attain that level, we want it,
22:01
and we're going to the next level. And it's always
22:04
going to be, they're going to go, we're going
22:05
to catch up. They're going to go, we're going
22:06
to catch up. So I absolutely agree with that.
22:10
Okay, let's bring this podcast full circle. 20
22:14
years from now, what do you hope people say that
22:17
the banking industry got right? Not technically,
22:21
but humanly. during the rise of AI? Again, I'll
22:27
start off with a happy answer here. Did we imagine
22:31
flying in an aircraft? The answer is they were
22:33
like, oh, there is no way. And why do we even
22:35
need it? In my opinion, everything is progressing
22:39
for a greater goal and a greater achievement.
22:42
There will be more efficiency and more satisfactory
22:45
products that will be delivered to human beings.
22:47
And they will be adopting that as their normal.
22:50
In my opinion, the things will now go much faster
22:53
and the way we will start looking life is very
22:57
different from what we have been seeing because
22:59
there will be more availability of aspects around
23:01
it. So all positive from my side, I'm already
23:04
seeing that there is so much more mindset that
23:07
is being created. And just to add to this from
23:11
a maturity model point of view, imagine the newer
23:15
generation who is going to start off with AI.
23:18
Their background is not what we have seen. The
23:21
reason these questions are being asked is somebody
23:24
has a comparison. Somebody who does not, they're
23:28
going to be basically sailing through this. Their
23:30
expectations, their maturity, and their mindset
23:32
will be based out of this AI paradigm shift.
23:34
And in my opinion, 20 years from now, the world
23:37
will be even better. It will be much safer, much
23:40
stronger, much more capable of what we are today.
23:45
Very good. Very good. You're just a great podcast
23:49
guest. You are filled with information that I
23:54
was dying to know, and you answered absolutely
23:57
every question that I had. That's so beautiful.
23:59
Sonny, if somebody wanted to get hold of you,
24:03
what's the best way to get hold of you, either
24:05
to read your book or be mentored or just to say
24:09
hi, how would they get hold of you? So various
24:12
ways, like I said, I'm always reachable through
24:15
my contact details and that's the best way to
24:17
reach out to me. But if somebody wants to understand
24:20
how I'm like contributing to this space, there's
24:23
a lot of aspects around me. I am right now a
24:26
dedicated global researcher. Like I said, I have
24:29
printed my book. It's already on Amazon. It literally
24:32
just got launched. This got published this month.
24:35
My two patents are very interesting for anybody
24:38
who's interested in understanding from a more
24:40
technical aspect. It's driven around a European
24:44
regulatory compliance. Very interesting to know
24:46
how things can actually be achieved through AI.
24:49
More aspects are like I'm currently contributing
24:51
to a lot of scholarly articles. I contribute
24:54
my knowledge into that. I'm basically authoring
24:57
those articles to express different aspects of
25:00
AI. And one of the major influences that I am
25:03
actually really enjoying it as being a keynote
25:05
speaker to a lot of international conferences.
25:08
I've seen that people are very curious about
25:10
knowing from an American point of view, I'm privileged
25:13
and honored that I'm in US for past 20 years.
25:16
They've seen this world very closely. And to
25:19
be honest with you, I'm really enjoying my journey
25:20
of sharing what I know, learning from a lot of
25:24
very, very learned people. And it has given me
25:27
a new enthusiasm. It's more like me being a student
25:29
again and trying to say what's next. Good. And
25:33
you know what? That's what this podcast is all
25:36
about. It's educating people on the various subjects
25:39
that I have brought. It's what I go from coast
25:43
to coast and I speak about. It's the communication
25:46
between everybody, everything, the networking.
25:49
It's all to educate. So, Sonny, I am so grateful
25:53
that you came on. And here's the takeaway. AI
25:57
can process the information, but people have
26:00
to own the decision. As technology gets smarter.
26:05
As technology gets smarter, leadership has to
26:08
become more human, not less. Trust judgment,
26:12
transparency, and accountability aren't outdated
26:16
skills. They're becoming more valuable. If you
26:20
enjoyed today's episode, follow and subscribe
26:22
to Networking Unleashed, Building Profitable
26:25
Connections for more conversations about networking,
26:28
communication, leadership, and relationships
26:31
behind business success. and share this episode
26:35
with a leader who's trying to figure out where
26:38
AI ends and human responsibility begins. I'm
26:42
Michael Foreman. Remember, technology can help
26:45
us make faster decisions. Character determines
26:49
whether they are the right ones. So I'll see
26:52
you on the next episode. Sonny, thank you again
26:55
for coming on my podcast. I'm wonderful. You
26:58
started my day really well, and I'm so motivated
27:00
and pumped. Thank you so much. Appreciate it.
27:02
Hello. I would like to welcome you to the Fusion
27:09
Alliance Business Expo 2. That's right. We're
27:13
having another networking expo. Now, this one
27:17
is going to be even better than the first one
27:19
in March. This one is October 22nd, held at Iphone
27:24
Restaurant and Event Center, 6000 Medlock Bridge
27:28
Parkway, Georgia. Now, this is your chance. This
27:32
is your chance to showcase your business. connect
27:35
with the community, and gain unmatched exposure.
27:39
This event is designed to highlight your thriving
27:42
business and is a must -attend gathering for
27:46
most local leaders and entrepreneurs. So now,
27:50
what is there going to be? First of all, it's
27:53
free admission to the public. So come one, come
27:56
all. There's going to be a large audience to
27:59
see your business. You're going to gain new customers.
28:02
build your brand, and establish strategic partnerships.
28:06
So whether you're looking to gain new customers,
28:10
build your brand, or establish strategic partnerships,
28:14
Business Expo 2 is the place to be. Don't miss
28:18
your chance to be part of this exclusive annual
28:21
showcase of Johns Creek's best businesses. Remember,
28:25
it's October 22nd. Remember that. October 22nd,
28:30
between the hours of 11 a .m. and 4 p .m. The
28:34
location, 6000 Medlock Bridge Parkway, Johns
28:38
Creek. You can go to the website and it's www.
28:45
FusionAlliance .info. F -U -S -I -O -N -A -L
28:50
-L -I -A -N -C -E .info. You can get all of it
28:55
there. You can be a vendor. You can be a sponsor.
28:57
Or if you want, you can just come on and enjoy
29:00
it. So come on down. Everyone else is going to
29:03
be there. And just enjoy yourself. All right,
29:07
folks. A huge thank you to our guests for sharing
29:10
such incredible insights today. And, of course,
29:14
a big shout -out to you. our amazing listeners
29:16
for tuning in and spending your time with us.
29:20
If you're interested in my digital courses, being
29:23
coached or having me come and talk to your company,
29:26
just go to Michael and fill out the request form.
29:30
Remember, networking isn't about being perfect.
29:33
It's about being present. So take what you've
29:36
learned today, get out there and make some meaningful
29:39
connections. If you've enjoyed this episode,
29:42
please don't forget to subscribe. leave us a
29:45
review, and share it with someone who could use
29:48
a little networking inspiration. Let's keep the
29:51
conversation going. You can find me on Apple,
29:54
Spotify, Pandora, YouTube, or my website, foreman
29:59
.com slash podcasts.