The Accounting Technology Lab

Brian F. Tankersley, CPA.CITP, CGMA: Ryan,
welcome to the accounting

Technology Lab sponsored by CPA
practice advisor, with your

hosts, Randy Johnston and Brian
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us, and here we are back in the
lab.

Randy Johnston: Welcome to the
accounting Technology Lab. I'm

your host, Randy Johnston, with
co host Brian Tankersley, and we

are so pleased to have a guest
today, Eric eager. Now, I've

known Eric for 20 plus years
from his old days at a

predecessor company which we'd
recommended to you, biznet, but

about seven or eight years ago,
Eric reached out to me and said,

You know, I've got a new idea.
And I listened to him, and I

said, you know, Eric, you could
be playing golf. And he said,

No, I want to make a difference.
I want to help small businesses

succeed, and I've got a great
idea to do it. It turns out, I

think he did, and over the last
years, he's been building a

platform called for impact data,
the number four impact data,

Eric, welcome to our podcast
today. Would you like to give a

little bit of introduction on
yourself now?

Eric Eager: Great, Ray, thank
you for having me on the show

again. I am a CPA, and I feel
like we been working on this

challenge of, how do we change
the odds for business owners,

and then at the same time, how
do we elevate the profession and

recognize the work and the
impact that we have on

businesses? And so we've been
working really hard on this. How

do we help the shift to
advisory? And I think that we

have broken the code, cracked
the code, as they say, and we'll

talk more about it, but, man, we
are super excited to tell people

more about it and help the
transformation in the

profession.

Randy Johnston: Very good. Well,
for our dedicated listeners, you

may recognize that Brian and I
have recorded a session on for

impact data in the past, but oh
my, it is so different.

Brian F. Tankersley, CPA.CITP, CGMA: So,
you know, Brian, it was like

four years

Randy Johnston: ago, so
different. So, as you may know,

has probably reviewed more small
accounting products than you

have ever seen in the past. And
just to give you a perspective

on that, you know, we go back to
the days of the peach trees. In

fact, I was actually drawn into
a recent interview from the

Privacy Forum, and I couldn't
believe that I heard an old

lotus, 123, name. I didn't
realize he had helped found the

Privacy Forum. But again, we're
lucky enough to have had the

long haul with the some of these
very well known products of the

past as well some of the new
products of today, so the

digits, which we've done
podcasts on, and others. So

we're really shifting from
transactional accounting and

financial reporting into
something that is quite

different. And you know, the
team at for impact data have

landed on the term decision
intelligence, but it really

probably evolved from a bit of,
I'll say, observation by Gartner

Group. So Eric, I might ask you
to take a moment and just help

our listeners understand what
decision intelligence is.

Eric Eager: Well, it's going to
be, you know, here's the thing

is that it is the next evolution
of AI, and it's not replacing

AI. It's kind of the things that
we've we've been working on. And

as you guys pointed out for the
last four or five years, and we

didn't realize we were building
it. But what decision

intelligence does is that it
takes the combination of AI,

data science, business
intelligence and humans

expertise, it literally gives
you the ability to codify the

experiences of others, but the
differences here is that what AI

is what they call probabilistic
and text driven. Decision

intelligence is deterministic.
It will literally tell you

statistically. Here are the best
actions to take, taking all

things considered, and it
provides you an audit trail of

how that decision was come to so
it is really this ability to

take from probabilities and what
you think to literally what

decisions are going to give you
the highest probability of

success.

Randy Johnston: And for those of
you who have attended a lot of

our k2 events. You might recall
that over a decade ago, it was

2015, and 16, we were presenting
heavily on data science, and for

those of you where I actually
did your on site tech

assessments, I frequently
recommended that you had a data

scientist in that window. Now, a
lot of this AI that we're

dealing with as you are,
probably also where it's been

around since the late 50s. 1958
is when AI started. But many

people think AI started when
chat GPT was released in

November of 22 you know, his
granddaughter from New York

says, grandpa, that not be the
plan. That is not the plan.

That's not how it happened. But
in about 2010 we started seeing

a lot of these pattern
recognition and pattern matching

and machine learning and this
evolution into the reporting

tools that Eric and his team
used because they took as their

basis Power BI and wanted to
have drillable dashboards in

some of the earliest models.
That was interesting, but it's

now a combination of for
decision intelligence, all of

these things, of AI and data
science and behavioral and so

forth. So you know, Eric, I know
you've been looking at the

Gartner content on this. What's
Gartner have to say

Eric Eager: on this? Well,
Gartner says that, literally, if

you haven't heard of decision
intelligence, you're going to

hear quite a bit about it in the
coming years. And here's what it

is, the reason being, and the
thing that I'm trying to help

elevate is that while you're
hearing all this AI decisions,

the challenge is that it is
incredibly powerful, but it's

changed. The answers are
changing. Every time you ask a

question, it is a black box. And
what's happening is that more

and more as we move into
advisory in these other pieces,

it is going to cause,
unbeknownst, what we call false

confidence and advisory, and
they are projecting it's going

to cause financial and
reputational loss simply from

the fact of human bias, ability
of critical thinking and aos AI

sycophancy, it is still as much
as they're trying it is going to

please you. And 2030 Yeah, I'm
sorry, go ahead.

Brian F. Tankersley, CPA.CITP, CGMA: So
effectively, we're going to be

lemmings running off a cliff.
Because AI said, Hey, wouldn't

it be a great idea if you ran
off a cliff Exactly?

Eric Eager: Now, here's the
thing, though, AI, if managed

correctly and you compliment it,
it will unleash capabilities

that all the positives and the
excitement, and why I'm excited

about it, and these models, by
2030 it will be five times more

trusted. It will be faster in
governing decisions than

ungoverned decisions. And this
is why you're going to hear

these things, because, and I'll
talk a little bit about, you

know, why is this happening?

Randy Johnston: Well, but you
know, on that point, Eric, I

think the good and bad we've
talked about that with past all

technology can be used for good
or bad. But the bad number that

we didn't quote for you is that
by 2027, 25% of the decisions

will actually have financial
impact in a negative way. That's

a big deal, because 2027 is a
lot closer than you might think

Eric Eager: well, and I'm glad
you pointed that, Alex, that

sometimes I forget we have audio
listeners and not video

listeners. So yeah, thank you
for pointing it out, because

that and I've heard and I've
talked to, you know, profession

and AI leaders throughout the
world, and they say that number

may be low, that it can be
significantly higher if we don't

watch it. So I'm glad you point
that out and in. So why is this

in? Important. Well, you know
what's happening is, AI, is the

world and velocity of business
is accelerating way before it's

happening so fast that we're all
having to react and do things

well. Ai, you know, the way that
we make decisions today is that

before you know, we have these
analysts that would bring

reports to us, and as leaders,
we would take all this

information and have to
prioritize and risk and see

what's short term and long term,
and then you had to make the

call, and then you go hand it
down to your operational team.

Well, what AI? And the
excitement about AI, it is

surfacing so many options now
that you're turbo charging your

analyst? Well, what that's doing
is that now it is accelerating

all these options to leaders,
and it still doesn't tell you.

It doesn't give you the well,
all these options for my

company, which one takes
precedence? What time do we need

to implement? What's the trade
offs, if we do this versus this,

I still have to make those
calls, and that's myself and my

advisor. Because we're always
going to have the need for

advisors. No matter what the
technology does, we're still

going to need that human
advisor, and it's going to cause

decision fatigue. And so all of
a sudden, we're going to make

the call. And now, if you add in
AI agents to that, the speed of

exit, the beauty of what Randy
said, the beauty of it is we can

execute with such speed and
precision. But the challenge is

that you may be heading towards
a brick wall, except now we're

just going to do it 100 miles an
hour.

Randy Johnston: Yeah. Yeah, so
the question is, bugger

windshield, huh?

Eric Eager: Well, we're going to
make sure that here's the thing,

and this is the missing piece. I
want to give people hope that

this unbridled power, I, like,
you know, like spider man, with

great power, comes right, great
responsibility. Here's the

thing, that there is some
excitement and that you add the

layer of decision intelligence.
This is why you see Gartner and

everybody. You add that as a
layer to complement your AI. And

it does is it continuously
monitors. It helps you see the

emerging risk. It sees the
opportunities. And now it's an

augmentation of decision
confidence. It helps the

advisors and leaders prioritize
actions, what timing, and it

doesn't replace it. Now turbo
charges the advisor and oh, by

the way, it raises the
confidence level of the

decisions, and now the agents
can execute. So this can really

have the impact that I think
we've all been wanting to help

businesses with. And we will, we
really do have a chance to

change the profession.

Brian F. Tankersley, CPA.CITP, CGMA: So
effectively, this is the human

in the loop, the advisor that is
serving as those Spartans at

Thermopylae that are preventing
the hordes of bad ideas from

coming to reality bingo.

Eric Eager: And this is where I
think the this we have always

been business advisors that the
CPA profession has always we've

been what I want to call
invisible advisors. And this is

our opportunity to really
showcase where we have been.

Always. A lot of people get in
the profession because we really

want to help businesses, but we
got so bogged down into in my

history, you know, I'm a tax
guy, I got so bogged down that

by the time I got everything
finished, I didn't have any time

left to really help people. And
now I really think this is

elevating. It's the grand
promotion for everybody. Now, a

lot of people listening are
probably going, I still don't

understand what's the difference
between AI and decision

intelligence. So there's a lot
of things. AI is reactive. It

only reacts when you ask it a
question, and it will answer

questions. It's really text
oriented. But here's the thing,

it's probabilistic. So what that
means is, every time you ask it

a question, you'll get a
different answer. But the

things, the most important thing
that everybody needs to listen

and I think everybody gets it
operates in a black box. You

don't know. So if you're growing
an advisory firm and you're

going AI first, the challenge
you've got is that you may have

10 advisors ask the same
question and get 10 different

answers and oh, by the way,
here's the other thing your

clients can punch in the same
queue and same prompt into AI is

your advisors, inner decision
intelligence, it is now

proactive. It's constantly
probing and seeing the emerging

risk. But it's what we call
deterministic. So what that

means is that, depending on the
same input, you will get the

same output, and it continuously
learns, we call this code. Five

wisdom. So it's continuously
learning, but that's that human

advisor in the loop. It
literally tracks, hey, what

worked, what didn't, and it
keeps the advisor in the loop

for a point of context. And last
but not least, it gives you a

complete audit trail. It's
transparent of how those

decisions and literally we can
get in, it literally creates

decision tokens. So at any point
in the you know, things go by,

you can see how the decisions
were made. This is why I think

the accounting profession will
be so excited about this

possibility, because it fits
within our audit ability and

tracing, but also increases
confidence of what advice we're

giving the client.

Randy Johnston: Yeah, in fact,
Eric, when you first showed this

to me and the audit trails and
how you could track how the AI

was making decisions in the
platform, and how it was showing

things over a longer period of
time and so on. It's like, this

is really smart, and, more
importantly, it is reproducible.

So you know, your whole codified
wisdom is, I've watched your

journey on this, Eric, over the
last few years, because it was

some years ago that you came up
with this business GPS idea and

use the cockpit in the aircraft
system, which, again, makes

great sense. If you've ever
flown an airplane in particular,

it makes all the difference in
the world and the way the GPS is

work. But this decision
intelligence engine has several

different tricks, as I would see
it to it, it's, can you explain

that to our listeners?

Eric Eager: Sure. So the
difference between, like I said,

the difference between AI and
decision intelligence is it is

continuously monitoring so it
has your financial operational

data, and what it does is it
looks for signals and trends.

And it's not just on one plane.
And literally looks across

multiple planes for signals, so
it can see things happening

months at a time, so it begins
to uncover these emerging risk

and opportunities. Because, just
to kind of backtrack a little

bit, even while we started doing
all this, is that we were

wondering we took on this
gigantic challenge of why

businesses are failing at 50%
you know, 50% are going to fail

in the first five years. We hear
this over and over again. So we,

I went to Randy and said, this
has got to change. How in this

world does this continue to
happen? Well, that sent off a

journey of why businesses were
failing. Well, they were

failing, you know. And I'm sure
that a lot of listeners can

think, well, it's cash flow. It
really came down to and I'm glad

everybody's sitting down or
driving your car. It was because

we don't know what we don't
know. And what happens is that

we have to see and the primary
reason is that business owners,

we see the risk too late, and we
make decisions after the fact,

and then we point on the wrong
things. So what decision,

intelligence, or this codified
wisdom, is to monitor where

you're at, see what the road
ahead looks like, and reroute

you to the destination so see
what signals are coming, see the

emerging risk. Have the GPS kind
of thing is recommend the best

routes to take. But here's the
magic, you always have an

advisor in the loop. You have an
advisor going, let me measure

these things and make a
recommendation. You know, work

with the business leader, but
now you got confidence of how

you came to those things. And
then you begin to track what

actions were executed. Because
the other thing Gartner pointed

out is that 80% of decisions
that are executed never get

measured. So you get this teams
you execute and you don't

measure it. So you have this
closed loop of working with your

advisor, measuring what you
know, basically dead,

documenting what actions were
taken in the system, and

continuously measure those
outcomes, and then you learn

what worked best, and then it
creates this closed loop, and

think about that at scale. So
now, as entrepreneurs and this,

you know, guardians, we all
don't have to make the same dumb

mistakes over and over again. I
am a I have a PhD in dumb things

to do in business, and so this
helps elevate everybody across

the board, and it continuously
gets smarter, and it

continuously helps us, guide us
and our clients of what's

working and What works best, if
that makes sense to everybody,

yeah.

Randy Johnston: So this whole
strategy of trying to help

business proactively decide, and
I was reflecting on your mention

of KPIs, because I've been a fan
of KPIs since Harvard introduced

those back in 1992 but the KPIs
were often in. Correctly

selected, not measured, not
really the right things. It took

me better part of 10 years to
get the right KPIs for my own

nmgi business, and now I'm
thinking about it, saying, I

wonder if I've still got the
right KPIs. But in effect, this

is not automatically, but it is
surfacing the right KPIs, the

right actions, and then
monitoring those after the fact,

which is all a pretty big deal.
So in effect, then you said,

scale. So can you explain how
this allows advisory to scale?

Eric Eager: Well, that's a great
question, because the other

thing too is, you guys, you
pointed it out. We've been after

this, solving this problem for
about, you know, going on about

five years now. Well, what we
discovered in this process and

journey, because we were just
dogmatic, we were going to fix

this problem, we were going to
solve this problem, how to help

our profession. What we realized
is that the the whole

profession, the reason that
we're struggling with moving to

advisory. It's what we call a
confidence gap. And it's really

and it makes sense, when you
look at it, is that you've got,

you know, we, most people,
realize this is 75% of the

partners in the profession right
now are retirement age. There is

going to be a massive brain
drain knowledge walking out the

door at the same time, you've
got this next generation of

people with advisors. Here's the
confidence gap problem. I'm a

young advisor, and I want to
start doing advisory Well, I've

got a major client, a major tax
or audit client, a lot of

revenue to the firm. I'm afraid
to make the wrong decision. I

don't know if I have the
confidence to make that call. At

the same time, the senior
partners are going, I man, we

can't risk this. And so you have
the partners that all the

knowledge is tight, and so
everything's going to go through

them. The younger staff are
going, I don't want to make the

call. So this, I'm going to get
this documented and all over the

place, so it creates this huge
gap of I can't move forward and

enter now, the bigger risk is
that now, all of a sudden, you

know, I don't have confidence. I
don't wanna do this. Here's the

bigger issue, is false
confidence. Now the younger

staff and everybody's relying on
AI to give me decisions, and

it's got different answers.
Doesn't prioritize operating

black box. This is a huge risk,
because now I'd rather have low

confidence than false
confidence. Enter the world of

decision intelligence and ran.
I'm sure you have some thoughts

on that. What do you think in
the profession?

Randy Johnston: You've got me
headed down all sorts of

different paths with you here,
Eric, because I've said on this

podcast before that for advisory
to work, I used to think it took

gray hair. And fact, the matter
is, it's the right tools that

really make the difference. Kind
of number one, observation

number two, the risk of the
firm, as you pointed out, is

very high when I see CPA and
accountants who have great

advisory skills. It's a
beautiful thing, but there's so

many that have been so focused
on tax and audit because that's

where they were making the
money. Didn't really have time

to do these other tasks. Now, if
we can do this at scale, that's

also another huge opportunity.
Then third, it Brian and I will

continue to talk to you about
different advisory approaches

that are out there. In my mind
right now, for impact data has

the most scalable, logical,
repeatable advisory offering in

the market. And you know, things
are changing quickly, but I can

tell you, there's a lot of
discussion around advisory, of

which I have labeled fake
advisory, where people are doing

client accounting services and
financial reporting and thinking

it's advisory, and it's not that
at all, or the opposite end of

the spectrum, They're doing CFO
services, and it's not really

advisory, either. So you know,
this whole tipping point is upon

us. And you know, Eric, you've
just toned it again with the

shift in labor that's going to
happen and all this loss of so

much knowledge. I'm really
concerned about that as well.

Now I think you've written a
paper on this topic as well, and

I might encourage our listeners
to try to pick up that paper.

It's called Why decision
intelligence will power the next

generation of Cavs. And you
know, it's almost like, I wish I

could have you take CAS out of
the title, Eric, but I do that.

You know, many of our firms have
just been building these client

accounting services operations,
and they're trying to extend it

with advisory. And CAS and
advisory are getting all mixed

up in the terminology. We're
almost gonna have to invent a

new term. But you know, for the
moment, I'm going to go with

decision Intel. Budgets for
advisory.

Eric Eager: I think I like that.
So I like that. I may have to

modify the title there.

Randy Johnston: So final,
parting thoughts you might have

for our listeners today, Eric,

Eric Eager: you know, here's the
thing. There's a couple things,

and there is an approach where
there is a lot of nervousness in

the profession that our
traditional, you know, service

line offerings are becoming much
more automated. The margins

we're starting to see shrink.
We're starting to have, you

know, it's beginning to
commoditize. And I know that

people have said, I've heard
that storm. We've weathered that

storm years before and
everything, but I've had the

chance to work with Randy and
Brian and, you know, Barry,

Milan song and Gary, a lot of
the leading professions, and

they are all saying the storm is
coming, and it can be gloom and

doom or excitement. And I'm on
the abundant side and saying

this is an exciting time for us.
There is now we can unleash the

power of our advisory
capabilities, our impact. And

I'm going to say boldly that you
know that the accounting

profession is going to change
the world, and I want to believe

that. And so for those who want
to join the movement and join

the bandwagon of this is an
exciting time. You know,

download the white paper. I'd
love to continue having

conversations, because I'm
excited about the opportunities

that lie ahead for the
profession, because I really

think there's no other
profession globally that can

change the odds and have such an
impact on so many businesses

globally, we just had to wait
for the technology to catch up,

to shine a spotlight on the true
work that we've been doing for

decades. Yeah, and so I
appreciate your time, and thanks

for letting me have a
conversation today. So Brian,

Randy Johnston: you've been
awful quiet today. Any other

parting thoughts from either
side?

Brian F. Tankersley, CPA.CITP, CGMA: Well,
I think it's very important to,

you know, to address this
confidence gap that we have

between the experienced partners
that have taken risks and have

learned from them, and the
junior staff that are just

trying to keep their, you know,
trying to figure out what their

career looks like. Okay? And the
thing I would say here is that,

first off, I think you're
absolutely right, Eric, that

validating the data that comes
out of AI and having that human

in the loop is an essential part
here. And I think that is a

significant definition of what
advisory looks like to me, you

know, because there is some
measurement here, you know, as

this goes back, I mean, I think
about, I think I was fortunate

enough to watch my great uncle
coach my father in

entrepreneurship when I was a
kid. And one of the things I

remember my great uncle saying
to my dad was, my great uncle

was a very successful
entrepreneur and engineer, and

has, you know, founded a
business that now has sales in

the hundreds of millions of
dollars. I will say that the

thing that was so cool about
what he said was that he said

that, you know, if you make a
mistake, for God's sake, tell

everybody about it, because we
don't want to make the same old

mistakes. We want to make new
and interesting ones. And that's

the thing. I think that's
critical for this, because, you

know, you don't your part, your
partners are very quiet, and

they don't share where they took
risks and explain that, and

explain the thinking and explain
the calculus that's happening in

the background. And these staff
are sitting out here, and it

looks like, you know, the
partner is some Harry Potter

here. No, he's taken a lot of
small chances over the years,

increasingly bigger, and then
they, he or she's figured out

that this is how we make, this
is how we do here. And the

things is that we've all been
taught that accounting is black

and white, but the reality of it
is that there are gambles that

we have to take, just like when
you're playing chess, when

you're playing any kind of game
with anybody. You know there is

a risk associated with every
move you make, and the bet the

easiest way to lose is to stop
going forward altogether. So

very cool, Eric. I love what
you're doing, and I think it's I

agree with you. I think the
accounting profession is going

to change the world. I think
it's going to be different than

we all think it is. But at the
end of the day, somebody's got

to be like I said earlier, those
300 Spartans at Thermopylae that

keep the hallucinations from
going through and turning into

worse decisions than we could
ever dream

Randy Johnston: up as humans. So
Brian and Eric, such a pleasure

to spend time with you. So one
parting thought from my side

today, we recognize how much is
going to change on the

compliance side, and I can tell
you that this season just

completed on AI tax has been a
pretty significant move. We're

going to see transactions of all
kinds automated in client

accounting services, in audit
and in tax. And what that will

do for us is give us time for
these other. Activities, and to

me, that's a really big deal. So
you're going to see me continue

throughout the year to record my
recommend advisory platforms,

and you'll start hearing me talk
more about the interstitium,

because I think that's what the
accountants are to the

profession. A delight having you
here today, join us again for

another accounting Technology
Lab. Good day.

Brian F. Tankersley, CPA.CITP, CGMA: Thank
you for sharing your time with

us. We'll be back next Saturday
with a new episode of the

technology lab from CPA practice
advisor. Have a great week.