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< Intro >

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

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I'm your host, Adam Larson,

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

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The founder and CEO
of Ascent CFO Solutions.

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

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Such as coding transactions and
streamlining forecasting processes.

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

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The potential for growth
and efficiency is immense.

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But it's important to proceed with caution,

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

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Throughout this episode we
highlight the evolving role of finance

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

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to leverage its benefits.

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From bookkeepers, to CFOs,
to fractional CFOs,

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AI has the power to enhance efficiency

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and transform the way we
approach financial management.

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So grab your headphones,
and join us as we uncover

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the exciting world of AI in accounting.

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Let's dive in.

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< Music >

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

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

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

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

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Obviously, it does things
like enhance efficiency

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

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– Yes, thanks for having me on, Adam.

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

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

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

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

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

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

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for coding transactions
and things like that.

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

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

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and make iterations to
financial models and forecasts.

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

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

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and run different scenarios around that.

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Using large language models, and data,

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and being able to bring in data
and run multiple scenarios

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and see what things look like there.

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

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

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

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

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– Yes, that's a great point,

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

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are adapting quickly, other ones aren't.

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And software companies are
trying to integrate it into there

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but it's still in the early phases.

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So our traditional role-

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

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– Exactly.
– Yes, we've

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

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

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So I think proceed with caution,

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

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

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the emergence of the
Internet, and commercial use,

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

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

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

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and how life changing this is.

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

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Because there are so many
biases among how people think,

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

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

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

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– Correct, yes, I agree with that.

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

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

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and intellectual property,
and protection there.

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

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and protected and what's not.

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

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

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or being utilized improperly.

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And along the same lines,
research is another area.

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Tax research and other
types of accounting research,

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

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

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around trusting that research
and validating that it is accurate.

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

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

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

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and as you're looking at things online.

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

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Or "No, it's not."

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And how do you trust
those as you go forward?

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

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

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

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

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

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and accounting are going to
change because of these?

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I mean, obviously, they are.

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But how can we adapt as we go forward?

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

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

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

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the day to day transactional stuff.

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

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

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

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So it's definitely going to
change that bookkeeper

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

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

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

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

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

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But I think it'll make us more efficient.

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– Yes, I definitely agree with that.

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And as you're talking
about things like analysis

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and looking at it from that higher level.

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

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but we still need that human element.

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And how does that traditional
human analysis going to affect,

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as we look at the output from the AI?

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

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

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

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

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

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

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and you got large data sets out there.

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

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that stand out and look unusual.

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

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or sales orders that look unusual.

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

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

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might see that something
that a particular manager

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might tend to override things more often.

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Or looking at addresses, and zip codes,

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and understanding if there might be
some inappropriate payments made

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that match up to addresses,

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vendors matchup to employee
addresses or things like that.

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So that could be bogus,
that could be fraudulent.

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

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

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Where that AI tool can go in
and start digging around

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and finding some unusual patterns.

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

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

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What are some challenges
or ethical considerations

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that should be addressed,
when implementing it?

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– The first thing that comes
to mind is security.

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Right now, I've been reading some things

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

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bring in those tools inside your internet.

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

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

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and then utilizing that
in the greater universe.

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

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where things stay within
the four walls very clearly.

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That's the first thing that comes to mind.

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

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

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as opposed to it's really validating it.

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Whether that's research around case law,

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

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Just what comes out of a financial model,

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

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when you're forecasting your financials.

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

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

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

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

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

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I think that's a big part of it.

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

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Whether it be payroll,
invoicing, accounts payable,

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

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

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your initial review of a month-end close.

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

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

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to forecast, and pulling those out.

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So I think there can be
some automation around that.

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

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

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

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is the fractional leadership,
the fractional executive,

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and especially the fractional CFO.

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

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

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

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that you're with in that fractional capacity?

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

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

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

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

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to really implement these tools.

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

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

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

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

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the faster you can make adjustments.

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When you see something
change with your pipeline,

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I think, more agile an
executive team can act.

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

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

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

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

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and when you're in that transition,

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

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But how do you come in

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

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But they have never used those before.

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How do you bridge that gap?

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– Yes, it's an incremental process.

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

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they are often going through a transition.

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

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They've recently raised
another round of capital.

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They've got a new board
reporting requirements.

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

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

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it's going to be incremental steps.

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You first have to get a really solid ERP,

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

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

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

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That's something we've been leaning into

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

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

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

231
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And, so, those technologies first
need to have really reliable actuals,

232
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before you can lean heavily into some
of the other newer technologies,

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and more robust technologies.

234
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– That makes me think of how
important it is to have good data.

235
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Because you don't want to have
garbage in, then, it'll just be garbage out.

236
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So you have to really make sure
your data is in a good spot.

237
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– You don't even want to start to forecast

238
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or implement those better tools until
your historicals are accurate, for sure.

239
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And it's not just plain GAAP financials,
it's also what your KPIs look like.

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What are the real drivers of your business?

241
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And that's one of the things we look at
when we come into a new client,

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

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

244
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What's driving their growth, and
their revenue, and their cash flow.

245
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So we really lean into that.

246
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And, so, we'll often start with
what we call an assessment phase.

247
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We'll spend 20 to 40 hours
just really digging in deep,

248
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to understand every
component of the business.

249
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– Do you think that all
businesses would benefit

250
00:14:21,326 --> 00:14:25,050
from some a fractional executive
coming in and relooking at things?

251
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A lot of times people bring in
consultants to do that.

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But it's just like they look at everything,

253
00:14:29,680 --> 00:14:32,060
give you a PowerPoint,
and head out the door.

254
00:14:32,060 --> 00:14:35,493
But that fractional seems to be like
that person who partners with you

255
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for a period of time.

256
00:14:37,160 --> 00:14:40,930
– Yes, definitely, our model is
based on long-term but part time.

257
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So we're, generally, looking at
companies in the SMB market.

258
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So, generally, we work with companies

259
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between 2 million
and 100 million in revenue.

260
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And, so, as that company scales,

261
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some companies are too
quick to hire a full-tim CFO.

262
00:14:56,430 --> 00:14:58,760
Where they might really just
need a full-time controller,

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a really solid controller,
and an accounting team.

264
00:15:00,826 --> 00:15:03,326
And, then, a fractional CFO
for a couple of days a week,

265
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who's extremely well qualified and very
experienced, could be a great fit for them.

266
00:15:07,826 --> 00:15:13,826
To bring in that true executive level
oversight, with decades of experience,

267
00:15:13,826 --> 00:15:17,326
to help them navigate, again,
what those critical KPIs are.

268
00:15:17,399 --> 00:15:19,326
Where the holes are and the different
strategies that are being considered

269
00:15:19,326 --> 00:15:21,160
and things like that.

270
00:15:21,160 --> 00:15:25,130
So, yes, companies that
are worth 75 or 100 million

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00:15:25,130 --> 00:15:28,630
very likely to have a full-time CFO,
a very qualified CFO.

272
00:15:28,630 --> 00:15:30,992
But companies under 75 million

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or depending upon the transaction
complexity, and transaction volume, 

274
00:15:34,992 --> 00:15:38,992
companies that are small
and medium-sized businesses

275
00:15:38,992 --> 00:15:42,560
can really benefit from having
a top-notch CFO on their team.

276
00:15:42,560 --> 00:15:46,319
But it may not need to be a 40
hours or 60 hours a week job.

277
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It can maybe be a 20 hours
a week type of engagement.

278
00:15:49,992 --> 00:15:53,910
– So you get that full-time experience,
that experienced person there.

279
00:15:53,910 --> 00:15:57,326
But you may not, necessarily,
be able to afford the salary

280
00:15:57,326 --> 00:15:59,639
that would require to have
that person on full-time.

281
00:15:59,826 --> 00:16:04,826
– Yes, and there may not be enough, truly
strategic, CFO-level work for that person,

282
00:16:04,880 --> 00:16:08,740
that you need to have
someone on a full-time basis.

283
00:16:08,740 --> 00:16:11,160
That's what our whole model is based on.

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

285
00:16:16,639 --> 00:16:20,492
Our team is CFOs, and VPs of Finance,
and controllers, accounting managers, 

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00:16:20,492 --> 00:16:21,769
financial analysts, senior accountants.

287
00:16:21,769 --> 00:16:25,020
So we've got a full stack of people
with different levels of experience,

288
00:16:25,020 --> 00:16:27,825
who can come in and support a company

289
00:16:27,825 --> 00:16:31,900
during its growth phases, and
you pay for what you need.

290
00:16:31,900 --> 00:16:39,159
As opposed to having a real heavy fixed
cost on your G&A budget, G&A financials.

291
00:16:39,825 --> 00:16:41,240
– Yes, that seems like a really good benefit,

292
00:16:41,240 --> 00:16:43,460
especially, for the small
to medium-sized businesses.

293
00:16:43,460 --> 00:16:45,100
Is it beneficial for a startup?

294
00:16:45,100 --> 00:16:46,899
If a startup is just getting going;

295
00:16:46,899 --> 00:16:49,410
as an entrepreneur, is it good
to bring in fractional folks,

296
00:16:49,410 --> 00:16:51,992
or do you think full-time
would be more beneficial?

297
00:16:51,992 --> 00:16:56,149
– Yes, fractional makes a lot of
sense for an early stage company.

298
00:16:56,149 --> 00:16:58,992
I look at as a step function.

299
00:16:58,992 --> 00:17:01,850
You start out maybe you just
need a part-time accountant

300
00:17:01,850 --> 00:17:04,220
to make sure things
are being coded properly.

301
00:17:04,220 --> 00:17:07,860
Once you have revenue and you're
ready to raise around the capital,

302
00:17:07,860 --> 00:17:11,439
then, you probably want a strategic
fractional CFO or VP of finance,

303
00:17:11,439 --> 00:17:13,960
who can help you with
that capital fundraise,

304
00:17:13,960 --> 00:17:17,325
help you with a really
robust financial model,

305
00:17:17,325 --> 00:17:19,920
and understanding what
your KPIs and drivers are.

306
00:17:19,920 --> 00:17:24,492
And, then, over time, you start to fill in
some of those roles on a full-time basis,

307
00:17:24,492 --> 00:17:26,030
as you get a growth cycle.

308
00:17:26,030 --> 00:17:30,810
So it's not uncommon, maybe, you
start with a fractional senior accountant

309
00:17:30,810 --> 00:17:33,429
and a little bit of oversight,
from a fractional controller.

310
00:17:33,429 --> 00:17:38,158
And then that evolves into
one or two full-time accountants

311
00:17:38,158 --> 00:17:40,325
and, then, a fractional CFO,

312
00:17:40,325 --> 00:17:42,110
and, then, eventually, you
get a full-time controller,

313
00:17:42,110 --> 00:17:48,490
and it just builds as you go up the
ladder in revenue, and fundraising.

314
00:17:48,490 --> 00:17:51,491
– So this is not have to do
with fractional CFO.

315
00:17:51,491 --> 00:17:54,158
But I want to throw this question out there
and you feel free to answer it or not.

316
00:17:54,230 --> 00:17:56,590
But do you think that the evolution of AI

317
00:17:56,590 --> 00:17:59,970
will help bridge the gap
between US GAAP and IFRS,

318
00:17:59,970 --> 00:18:02,299
to make it a more international
accounting standards?

319
00:18:02,299 --> 00:18:04,325
– I think it definitely has potential to.

320
00:18:04,325 --> 00:18:10,324
I think that there's logic in
the way that things like RevRec

321
00:18:10,324 --> 00:18:14,491
and other things are being handled,
between IFRS and US GAAP.

322
00:18:14,491 --> 00:18:16,658
So, I think, there's definitely
some good potential there.

323
00:18:16,658 --> 00:18:22,824
– Yes, I don't know, because I just feel
like as we become a more global world

324
00:18:22,824 --> 00:18:24,824
and how we would do
business and everything.

325
00:18:24,824 --> 00:18:28,824
It would make more sense to have a
globally recognized accounting standard,

326
00:18:28,824 --> 00:18:32,824
so that everybody's doing the same, has
the same standards that they live up to.

327
00:18:32,870 --> 00:18:35,350
Obviously different countries have
different beliefs and stuff like that,

328
00:18:35,350 --> 00:18:38,158
but it would make sense
for us to think globally.

329
00:18:38,158 --> 00:18:41,158
– Yes, I like that, I hadn't given
that a lot of thought before,

330
00:18:41,158 --> 00:18:42,491
but that does make a lot of sense to me.

331
00:18:42,491 --> 00:18:45,491
– Mh-hmm, well, Dan, I want to thank you
so much for coming on the podcast.

332
00:18:45,491 --> 00:18:46,657
It's been great talking with you.

333
00:18:46,657 --> 00:18:47,824
Thanks so much for sharing

334
00:18:47,824 --> 00:18:49,989
your knowledge and expertise
with our audience.

335
00:18:49,989 --> 00:18:53,824
– My pleasure Adam, really it
was fun to meet you

336
00:18:53,824 --> 00:18:56,657
and fun to discuss these
emerging technologies with you.

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00:18:56,657 --> 00:18:58,800
< Outro >

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– This has been Count Me In,

339
00:19:00,324 --> 00:19:04,491
IMA's podcast, providing you with the
latest perspectives of thought leaders,

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00:19:04,491 --> 00:19:06,324
from the accounting and finance profession.

341
00:19:06,324 --> 00:19:08,991
If you like what you heard,
and you'd like to be counted in

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00:19:08,991 --> 00:19:11,370
for more relevant accounting
and finance education,

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00:19:11,370 --> 00:19:17,824
visit IMA's website at www.imanet.org.