< Intro >

– Welcome back for another
exciting episode of Count Me In.

I'm your host, Adam Larson,

and today we have a special
guest joining us, Dan DeGolier.

The founder and CEO
of Ascent CFO Solutions.

We start off by exploring current
use cases of AI in the industry.

Such as coding transactions and
streamlining forecasting processes.

But as Dan points out, we're only
scratching the surface of what AI can do.

The potential for growth
and efficiency is immense.

But it's important to proceed with caution,

and be aware of the biases and ethical
considerations that come along with it.

Throughout this episode we
highlight the evolving role of finance

and accounting professionals, in the
age of AI, and how they can adapt

to leverage its benefits.

From bookkeepers, to CFOs,
to fractional CFOs,

AI has the power to enhance efficiency

and transform the way we
approach financial management.

So grab your headphones,
and join us as we uncover

the exciting world of AI in accounting.

Let's dive in.

< Music >

Well, Dan, we're so excited to
have you on the podcast today,

as we're going to talk about
AI and fractional leadership.

And just to get started,
as we think about AI,

how is it currently being applied
to finance and accounting sectors?

Obviously, it does things
like enhance efficiency

and reduce errors, but how is
it being applied in those areas?

– Yes, thanks for having me on, Adam.

It's a pleasure to meet you,
pleasure to be here.

I think we're just getting
started, for one thing.

AI, even though it's been around
for a while, ChatGPT, GPT 4,

and all those things, are
relatively new to the mainstream.

And, so, a lot of this stuff we're just
starting to figure out right now.

Definitely, in the accounting side,
we're starting to see some use cases

for coding transactions
and things like that.

I think there are a lot of opportunities
in our world, in the finance realm.

When it comes to forecasting, to be
able to streamline multiple scenarios

and make iterations to
financial models and forecasts.

I think that's an area that
we're starting to see develop.

And, then, things like pricing strategy
and looking at different ways to price

and run different scenarios around that.

Using large language models, and data,

and being able to bring in data
and run multiple scenarios

and see what things look like there.

I think those are all some
areas that we're starting to see.

But, honestly, because it's so early, what
is really going to be the biggest use cases,

two years from now, is probably
something we haven't thought of.

Or somebody's thought of but
hasn't really been implemented, yet.

– Yes, that's a great point,

that we're so early in the generative
AI phase that some organizations

are adapting quickly, other ones aren't.

And software companies are
trying to integrate it into there

but it's still in the early phases.

So our traditional role-

– And it's still prone to errors as well.

– Exactly.
– Yes, we've

all read the articles about the
lawyer who tried to use it for briefs

and got in huge trouble, and the
hallucinations are still rampant.

So I think proceed with caution,

but recognize that it has enormous
potential and don't be left behind.

I was going to say, I've heard that it's
been compared to if you look at Web 1.0,

the emergence of the
Internet, and commercial use,

that this could be a 10x-type of opportunity.

From a growth potential, from
an efficiency potential, et cetera,

it's just fascinating to me,
just how massive this could be,

and how life changing this is.

– Well, and also the bias that's
implicit in there, in the AI.

Because there are so many
biases among how people think,

wording, that's out there in
the Internet and how it's learning.

There's going to be that bias that
you have to get over as well.

Because it's going to be embedded
in there because of how it is societally.

– Correct, yes, I agree with that.

I think one other ethical consideration
that needs to be taken into account,

when you're implementing AI, is
things around copyright infringement,

and intellectual property,
and protection there.

I think the chat bots aren't
necessarily aware of what's IP

and protected and what's not.

And, so, it's important that we take into
that, that there's a human overseeing that,

and making sure that there's
nothing being taken out of context

or being utilized improperly.

And along the same lines,
research is another area.

Tax research and other
types of accounting research,

is a place where there is
a lot of use cases for AI.

But, again, this is where
you need to be very careful

around trusting that research
and validating that it is accurate.

So we don't end up in a situation, where
something that's not valid is being utilized.

– It's going to be very difficult to
understand what has been verified

and what hasn't,
and as you're doing research

and as you're looking at things online.

I imagine new tools are going to have to
be developed to verify, "Yes, this is valid."

Or "No, it's not."

And how do you trust
those as you go forward?

– Yes, that's really important, and
there are going to be mistakes made.

As we start to adopt this, we're
going to see mistakes being made.

And, as humans, we need
to learn from our mistakes

and learn from others' mistakes,
that's how we evolve.

– Mh-hmm, do you think that
the traditional roles in finance

and accounting are going to
change because of these?

I mean, obviously, they are.

But how can we adapt as we go forward?

– Yes, I think, first thing I would suggest
is pay attention to what's going on,

see what's evolving, see
where things are taking it.

I think it's going to definitely
change the accounting side,

the day to day transactional stuff.

There's a YouTuber out there,
Hector Garcia, who has done some demos

of how you can plug in a ChatGPT
tool into QuickBooks Online,

and how that can help ease the coding
of transactions and things like that.

So it's definitely going to
change that bookkeeper

and junior accountant role significantly,
I think it'll change all aspects.

The CFO's desk, it's going to still
require somebody with experience,

and knowledge, and understanding,
to validate what's coming out of it.

Just like in any other industry,
there's a lot of need to confirm,

and double check, and be heavily
involved at that strategic level.

But I think it'll make us more efficient.

– Yes, I definitely agree with that.

And as you're talking
about things like analysis

and looking at it from that higher level.

I mean, obviously, the AI
has a better computing power,

but we still need that human element.

And how does that traditional
human analysis going to affect,

as we look at the output from the AI?

– Yes, that it's still going to be critical.

Machines are going to do a lot of
the analysis and it'll find pattern.

It's better at pattern recognition than
us, especially, with large data sets.

But when it comes back to that
human element of truly understanding,

and the uniqueness of certain things,
it's going to require a human element.

In preparation for this call, I was
thinking a lot about fraud detection,

and you got large data sets out there.

I think, again, back to pattern recognition,
AI can be really good at identifying things

that stand out and look unusual.

I mean, if you think about,
maybe, purchase orders

or sales orders that look unusual.

Maybe have overrides from managers
and they can look for patterns there,

where particular users, within an
ccounting system or ERP system,

might see that something
that a particular manager

might tend to override things more often.

Or looking at addresses, and zip codes,

and understanding if there might be
some inappropriate payments made

that match up to addresses,

vendors matchup to employee
addresses or things like that.

So that could be bogus,
that could be fraudulent.

I think those things are going to
be a huge area for auditors,

both, internal and external auditors
starting to use those data sets.

Where that AI tool can go in
and start digging around

and finding some unusual patterns.

– Yes, and thinking about implementing
AI, within your organization,

if you're really considering this,
you've done all the research.

What are some challenges
or ethical considerations

that should be addressed,
when implementing it?

– The first thing that comes
to mind is security.

Right now, I've been reading some things

that we're trying to be able
to bring it inside your intranet,

bring in those tools inside your internet.

But you don't want to have breaches
of data, things that go out,

where the chat bot is getting
a hold of your corporate data

and then utilizing that
in the greater universe.

And, so, that's going to be really critical,
is that we solve for security concerns

where things stay within
the four walls very clearly.

That's the first thing that comes to mind.

And I think the other one is touched on
earlier, which is just trusting it too much

and seeing that something that
comes out of it is just trustworthy,

as opposed to it's really validating it.

Whether that's research around case law,

when it comes to tax law,
or whether it has to do with...

Just what comes out of a financial model,

and what's practical from a pipeline
perspective and things like that,

when you're forecasting your financials.

– Yes, so as we look to the
future, when it comes to AI.

What are some of the breakthroughs that
you think will happen within the finance

and accounting industry, as we
look to the future with AI?

– Automation, in general, and
that can take multiple forms.

We touched on the accounting coding
of transactions and things like that,

I think that's a big part of it.

There can be a lot more automation
around all of the accounting cycles.

Whether it be payroll,
invoicing, accounts payable,

there can be a tremendous amount
of automation on that side.

Variance analysis when it comes
to your soft close of the books,

your initial review of a month-end close.

I think there can definitely be an
analysis and digging in a transaction,

and looking for those variances to prior
periods variances, to budget variances,

to forecast, and pulling those out.

So I think there can be
some automation around that.

And, then, again, on the
financial modeling piece,

the forecast piece, there will
be automation there as well.

– So one area of expertise that
you have a lot of expertise in,

is the fractional leadership,
the fractional executive,

and especially the fractional CFO.

And as we're talking about AI and
the changing of how that CFO looks.

How do you see the ability to
have this AI as a fractional CFO.

How does that really enhance your
ability to help the organizations,

that you're with in that fractional capacity?

– Yes, well at our firm,
we're technology first,

and we've always been focused
on automation where we can.

So I think for us, it's going to be
those same types of approaches.

Where we find ways to be more
efficient, to be more cost effective,

to really implement these tools.

Identify the best use cases for
these tools, kind of trust but verify,

Make sure that you still got that
adult supervision, with that AI tool.

But really leaning into it and making it a
tool that speeds up data for the C-suite.

The faster you can close your books,
the faster you can update your model.

the faster you can make adjustments.

When you see something
change with your pipeline,

I think, more agile an
executive team can act.

– So when you're coming in
as a fractional executive,

a lot of times the best place for that
model is an organization in transition.

And, so, that's what I've been reading
when I've had other conversations.

It seems like it's organizations
that are in transition,

and when you're in that transition,

it seems like you would be
looking at all your systems.

But how do you come in

and say, "Hey, I want to have this
technology first and utilize these tools."

But they have never used those before.

How do you bridge that gap?

– Yes, it's an incremental process.

I mean, when we look at
working with a company,

they are often going through a transition.

Maybe, they're looking to raise
an additional round of capital.

They've recently raised
another round of capital.

They've got a new board
reporting requirements.

They need better discipline, when it
comes to forecasting their cash flow.

So if they're a little behind the 8-ball,
when it comes to technology,

it's going to be incremental steps.

You first have to get a really solid ERP,

or accounting system in place that
is trustworthy and fully GAAP.

Whether they're audited or not, you want
them to be fully on accrual GAAP basis.

Once you have that, then, you start to put
in place those data visualization tools.

That's something we've been leaning into

really heavily the last year or two,
is creating really robust dashboards

and data visualization, that not only
show your historical financials,

but your forecast, and your HR, and
your payroll, and your sales pipeline.

And, so, those technologies first
need to have really reliable actuals,

before you can lean heavily into some
of the other newer technologies,

and more robust technologies.

– That makes me think of how
important it is to have good data.

Because you don't want to have
garbage in, then, it'll just be garbage out.

So you have to really make sure
your data is in a good spot.

– You don't even want to start to forecast

or implement those better tools until
your historicals are accurate, for sure.

And it's not just plain GAAP financials,
it's also what your KPIs look like.

What are the real drivers of your business?

And that's one of the things we look at
when we come into a new client,

is really take the time to look at
the true drivers of the business.

They may not be obvious at first,
every company is a little bit different.

What's driving their growth, and
their revenue, and their cash flow.

So we really lean into that.

And, so, we'll often start with
what we call an assessment phase.

We'll spend 20 to 40 hours
just really digging in deep,

to understand every
component of the business.

– Do you think that all
businesses would benefit

from some a fractional executive
coming in and relooking at things?

A lot of times people bring in
consultants to do that.

But it's just like they look at everything,

give you a PowerPoint,
and head out the door.

But that fractional seems to be like
that person who partners with you

for a period of time.

– Yes, definitely, our model is
based on long-term but part time.

So we're, generally, looking at
companies in the SMB market.

So, generally, we work with companies

between 2 million
and 100 million in revenue.

And, so, as that company scales,

some companies are too
quick to hire a full-tim CFO.

Where they might really just
need a full-time controller,

a really solid controller,
and an accounting team.

And, then, a fractional CFO
for a couple of days a week,

who's extremely well qualified and very
experienced, could be a great fit for them.

To bring in that true executive level
oversight, with decades of experience,

to help them navigate, again,
what those critical KPIs are.

Where the holes are and the different
strategies that are being considered

and things like that.

So, yes, companies that
are worth 75 or 100 million

very likely to have a full-time CFO,
a very qualified CFO.

But companies under 75 million

or depending upon the transaction
complexity, and transaction volume,

companies that are small
and medium-sized businesses

can really benefit from having
a top-notch CFO on their team.

But it may not need to be a 40
hours or 60 hours a week job.

It can maybe be a 20 hours
a week type of engagement.

– So you get that full-time experience,
that experienced person there.

But you may not, necessarily,
be able to afford the salary

that would require to have
that person on full-time.

– Yes, and there may not be enough, truly
strategic, CFO-level work for that person,

that you need to have
someone on a full-time basis.

That's what our whole model is based on.

As you grow and evolve, you get the
resources you need on a fractional basis.

Our team is CFOs, and VPs of Finance,
and controllers, accounting managers,

financial analysts, senior accountants.

So we've got a full stack of people
with different levels of experience,

who can come in and support a company

during its growth phases, and
you pay for what you need.

As opposed to having a real heavy fixed
cost on your G&A budget, G&A financials.

– Yes, that seems like a really good benefit,

especially, for the small
to medium-sized businesses.

Is it beneficial for a startup?

If a startup is just getting going;

as an entrepreneur, is it good
to bring in fractional folks,

or do you think full-time
would be more beneficial?

– Yes, fractional makes a lot of
sense for an early stage company.

I look at as a step function.

You start out maybe you just
need a part-time accountant

to make sure things
are being coded properly.

Once you have revenue and you're
ready to raise around the capital,

then, you probably want a strategic
fractional CFO or VP of finance,

who can help you with
that capital fundraise,

help you with a really
robust financial model,

and understanding what
your KPIs and drivers are.

And, then, over time, you start to fill in
some of those roles on a full-time basis,

as you get a growth cycle.

So it's not uncommon, maybe, you
start with a fractional senior accountant

and a little bit of oversight,
from a fractional controller.

And then that evolves into
one or two full-time accountants

and, then, a fractional CFO,

and, then, eventually, you
get a full-time controller,

and it just builds as you go up the
ladder in revenue, and fundraising.

– So this is not have to do
with fractional CFO.

But I want to throw this question out there
and you feel free to answer it or not.

But do you think that the evolution of AI

will help bridge the gap
between US GAAP and IFRS,

to make it a more international
accounting standards?

– I think it definitely has potential to.

I think that there's logic in
the way that things like RevRec

and other things are being handled,
between IFRS and US GAAP.

So, I think, there's definitely
some good potential there.

– Yes, I don't know, because I just feel
like as we become a more global world

and how we would do
business and everything.

It would make more sense to have a
globally recognized accounting standard,

so that everybody's doing the same, has
the same standards that they live up to.

Obviously different countries have
different beliefs and stuff like that,

but it would make sense
for us to think globally.

– Yes, I like that, I hadn't given
that a lot of thought before,

but that does make a lot of sense to me.

– Mh-hmm, well, Dan, I want to thank you
so much for coming on the podcast.

It's been great talking with you.

Thanks so much for sharing

your knowledge and expertise
with our audience.

– My pleasure Adam, really it
was fun to meet you

and fun to discuss these
emerging technologies with you.

< Outro >

– This has been Count Me In,

IMA's podcast, providing you with the
latest perspectives of thought leaders,

from the accounting and finance profession.

If you like what you heard,
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visit IMA's website at www.imanet.org.