Inside Marketing with MarketSurge

Hello and welcome again to
the MarketSurge Podcast inside

Marketing with Market Surge.

Today we're gonna talk about AI and
talk about it at a business level

for non-technical professionals.

So I would raise my hand and say, I'm
one of those non-technical professionals.

I was actually an Italian major when in my
undergrad learned ai through application.

And I hope I can convey the sense that
this is learnable and you can adopt

this for your business even if you
aren't at your computer all the time.

But hopefully there is
some utility you can find.

So I also promise not to let AI steal my
job or your job by the end of this show.

I do have a passion for making
technology accessible to

business owners of all kinds.

Particularly the
non-technical business owners.

And really wanna show you how you
can use the power of AI to grow

your business and rather than
replace you to extend your efforts.

Just to level set.

By 2027, the global AI market is
expected to reach $500 billion.

So essentially it's, it is going to
be an enormous market and we're going

to see so many businesses participate.

Now, Andrew Ing, who is an academic
and an entrepreneur he said

that AI is the new electricity.

Now if you think about it, you know
what life was like before electricity.

Obviously before any of us were born,
but we're aware of it and clearly

that was a world changing innovation.

AI is like that too.

It isn't something we can ignore.

It is something that we
have to embrace and rely on.

It's like when the buggy whip maker
had an opportunity to invest in Ford

early, but didn't see the utility,
didn't see the opportunity the

ground shifting underneath his feet.

That is something that we all
have to be cognizant of as we

approach AI and how we use it.

AI really is the next step
in the information economy.

The internet affected every business
that was so you had electricity

and telephones and the internet
which was a huge leap forward.

But now we've added the
capacity for growth of ai.

And it is something that we
should adopt and utilize.

Now today we're gonna talk about in a
few segments the AI fundamentals and

how it's revolutionizing industries.

In the second section, some
insights from some experts and

finally, some practical tips for
dipping your toes into the AI pool.

Now I'd invite you if you
have any questions to comment

or contact us anytime.

We love to talk AI and maybe a human
will even respond to what you ask.

No promises though.

So let's jump into the
AI fundamentals now.

AI really is high tech software that can
learn patterns faster than you can say

the extended artificial intelligence.

It learns extremely rapidly
and it relies on technology.

So both code and physical hardware
that are light years ahead of what

we have been using in recent years.

Now there are three key
concepts to be familiar with.

That's machine learning, deep learning
and natural language processing.

Really it's, this is the technical
part of the presentation, but

something that is worth being aware of.

Machine learning, first of all, it's a
branch of artificial intelligence that

enables computers to learn from data.

And improve over time without
being explicitly programmed

or explicitly taught.

It involves developing.

Complex algorithms that identify
patterns, make predictions and

adapt to new circumstances as
they process more information.

So essentially they ingest some
information, learn from it expand on their

capabilities and ingest more information,
and the same over and over again.

They leverage statistical
techniques, data analysis, and

can automate decision making.

Optimize processes and provide
insights in areas ranging from

recommendations for shopping personal
decision making or fraud detection.

It turns raw data into actionable
intelligence, allowing organizations to

solve complex problems more efficiently.

And frequently uncovering new
opportunities for innovation.

So our second term is deep learning.

Deep learning is a subset
of machine learning where a

computer learns by processing
information through many layers.

So it's a bit like how the brain works.

imagine showing the computer
lots of pictures and it gradually

figures out that some pictures
have cats while others don't.

Each layer picks up on simple details
until it can recognize the whole cat.

This layered approach helps the
computer understand complex things

like speech, images and texts, all
by learning from examples rather

than being told exactly what to do.

Okay.

Our final technical term,
natural language processing.

So it's often referred to as NLP.

It's giving the computers the ability
to understand and talk like we do.

It's a technology that helps computers
read and interpret the way we communicate

with computers in a more sensical way.

So whether it's powering chat
bots translating languages

or sorting through emails.

NLP makes our interactions with technology
feel a lot more natural and less robotic.

And I think if you've had interactions
with chat bots over the years

you'll remember two or three years
ago it seemed very mechanical.

And they are getting better.

That's the truth.

And this NLP enables the
machines to better understand us.

Let's talk a little bit
about the history around ai.

Jump to our, understanding
of where it started.

So obviously AI has been a
plot in many sci-fi movies.

I think about blade Runner
the Terminator, the Matrix.

Now, in each of those, I.

Arguably the AI represents the villain
or the antagonist, something that is

going to sweep and destroy humanity.

Ai, as the, as it's manifested,
actually been a great resource to us.

But the concept of AI has been around
long before those movies were, in

the 1950s, it was incepted but the
limitations of both the technology

and the logic algorithms held it back.

Around the mid two thousands, there
were some new and better deep learning

techniques that began to outshine.

What they'd done.

And that allowed them to have
great innovation in computer vision

and natural language processing.

So you know that was manifested in
Google images, being able to recognize

things in pictures and compare and find
similar images and better understand

things that you'd type in search.

That's probably the best
example to think about.

One big leap forward came in 2012 when
Alex net dramatically outperformed

competitors and image recognition
tasks, and that really ignited some

excitement around deep neural networks.

And that excitement came with
investment and this momentum

carried into voice assistance.

So you think like Siri, Alexa.

Whatever Google Assistant was
called, sorry, I'm not familiar.

But this started to conceptualize
self-driving car technology.

And what was science fiction before
now became reality now in 2016.

Famously.

Google's Alpha Go made headlines
by beating a world champion

in the complex game of Go.

It's so complex.

I don't even know how to play it.

I don't even know what it is.

Obviously it's way over my head, but this
machine beat the world's grand at go.

And apparently that had never been done.

If you remember some of the battles.

Between chess, grand masters and
computers over the fifties and beyond.

It was Watson.

I think that was finally very
victorious and with some controversy,

I think but victorious over some
of the greats in the chess world.

But recently we've seen big
leaps forward in the GPT models.

So the actual apps you can use
like chat, GPT and Gemini from

Google, and Grok from TikTok.

So big advances and then other image
generation engines like Dally and

mid Journey and many like that.

You go from having six fingers
on each hand to having much more

high fidelity high resolution
images that look realistic.

And today, even just a few weeks ago,
we saw a huge leap forward in even

the free version of chat, GPT enabling
you to create production ready images

that previously you had to have a
graphic designer create for you.

The history is continuously being written.

We're going to have changes next week.

We're going to see continued
increased capabilities of this in

the way that we interact with this.

We're not gonna be able to
avoid ai even as consumers.

By the end of 2025, Gartner forecasts that
75% of companies will be operationalizing

ai, so it may not feel like it, and maybe
you feel like you are one of those that.

Might fall on that 25% but it is quite
accessible, quite easy to adopt and

bring into your business in small cases.

So let's talk a little bit
about how it's being used.

We know some obvious ways.

I think we've received robocalls that
have a little bit of intelligence

or placed a customer support
call that was an automated voice.

But, in retail ai, chatbots and other
smart inventory systems are helping

up to 70% of retailers improve the
results that customers find in search.

And it has improved the shopping
experience and it has increased.

Sales because customers are more
frequently presented with what they

actually want to buy or what they,
maybe didn't realize they needed.

But they're presented at the right time.

So in finance 60% of banks have
deployed AI for fraud detection.

So that's great.

Can't be grateful enough for a
few times that the AI has saved.

Me from potentially being hacked,
wish the world were different

but we do need powerful resources
to protect us from fraud.

Now in the healthcare world.

So healthcare providers are using AI to
streamline diagnostics and even treatment

plans, they have access to tools.

These doctors and other medical
professionals have access to tools that.

Can rapidly identify and provide
treatment for all sorts of things.

And so that speeds up things and it
provides additional intelligence.

So from a marketing standpoint
that almost any business could use

personalization it's an important
concept for any marketer to bring.

The right message to the right,
to the individual groups.

In addition to the response
rate that comes from.

Effective personalization.

There's the concept of automation.

Not only are the parameters and the
ability to distinguish between different

kinds of consumers now available from
ai, but also it powers the interaction.

The example is chatbots are now handling
over 85% of routine customer interactions.

We've all interacted with
a chatbot at some level.

But as a business owner that frees you
up to deal with the more interesting

parts of your business essentially.

Now I think this was probably a similar
phenomenon, we've used chatbots both for

support and for initial responses to.

Incoming leads.

Occasionally we're met with
some anger, and in particular a

gentleman today just lost his mind.

When he realized that he was interacting
with a bot, which, was unfortunate.

But.

It's unrealistic to think that
you're going to get humans in

every interaction with a business.

And also remember, I would remind
all of us that when you have a rant

either on typing text or on the voice
those interactions are recorded and

those are tied to your identity.

So remember, the internet is forever.

AI can also be a predictor.

It can potentially predict future
purchases that you need to make

based on a large audience that
it has observed and synthesized.

And that can be helpful for making
future business decisions now.

Let's talk a little bit about what
some of the thinkers around ai, so

that's both the innovators and the
academics and the business leaders

in the AI world have specified.

I mentioned Andrew ing and he
described AI as the new electricity.

So if electricity can power your phone.

AI can power your business growth
with the information and the thinking

power it can provide can hugely
expand your business's potential.

Fu Lee, who was a business
executive Taiwanese, that worked

for both Google and Apple.

He claims that AI will
be the biggest technology

breakthrough of the 21st century.

Not super revolutionary, but
it's important to think of.

Like we have to think of it as it is, this
is a tremendous game changer for business.

Jenny Rome maybe from a
more pragmatic standpoint.

She was the CEO of IBM
for many years, and was.

One of her big projects was the
development of the Watson machine.

So she brought AI and very high
speed computing machine learning

to a practical business level.

IBM obviously had a lot of
financial and other large.

Large business clients and with
Watson were able to power much

more advanced analytics than
had been previously possible.

So she's said that these cognitive
systems can help businesses not just

process these vast amounts of data, but
also derive intelligence, provide that

intelligence to business leaders and.

Essentially that this part, this
technology is a smart partner to the

human managers at these businesses.

Satya Nadela and Eric Olsen have
mentioned so Satya Nadela, the CEO of.

Microsoft and Eric Brisen who is another
academic in the computer science space.

They have been big advocates
for democratizing ai.

Now, what that means is, making aI
tools accessible at free levels.

Most of our AI technologies have a free
tier available for you to experiment

so that AI can learn, but also as a
human population, we can embrace this

technology and be familiar with it.

And this isn't something that the elite
or the rich can only use and access.

There is a concern that AI replaces
workers or that it replaces professions

or industries and this democratization
and making it accessible at free levels

to all who have access to a computer or
even a smartphone this is how they are

attempting to counter those concerns.

And I think it's a.

Very worthwhile pursuit.

A couple of the big power players in
this are Sam Altman, who is running

open ai, which Powers Chat, GPT,
and then Elon Musk who powers grok.

Unfortunately I think the biggest
story around the two of them,

though, they have very powerful.

Ai frameworks, they are playing out a very
bitter rivalry in public on social media.

But, they have with their wealth
and resources and strength and

innovation really pushed this
forward into the commercial space.

Now that we've had our fill of the
experts and the thought leaders in

this space, let's talk a little bit
about some of the concerns around ai.

So there are some challenges.

It isn't easy to ramp up.

There are obviously data quality issues.

You can ask chat GPT something and get
a response that say you're an expert in

it'll res return a response occasionally
that is just flat out wrong.

It is.

Important to check your work and
not rely solely on one engine.

You can always ask for sources when
you're looking and you can check

those sources when you're using
chat, GT or other GPTs for research.

So there's also some
ethical issues around bias.

AI is trained on human communications,
whether it's on social media or comments

or anything, it's reading online.

And so as a result, it does have
some biases that it picked up from

those interactions because humans
have biases in some cases they've

reflected prejudices against women,
minorities that are unfair and bad.

And here's a couple examples.

So there's a criminal justice
tool compass, which is used

to predict re-offending risks.

It was found to exhibit racial biases
leading to higher false positive

rates for minority defendants.

Recruiting tool developed by Amazon was
discontinued after it was discovered

that its algorithms favored male
candidates reflecting historical gender

biases hiring data facial recognition
systems, things we use on our phones

and maybe at airports have been.

Criticized for misidentifying
people of color at higher rates

than people with lighter skin.

It is important to be aware of
these things and to advocate for

fairness in all of AI's uses, so
let me talk a little bit about best

practices for getting started with ai.

The first thing you want to do is
start with a small pilot project.

And like I said, you can use
free tools to get started.

So maybe that's a simple search of
to prepare for a client presentation,

to do some deep research.

You also need to have.

As many people on your staff as
possible come familiar with using ai.

And then you all may want to enlist
the expertise of an AI or tech

expert to help you get started.

Now, Rome wasn't built in a day and
neither was an AI powered business.

You'll need to take baby steps.

You don't want to just totally
turn on the switch and rely on it.

AI learns and so you need to take
it through every kind of training

that you would do for a new
employee or somebody just learning

the business from the outside.

Now AI can do that quite quickly,
but you have to check its work.

Now let me just recap
a few key points here.

AI is built on self-learning technology.

It will continue to improve.

So everything that I've shared
here is accurate up to this moment.

And things will continue to change.

It has a revolutionary role in many
industries, and we're just learning

about its potential for many others.

It can provide increased
efficiency, better customer

engagement, and potentially a more
futuristic flare to your business.

So let's talk a little bit
about some actionable steps.

Now I'd like you to all identify
one area in your business that

is ripe for an AI upgrade.

You wanna start with a pilot product.

You wanna start with a pilot project
that won't leave you in the dust.

So feel free to use books, online
resources, training courses.

There's a lot of resources on YouTube.

There's a lot of resources that
come with these AI engines.

And you'll be able to, it.

This is learnable and accessible.

Even the savviest business mogul started
somewhere, and often it was just with

what is ai, Googling, what is ai?

Excuse me.

Now I am very excited
about the future of ai.

I think it enables so many people and the
innovations are going to be mind blowing.

We just can't even predict them.

But I would encourage you to start your
AI journey today and if you've started

to continue to learn and optimize
and find more places that you can

accelerate your business and grow but.

You know it, this is doable.

And I'm excited for what the future
holds for you and your business.