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Brian F. Tankersley, CPA.CITP, CGMA: Ryan,
welcome to the accounting
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Technology Lab sponsored by CPA
practice advisor, with your
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hosts, Randy Johnston and Brian
Tankersley, hi everybody. It's
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Brian, working hard at the lab
today, but I thought I would let
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you know that do have a quick
announcement? We have a
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giveaway. We're going to be
giving away one Rico, scan, snap
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IX, 2500 receipt edition. We're
going to draw. We're going to
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make the drawing right after
April 30. No purchase required.
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Suggested Retail value, $599
this is a one has one touch
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simplicity, and our friends at
Rico graciously provided it to
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us with automatic invoice OCR,
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small and curl documents and
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minute, duplex scanning. It
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searchable digital data in
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register, it's CPA te.ch/scan
snap. The rules are at CPA
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te.ch/rules and the privacy
policy is at CPA, te.ch,
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forward, slash, scanner, dash,
privacy. And for those of you
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attending the video, attending
the video version of this, I've
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actually put on the screen now a
QR code that you can capture and
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use to register for the for the
again, for the scanner. Giveaway
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again. We're giving one away.
We're going to give it away
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again right after April 30 and
again. You must, you must be an
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accounting professional when all
the rules again are at CPA te
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CH, CPA te.ch/rules so anyway,
with that, thanks for joining
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us, and here we are back in the
lab.
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Randy Johnston: Welcome to the
accounting Technology Lab. I'm
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your host, Randy Johnston, with
co host Brian Tankersley, and we
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are so pleased to have a guest
today, Eric eager. Now, I've
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known Eric for 20 plus years
from his old days at a
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predecessor company which we'd
recommended to you, biznet, but
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about seven or eight years ago,
Eric reached out to me and said,
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You know, I've got a new idea.
And I listened to him, and I
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said, you know, Eric, you could
be playing golf. And he said,
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No, I want to make a difference.
I want to help small businesses
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succeed, and I've got a great
idea to do it. It turns out, I
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think he did, and over the last
years, he's been building a
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platform called for impact data,
the number four impact data,
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Eric, welcome to our podcast
today. Would you like to give a
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little bit of introduction on
yourself now?
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Eric Eager: Great, Ray, thank
you for having me on the show
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again. I am a CPA, and I feel
like we been working on this
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challenge of, how do we change
the odds for business owners,
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and then at the same time, how
do we elevate the profession and
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recognize the work and the
impact that we have on
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businesses? And so we've been
working really hard on this. How
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do we help the shift to
advisory? And I think that we
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have broken the code, cracked
the code, as they say, and we'll
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talk more about it, but, man, we
are super excited to tell people
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more about it and help the
transformation in the
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profession.
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Randy Johnston: Very good. Well,
for our dedicated listeners, you
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may recognize that Brian and I
have recorded a session on for
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impact data in the past, but oh
my, it is so different.
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Brian F. Tankersley, CPA.CITP, CGMA: So,
you know, Brian, it was like
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four years
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Randy Johnston: ago, so
different. So, as you may know,
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has probably reviewed more small
accounting products than you
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have ever seen in the past. And
just to give you a perspective
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on that, you know, we go back to
the days of the peach trees. In
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fact, I was actually drawn into
a recent interview from the
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Privacy Forum, and I couldn't
believe that I heard an old
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lotus, 123, name. I didn't
realize he had helped found the
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Privacy Forum. But again, we're
lucky enough to have had the
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long haul with the some of these
very well known products of the
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past as well some of the new
products of today, so the
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digits, which we've done
podcasts on, and others. So
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we're really shifting from
transactional accounting and
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financial reporting into
something that is quite
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different. And you know, the
team at for impact data have
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landed on the term decision
intelligence, but it really
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probably evolved from a bit of,
I'll say, observation by Gartner
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Group. So Eric, I might ask you
to take a moment and just help
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our listeners understand what
decision intelligence is.
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Eric Eager: Well, it's going to
be, you know, here's the thing
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is that it is the next evolution
of AI, and it's not replacing
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AI. It's kind of the things that
we've we've been working on. And
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as you guys pointed out for the
last four or five years, and we
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didn't realize we were building
it. But what decision
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intelligence does is that it
takes the combination of AI,
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data science, business
intelligence and humans
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expertise, it literally gives
you the ability to codify the
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experiences of others, but the
differences here is that what AI
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is what they call probabilistic
and text driven. Decision
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intelligence is deterministic.
It will literally tell you
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statistically. Here are the best
actions to take, taking all
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things considered, and it
provides you an audit trail of
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how that decision was come to so
it is really this ability to
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take from probabilities and what
you think to literally what
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decisions are going to give you
the highest probability of
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success.
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Randy Johnston: And for those of
you who have attended a lot of
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our k2 events. You might recall
that over a decade ago, it was
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2015, and 16, we were presenting
heavily on data science, and for
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those of you where I actually
did your on site tech
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assessments, I frequently
recommended that you had a data
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scientist in that window. Now, a
lot of this AI that we're
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dealing with as you are,
probably also where it's been
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around since the late 50s. 1958
is when AI started. But many
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people think AI started when
chat GPT was released in
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November of 22 you know, his
granddaughter from New York
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says, grandpa, that not be the
plan. That is not the plan.
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That's not how it happened. But
in about 2010 we started seeing
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a lot of these pattern
recognition and pattern matching
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and machine learning and this
evolution into the reporting
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tools that Eric and his team
used because they took as their
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basis Power BI and wanted to
have drillable dashboards in
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some of the earliest models.
That was interesting, but it's
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now a combination of for
decision intelligence, all of
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these things, of AI and data
science and behavioral and so
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forth. So you know, Eric, I know
you've been looking at the
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Gartner content on this. What's
Gartner have to say
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Eric Eager: on this? Well,
Gartner says that, literally, if
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you haven't heard of decision
intelligence, you're going to
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hear quite a bit about it in the
coming years. And here's what it
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is, the reason being, and the
thing that I'm trying to help
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elevate is that while you're
hearing all this AI decisions,
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the challenge is that it is
incredibly powerful, but it's
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changed. The answers are
changing. Every time you ask a
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question, it is a black box. And
what's happening is that more
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and more as we move into
advisory in these other pieces,
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it is going to cause,
unbeknownst, what we call false
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confidence and advisory, and
they are projecting it's going
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to cause financial and
reputational loss simply from
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the fact of human bias, ability
of critical thinking and aos AI
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sycophancy, it is still as much
as they're trying it is going to
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please you. And 2030 Yeah, I'm
sorry, go ahead.
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Brian F. Tankersley, CPA.CITP, CGMA: So
effectively, we're going to be
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lemmings running off a cliff.
Because AI said, Hey, wouldn't
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it be a great idea if you ran
off a cliff Exactly?
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Eric Eager: Now, here's the
thing, though, AI, if managed
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correctly and you compliment it,
it will unleash capabilities
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that all the positives and the
excitement, and why I'm excited
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about it, and these models, by
2030 it will be five times more
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trusted. It will be faster in
governing decisions than
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ungoverned decisions. And this
is why you're going to hear
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these things, because, and I'll
talk a little bit about, you
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know, why is this happening?
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Randy Johnston: Well, but you
know, on that point, Eric, I
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think the good and bad we've
talked about that with past all
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technology can be used for good
or bad. But the bad number that
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we didn't quote for you is that
by 2027, 25% of the decisions
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will actually have financial
impact in a negative way. That's
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a big deal, because 2027 is a
lot closer than you might think
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Eric Eager: well, and I'm glad
you pointed that, Alex, that
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sometimes I forget we have audio
listeners and not video
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listeners. So yeah, thank you
for pointing it out, because
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that and I've heard and I've
talked to, you know, profession
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and AI leaders throughout the
world, and they say that number
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may be low, that it can be
significantly higher if we don't
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watch it. So I'm glad you point
that out and in. So why is this
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in? Important. Well, you know
what's happening is, AI, is the
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world and velocity of business
is accelerating way before it's
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happening so fast that we're all
having to react and do things
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well. Ai, you know, the way that
we make decisions today is that
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before you know, we have these
analysts that would bring
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reports to us, and as leaders,
we would take all this
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information and have to
prioritize and risk and see
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what's short term and long term,
and then you had to make the
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call, and then you go hand it
down to your operational team.
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Well, what AI? And the
excitement about AI, it is
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surfacing so many options now
that you're turbo charging your
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analyst? Well, what that's doing
is that now it is accelerating
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all these options to leaders,
and it still doesn't tell you.
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It doesn't give you the well,
all these options for my
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company, which one takes
precedence? What time do we need
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to implement? What's the trade
offs, if we do this versus this,
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I still have to make those
calls, and that's myself and my
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advisor. Because we're always
going to have the need for
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advisors. No matter what the
technology does, we're still
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going to need that human
advisor, and it's going to cause
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decision fatigue. And so all of
a sudden, we're going to make
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the call. And now, if you add in
AI agents to that, the speed of
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exit, the beauty of what Randy
said, the beauty of it is we can
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execute with such speed and
precision. But the challenge is
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that you may be heading towards
a brick wall, except now we're
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just going to do it 100 miles an
hour.
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Randy Johnston: Yeah. Yeah, so
the question is, bugger
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windshield, huh?
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Eric Eager: Well, we're going to
make sure that here's the thing,
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and this is the missing piece. I
want to give people hope that
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this unbridled power, I, like,
you know, like spider man, with
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great power, comes right, great
responsibility. Here's the
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thing, that there is some
excitement and that you add the
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layer of decision intelligence.
This is why you see Gartner and
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everybody. You add that as a
layer to complement your AI. And
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it does is it continuously
monitors. It helps you see the
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emerging risk. It sees the
opportunities. And now it's an
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augmentation of decision
confidence. It helps the
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advisors and leaders prioritize
actions, what timing, and it
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doesn't replace it. Now turbo
charges the advisor and oh, by
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the way, it raises the
confidence level of the
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decisions, and now the agents
can execute. So this can really
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have the impact that I think
we've all been wanting to help
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businesses with. And we will, we
really do have a chance to
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change the profession.
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Brian F. Tankersley, CPA.CITP, CGMA: So
effectively, this is the human
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in the loop, the advisor that is
serving as those Spartans at
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Thermopylae that are preventing
the hordes of bad ideas from
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coming to reality bingo.
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Eric Eager: And this is where I
think the this we have always
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been business advisors that the
CPA profession has always we've
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been what I want to call
invisible advisors. And this is
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our opportunity to really
showcase where we have been.
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Always. A lot of people get in
the profession because we really
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want to help businesses, but we
got so bogged down into in my
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history, you know, I'm a tax
guy, I got so bogged down that
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by the time I got everything
finished, I didn't have any time
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left to really help people. And
now I really think this is
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elevating. It's the grand
promotion for everybody. Now, a
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lot of people listening are
probably going, I still don't
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understand what's the difference
between AI and decision
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intelligence. So there's a lot
of things. AI is reactive. It
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only reacts when you ask it a
question, and it will answer
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questions. It's really text
oriented. But here's the thing,
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it's probabilistic. So what that
means is, every time you ask it
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a question, you'll get a
different answer. But the
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things, the most important thing
that everybody needs to listen
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and I think everybody gets it
operates in a black box. You
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don't know. So if you're growing
an advisory firm and you're
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going AI first, the challenge
you've got is that you may have
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10 advisors ask the same
question and get 10 different
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answers and oh, by the way,
here's the other thing your
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clients can punch in the same
queue and same prompt into AI is
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your advisors, inner decision
intelligence, it is now
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proactive. It's constantly
probing and seeing the emerging
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risk. But it's what we call
deterministic. So what that
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means is that, depending on the
same input, you will get the
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same output, and it continuously
learns, we call this code. Five
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wisdom. So it's continuously
learning, but that's that human
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advisor in the loop. It
literally tracks, hey, what
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worked, what didn't, and it
keeps the advisor in the loop
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for a point of context. And last
but not least, it gives you a
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complete audit trail. It's
transparent of how those
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decisions and literally we can
get in, it literally creates
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decision tokens. So at any point
in the you know, things go by,
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you can see how the decisions
were made. This is why I think
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the accounting profession will
be so excited about this
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possibility, because it fits
within our audit ability and
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tracing, but also increases
confidence of what advice we're
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giving the client.
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Randy Johnston: Yeah, in fact,
Eric, when you first showed this
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to me and the audit trails and
how you could track how the AI
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was making decisions in the
platform, and how it was showing
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things over a longer period of
time and so on. It's like, this
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is really smart, and, more
importantly, it is reproducible.
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So you know, your whole codified
wisdom is, I've watched your
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journey on this, Eric, over the
last few years, because it was
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some years ago that you came up
with this business GPS idea and
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use the cockpit in the aircraft
system, which, again, makes
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great sense. If you've ever
flown an airplane in particular,
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it makes all the difference in
the world and the way the GPS is
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work. But this decision
intelligence engine has several
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different tricks, as I would see
it to it, it's, can you explain
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that to our listeners?
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Eric Eager: Sure. So the
difference between, like I said,
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the difference between AI and
decision intelligence is it is
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continuously monitoring so it
has your financial operational
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data, and what it does is it
looks for signals and trends.
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And it's not just on one plane.
And literally looks across
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multiple planes for signals, so
it can see things happening
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months at a time, so it begins
to uncover these emerging risk
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and opportunities. Because, just
to kind of backtrack a little
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bit, even while we started doing
all this, is that we were
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wondering we took on this
gigantic challenge of why
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businesses are failing at 50%
you know, 50% are going to fail
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in the first five years. We hear
this over and over again. So we,
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I went to Randy and said, this
has got to change. How in this
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world does this continue to
happen? Well, that sent off a
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journey of why businesses were
failing. Well, they were
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failing, you know. And I'm sure
that a lot of listeners can
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think, well, it's cash flow. It
really came down to and I'm glad
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everybody's sitting down or
driving your car. It was because
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we don't know what we don't
know. And what happens is that
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we have to see and the primary
reason is that business owners,
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we see the risk too late, and we
make decisions after the fact,
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and then we point on the wrong
things. So what decision,
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intelligence, or this codified
wisdom, is to monitor where
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you're at, see what the road
ahead looks like, and reroute
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you to the destination so see
what signals are coming, see the
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emerging risk. Have the GPS kind
of thing is recommend the best
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routes to take. But here's the
magic, you always have an
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advisor in the loop. You have an
advisor going, let me measure
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these things and make a
recommendation. You know, work
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with the business leader, but
now you got confidence of how
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you came to those things. And
then you begin to track what
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actions were executed. Because
the other thing Gartner pointed
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out is that 80% of decisions
that are executed never get
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measured. So you get this teams
you execute and you don't
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measure it. So you have this
closed loop of working with your
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advisor, measuring what you
know, basically dead,
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documenting what actions were
taken in the system, and
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continuously measure those
outcomes, and then you learn
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what worked best, and then it
creates this closed loop, and
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think about that at scale. So
now, as entrepreneurs and this,
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you know, guardians, we all
don't have to make the same dumb
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mistakes over and over again. I
am a I have a PhD in dumb things
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to do in business, and so this
helps elevate everybody across
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the board, and it continuously
gets smarter, and it
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continuously helps us, guide us
and our clients of what's
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working and What works best, if
that makes sense to everybody,
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yeah.
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Randy Johnston: So this whole
strategy of trying to help
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business proactively decide, and
I was reflecting on your mention
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of KPIs, because I've been a fan
of KPIs since Harvard introduced
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those back in 1992 but the KPIs
were often in. Correctly
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selected, not measured, not
really the right things. It took
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me better part of 10 years to
get the right KPIs for my own
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nmgi business, and now I'm
thinking about it, saying, I
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wonder if I've still got the
right KPIs. But in effect, this
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is not automatically, but it is
surfacing the right KPIs, the
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right actions, and then
monitoring those after the fact,
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which is all a pretty big deal.
So in effect, then you said,
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scale. So can you explain how
this allows advisory to scale?
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Eric Eager: Well, that's a great
question, because the other
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thing too is, you guys, you
pointed it out. We've been after
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this, solving this problem for
about, you know, going on about
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five years now. Well, what we
discovered in this process and
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journey, because we were just
dogmatic, we were going to fix
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this problem, we were going to
solve this problem, how to help
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our profession. What we realized
is that the the whole
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profession, the reason that
we're struggling with moving to
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advisory. It's what we call a
confidence gap. And it's really
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and it makes sense, when you
look at it, is that you've got,
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you know, we, most people,
realize this is 75% of the
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partners in the profession right
now are retirement age. There is
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going to be a massive brain
drain knowledge walking out the
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door at the same time, you've
got this next generation of
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people with advisors. Here's the
confidence gap problem. I'm a
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young advisor, and I want to
start doing advisory Well, I've
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got a major client, a major tax
or audit client, a lot of
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revenue to the firm. I'm afraid
to make the wrong decision. I
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don't know if I have the
confidence to make that call. At
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the same time, the senior
partners are going, I man, we
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can't risk this. And so you have
the partners that all the
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knowledge is tight, and so
everything's going to go through
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them. The younger staff are
going, I don't want to make the
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call. So this, I'm going to get
this documented and all over the
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place, so it creates this huge
gap of I can't move forward and
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enter now, the bigger risk is
that now, all of a sudden, you
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know, I don't have confidence. I
don't wanna do this. Here's the
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bigger issue, is false
confidence. Now the younger
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staff and everybody's relying on
AI to give me decisions, and
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it's got different answers.
Doesn't prioritize operating
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black box. This is a huge risk,
because now I'd rather have low
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confidence than false
confidence. Enter the world of
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decision intelligence and ran.
I'm sure you have some thoughts
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on that. What do you think in
the profession?
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Randy Johnston: You've got me
headed down all sorts of
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different paths with you here,
Eric, because I've said on this
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podcast before that for advisory
to work, I used to think it took
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gray hair. And fact, the matter
is, it's the right tools that
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really make the difference. Kind
of number one, observation
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number two, the risk of the
firm, as you pointed out, is
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very high when I see CPA and
accountants who have great
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advisory skills. It's a
beautiful thing, but there's so
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many that have been so focused
on tax and audit because that's
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where they were making the
money. Didn't really have time
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to do these other tasks. Now, if
we can do this at scale, that's
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also another huge opportunity.
Then third, it Brian and I will
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continue to talk to you about
different advisory approaches
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that are out there. In my mind
right now, for impact data has
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the most scalable, logical,
repeatable advisory offering in
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the market. And you know, things
are changing quickly, but I can
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tell you, there's a lot of
discussion around advisory, of
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which I have labeled fake
advisory, where people are doing
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client accounting services and
financial reporting and thinking
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it's advisory, and it's not that
at all, or the opposite end of
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the spectrum, They're doing CFO
services, and it's not really
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advisory, either. So you know,
this whole tipping point is upon
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us. And you know, Eric, you've
just toned it again with the
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shift in labor that's going to
happen and all this loss of so
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much knowledge. I'm really
concerned about that as well.
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Now I think you've written a
paper on this topic as well, and
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I might encourage our listeners
to try to pick up that paper.
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It's called Why decision
intelligence will power the next
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generation of Cavs. And you
know, it's almost like, I wish I
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could have you take CAS out of
the title, Eric, but I do that.
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You know, many of our firms have
just been building these client
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accounting services operations,
and they're trying to extend it
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with advisory. And CAS and
advisory are getting all mixed
381
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up in the terminology. We're
almost gonna have to invent a
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new term. But you know, for the
moment, I'm going to go with
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decision Intel. Budgets for
advisory.
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Eric Eager: I think I like that.
So I like that. I may have to
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modify the title there.
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Randy Johnston: So final,
parting thoughts you might have
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for our listeners today, Eric,
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Eric Eager: you know, here's the
thing. There's a couple things,
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and there is an approach where
there is a lot of nervousness in
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the profession that our
traditional, you know, service
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line offerings are becoming much
more automated. The margins
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we're starting to see shrink.
We're starting to have, you
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know, it's beginning to
commoditize. And I know that
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people have said, I've heard
that storm. We've weathered that
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storm years before and
everything, but I've had the
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chance to work with Randy and
Brian and, you know, Barry,
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Milan song and Gary, a lot of
the leading professions, and
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00:25:48,160 --> 00:25:53,680
they are all saying the storm is
coming, and it can be gloom and
399
00:25:53,680 --> 00:25:57,880
doom or excitement. And I'm on
the abundant side and saying
400
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this is an exciting time for us.
There is now we can unleash the
401
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power of our advisory
capabilities, our impact. And
402
00:26:07,680 --> 00:26:12,060
I'm going to say boldly that you
know that the accounting
403
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profession is going to change
the world, and I want to believe
404
00:26:15,660 --> 00:26:20,160
that. And so for those who want
to join the movement and join
405
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the bandwagon of this is an
exciting time. You know,
406
00:26:24,380 --> 00:26:27,140
download the white paper. I'd
love to continue having
407
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conversations, because I'm
excited about the opportunities
408
00:26:31,220 --> 00:26:34,220
that lie ahead for the
profession, because I really
409
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think there's no other
profession globally that can
410
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change the odds and have such an
impact on so many businesses
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00:26:42,520 --> 00:26:46,420
globally, we just had to wait
for the technology to catch up,
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to shine a spotlight on the true
work that we've been doing for
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decades. Yeah, and so I
appreciate your time, and thanks
414
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for letting me have a
conversation today. So Brian,
415
00:26:56,980 --> 00:26:58,720
Randy Johnston: you've been
awful quiet today. Any other
416
00:26:58,720 --> 00:26:59,980
parting thoughts from either
side?
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Brian F. Tankersley, CPA.CITP, CGMA: Well,
I think it's very important to,
418
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you know, to address this
confidence gap that we have
419
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between the experienced partners
that have taken risks and have
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learned from them, and the
junior staff that are just
421
00:27:12,900 --> 00:27:15,180
trying to keep their, you know,
trying to figure out what their
422
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career looks like. Okay? And the
thing I would say here is that,
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first off, I think you're
absolutely right, Eric, that
424
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validating the data that comes
out of AI and having that human
425
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in the loop is an essential part
here. And I think that is a
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significant definition of what
advisory looks like to me, you
427
00:27:32,300 --> 00:27:34,880
know, because there is some
measurement here, you know, as
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this goes back, I mean, I think
about, I think I was fortunate
429
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enough to watch my great uncle
coach my father in
430
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entrepreneurship when I was a
kid. And one of the things I
431
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remember my great uncle saying
to my dad was, my great uncle
432
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was a very successful
entrepreneur and engineer, and
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has, you know, founded a
business that now has sales in
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the hundreds of millions of
dollars. I will say that the
435
00:27:58,960 --> 00:28:02,640
thing that was so cool about
what he said was that he said
436
00:28:02,640 --> 00:28:06,780
that, you know, if you make a
mistake, for God's sake, tell
437
00:28:06,780 --> 00:28:10,020
everybody about it, because we
don't want to make the same old
438
00:28:10,020 --> 00:28:13,980
mistakes. We want to make new
and interesting ones. And that's
439
00:28:13,980 --> 00:28:17,160
the thing. I think that's
critical for this, because, you
440
00:28:17,160 --> 00:28:21,440
know, you don't your part, your
partners are very quiet, and
441
00:28:21,440 --> 00:28:25,160
they don't share where they took
risks and explain that, and
442
00:28:25,160 --> 00:28:28,400
explain the thinking and explain
the calculus that's happening in
443
00:28:28,400 --> 00:28:31,400
the background. And these staff
are sitting out here, and it
444
00:28:31,400 --> 00:28:33,860
looks like, you know, the
partner is some Harry Potter
445
00:28:33,860 --> 00:28:37,640
here. No, he's taken a lot of
small chances over the years,
446
00:28:37,640 --> 00:28:41,200
increasingly bigger, and then
they, he or she's figured out
447
00:28:41,380 --> 00:28:46,420
that this is how we make, this
is how we do here. And the
448
00:28:46,420 --> 00:28:48,820
things is that we've all been
taught that accounting is black
449
00:28:48,820 --> 00:28:53,140
and white, but the reality of it
is that there are gambles that
450
00:28:53,140 --> 00:28:55,360
we have to take, just like when
you're playing chess, when
451
00:28:55,360 --> 00:28:58,720
you're playing any kind of game
with anybody. You know there is
452
00:28:58,720 --> 00:29:02,400
a risk associated with every
move you make, and the bet the
453
00:29:02,400 --> 00:29:06,540
easiest way to lose is to stop
going forward altogether. So
454
00:29:06,540 --> 00:29:10,080
very cool, Eric. I love what
you're doing, and I think it's I
455
00:29:10,080 --> 00:29:12,240
agree with you. I think the
accounting profession is going
456
00:29:12,240 --> 00:29:14,880
to change the world. I think
it's going to be different than
457
00:29:14,880 --> 00:29:18,060
we all think it is. But at the
end of the day, somebody's got
458
00:29:18,060 --> 00:29:22,160
to be like I said earlier, those
300 Spartans at Thermopylae that
459
00:29:22,160 --> 00:29:24,920
keep the hallucinations from
going through and turning into
460
00:29:24,920 --> 00:29:27,020
worse decisions than we could
ever dream
461
00:29:27,020 --> 00:29:31,160
Randy Johnston: up as humans. So
Brian and Eric, such a pleasure
462
00:29:31,160 --> 00:29:35,120
to spend time with you. So one
parting thought from my side
463
00:29:35,120 --> 00:29:39,800
today, we recognize how much is
going to change on the
464
00:29:39,800 --> 00:29:43,600
compliance side, and I can tell
you that this season just
465
00:29:43,600 --> 00:29:48,700
completed on AI tax has been a
pretty significant move. We're
466
00:29:48,700 --> 00:29:52,540
going to see transactions of all
kinds automated in client
467
00:29:52,540 --> 00:29:56,560
accounting services, in audit
and in tax. And what that will
468
00:29:56,560 --> 00:30:01,620
do for us is give us time for
these other. Activities, and to
469
00:30:01,620 --> 00:30:06,480
me, that's a really big deal. So
you're going to see me continue
470
00:30:06,480 --> 00:30:11,820
throughout the year to record my
recommend advisory platforms,
471
00:30:12,120 --> 00:30:15,060
and you'll start hearing me talk
more about the interstitium,
472
00:30:15,060 --> 00:30:18,060
because I think that's what the
accountants are to the
473
00:30:18,060 --> 00:30:23,300
profession. A delight having you
here today, join us again for
474
00:30:23,300 --> 00:30:25,760
another accounting Technology
Lab. Good day.
475
00:30:31,100 --> 00:30:32,480
Brian F. Tankersley, CPA.CITP, CGMA: Thank
you for sharing your time with
476
00:30:32,480 --> 00:30:35,960
us. We'll be back next Saturday
with a new episode of the
477
00:30:35,960 --> 00:30:40,700
technology lab from CPA practice
advisor. Have a great week.
00:00:00,780 --> 00:00:02,040
Brian F. Tankersley, CPA.CITP, CGMA: Ryan,
welcome to the accounting
2
00:00:02,040 --> 00:00:07,200
Technology Lab sponsored by CPA
practice advisor, with your
3
00:00:07,200 --> 00:00:14,100
hosts, Randy Johnston and Brian
Tankersley, hi everybody. It's
4
00:00:14,100 --> 00:00:16,980
Brian, working hard at the lab
today, but I thought I would let
5
00:00:16,980 --> 00:00:20,240
you know that do have a quick
announcement? We have a
6
00:00:20,240 --> 00:00:23,780
giveaway. We're going to be
giving away one Rico, scan, snap
7
00:00:23,780 --> 00:00:27,020
IX, 2500 receipt edition. We're
going to draw. We're going to
8
00:00:27,020 --> 00:00:30,980
make the drawing right after
April 30. No purchase required.
9
00:00:30,980 --> 00:00:35,960
Suggested Retail value, $599
this is a one has one touch
10
00:00:35,960 --> 00:00:38,900
simplicity, and our friends at
Rico graciously provided it to
11
00:00:38,900 --> 00:00:43,120
us with automatic invoice OCR,
detachable receipt guide for
12
00:00:43,120 --> 00:00:47,020
small and curl documents and
lightning fast, 45 page a
13
00:00:47,020 --> 00:00:50,380
minute, duplex scanning. It
transforms paperwork into clean,
14
00:00:50,380 --> 00:00:53,020
searchable digital data in
seconds. If you want to
15
00:00:53,020 --> 00:00:58,720
register, it's CPA te.ch/scan
snap. The rules are at CPA
16
00:00:58,720 --> 00:01:03,240
te.ch/rules and the privacy
policy is at CPA, te.ch,
17
00:01:04,200 --> 00:01:07,500
forward, slash, scanner, dash,
privacy. And for those of you
18
00:01:07,500 --> 00:01:10,680
attending the video, attending
the video version of this, I've
19
00:01:10,680 --> 00:01:15,300
actually put on the screen now a
QR code that you can capture and
20
00:01:15,300 --> 00:01:20,900
use to register for the for the
again, for the scanner. Giveaway
21
00:01:21,140 --> 00:01:23,420
again. We're giving one away.
We're going to give it away
22
00:01:23,480 --> 00:01:28,880
again right after April 30 and
again. You must, you must be an
23
00:01:28,880 --> 00:01:32,240
accounting professional when all
the rules again are at CPA te
24
00:01:32,240 --> 00:01:38,480
CH, CPA te.ch/rules so anyway,
with that, thanks for joining
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00:01:38,480 --> 00:01:40,240
us, and here we are back in the
lab.
26
00:01:41,140 --> 00:01:43,060
Randy Johnston: Welcome to the
accounting Technology Lab. I'm
27
00:01:43,060 --> 00:01:46,780
your host, Randy Johnston, with
co host Brian Tankersley, and we
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are so pleased to have a guest
today, Eric eager. Now, I've
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known Eric for 20 plus years
from his old days at a
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predecessor company which we'd
recommended to you, biznet, but
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about seven or eight years ago,
Eric reached out to me and said,
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You know, I've got a new idea.
And I listened to him, and I
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said, you know, Eric, you could
be playing golf. And he said,
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No, I want to make a difference.
I want to help small businesses
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succeed, and I've got a great
idea to do it. It turns out, I
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think he did, and over the last
years, he's been building a
37
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platform called for impact data,
the number four impact data,
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Eric, welcome to our podcast
today. Would you like to give a
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little bit of introduction on
yourself now?
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Eric Eager: Great, Ray, thank
you for having me on the show
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again. I am a CPA, and I feel
like we been working on this
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challenge of, how do we change
the odds for business owners,
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and then at the same time, how
do we elevate the profession and
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recognize the work and the
impact that we have on
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businesses? And so we've been
working really hard on this. How
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do we help the shift to
advisory? And I think that we
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00:03:00,240 --> 00:03:04,860
have broken the code, cracked
the code, as they say, and we'll
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talk more about it, but, man, we
are super excited to tell people
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more about it and help the
transformation in the
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profession.
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Randy Johnston: Very good. Well,
for our dedicated listeners, you
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may recognize that Brian and I
have recorded a session on for
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impact data in the past, but oh
my, it is so different.
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Brian F. Tankersley, CPA.CITP, CGMA: So,
you know, Brian, it was like
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four years
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Randy Johnston: ago, so
different. So, as you may know,
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has probably reviewed more small
accounting products than you
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have ever seen in the past. And
just to give you a perspective
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on that, you know, we go back to
the days of the peach trees. In
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fact, I was actually drawn into
a recent interview from the
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Privacy Forum, and I couldn't
believe that I heard an old
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lotus, 123, name. I didn't
realize he had helped found the
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Privacy Forum. But again, we're
lucky enough to have had the
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long haul with the some of these
very well known products of the
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past as well some of the new
products of today, so the
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digits, which we've done
podcasts on, and others. So
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we're really shifting from
transactional accounting and
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financial reporting into
something that is quite
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different. And you know, the
team at for impact data have
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landed on the term decision
intelligence, but it really
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probably evolved from a bit of,
I'll say, observation by Gartner
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Group. So Eric, I might ask you
to take a moment and just help
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our listeners understand what
decision intelligence is.
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Eric Eager: Well, it's going to
be, you know, here's the thing
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is that it is the next evolution
of AI, and it's not replacing
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AI. It's kind of the things that
we've we've been working on. And
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as you guys pointed out for the
last four or five years, and we
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didn't realize we were building
it. But what decision
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intelligence does is that it
takes the combination of AI,
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data science, business
intelligence and humans
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expertise, it literally gives
you the ability to codify the
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experiences of others, but the
differences here is that what AI
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is what they call probabilistic
and text driven. Decision
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intelligence is deterministic.
It will literally tell you
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statistically. Here are the best
actions to take, taking all
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things considered, and it
provides you an audit trail of
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how that decision was come to so
it is really this ability to
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take from probabilities and what
you think to literally what
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decisions are going to give you
the highest probability of
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success.
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Randy Johnston: And for those of
you who have attended a lot of
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our k2 events. You might recall
that over a decade ago, it was
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2015, and 16, we were presenting
heavily on data science, and for
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those of you where I actually
did your on site tech
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assessments, I frequently
recommended that you had a data
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scientist in that window. Now, a
lot of this AI that we're
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dealing with as you are,
probably also where it's been
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around since the late 50s. 1958
is when AI started. But many
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people think AI started when
chat GPT was released in
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November of 22 you know, his
granddaughter from New York
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says, grandpa, that not be the
plan. That is not the plan.
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That's not how it happened. But
in about 2010 we started seeing
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a lot of these pattern
recognition and pattern matching
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and machine learning and this
evolution into the reporting
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tools that Eric and his team
used because they took as their
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basis Power BI and wanted to
have drillable dashboards in
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some of the earliest models.
That was interesting, but it's
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now a combination of for
decision intelligence, all of
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these things, of AI and data
science and behavioral and so
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forth. So you know, Eric, I know
you've been looking at the
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Gartner content on this. What's
Gartner have to say
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Eric Eager: on this? Well,
Gartner says that, literally, if
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you haven't heard of decision
intelligence, you're going to
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hear quite a bit about it in the
coming years. And here's what it
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is, the reason being, and the
thing that I'm trying to help
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elevate is that while you're
hearing all this AI decisions,
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the challenge is that it is
incredibly powerful, but it's
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changed. The answers are
changing. Every time you ask a
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question, it is a black box. And
what's happening is that more
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and more as we move into
advisory in these other pieces,
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it is going to cause,
unbeknownst, what we call false
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confidence and advisory, and
they are projecting it's going
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to cause financial and
reputational loss simply from
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the fact of human bias, ability
of critical thinking and aos AI
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sycophancy, it is still as much
as they're trying it is going to
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please you. And 2030 Yeah, I'm
sorry, go ahead.
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Brian F. Tankersley, CPA.CITP, CGMA: So
effectively, we're going to be
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lemmings running off a cliff.
Because AI said, Hey, wouldn't
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it be a great idea if you ran
off a cliff Exactly?
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Eric Eager: Now, here's the
thing, though, AI, if managed
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correctly and you compliment it,
it will unleash capabilities
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that all the positives and the
excitement, and why I'm excited
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about it, and these models, by
2030 it will be five times more
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trusted. It will be faster in
governing decisions than
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ungoverned decisions. And this
is why you're going to hear
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these things, because, and I'll
talk a little bit about, you
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00:09:02,339 --> 00:09:03,599
know, why is this happening?
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Randy Johnston: Well, but you
know, on that point, Eric, I
139
00:09:07,020 --> 00:09:11,040
think the good and bad we've
talked about that with past all
140
00:09:11,040 --> 00:09:14,700
technology can be used for good
or bad. But the bad number that
141
00:09:14,700 --> 00:09:21,620
we didn't quote for you is that
by 2027, 25% of the decisions
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will actually have financial
impact in a negative way. That's
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a big deal, because 2027 is a
lot closer than you might think
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Eric Eager: well, and I'm glad
you pointed that, Alex, that
145
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sometimes I forget we have audio
listeners and not video
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listeners. So yeah, thank you
for pointing it out, because
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that and I've heard and I've
talked to, you know, profession
148
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and AI leaders throughout the
world, and they say that number
149
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may be low, that it can be
significantly higher if we don't
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watch it. So I'm glad you point
that out and in. So why is this
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in? Important. Well, you know
what's happening is, AI, is the
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00:10:05,699 --> 00:10:10,679
world and velocity of business
is accelerating way before it's
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00:10:10,679 --> 00:10:14,879
happening so fast that we're all
having to react and do things
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well. Ai, you know, the way that
we make decisions today is that
155
00:10:18,479 --> 00:10:20,599
before you know, we have these
analysts that would bring
156
00:10:20,599 --> 00:10:23,659
reports to us, and as leaders,
we would take all this
157
00:10:23,719 --> 00:10:27,199
information and have to
prioritize and risk and see
158
00:10:27,199 --> 00:10:30,319
what's short term and long term,
and then you had to make the
159
00:10:30,319 --> 00:10:33,619
call, and then you go hand it
down to your operational team.
160
00:10:34,099 --> 00:10:37,219
Well, what AI? And the
excitement about AI, it is
161
00:10:37,219 --> 00:10:42,039
surfacing so many options now
that you're turbo charging your
162
00:10:42,039 --> 00:10:47,199
analyst? Well, what that's doing
is that now it is accelerating
163
00:10:47,319 --> 00:10:51,159
all these options to leaders,
and it still doesn't tell you.
164
00:10:51,279 --> 00:10:55,239
It doesn't give you the well,
all these options for my
165
00:10:55,239 --> 00:10:58,419
company, which one takes
precedence? What time do we need
166
00:10:58,419 --> 00:11:02,219
to implement? What's the trade
offs, if we do this versus this,
167
00:11:02,459 --> 00:11:07,019
I still have to make those
calls, and that's myself and my
168
00:11:07,019 --> 00:11:10,619
advisor. Because we're always
going to have the need for
169
00:11:10,619 --> 00:11:13,859
advisors. No matter what the
technology does, we're still
170
00:11:13,859 --> 00:11:16,379
going to need that human
advisor, and it's going to cause
171
00:11:16,379 --> 00:11:21,199
decision fatigue. And so all of
a sudden, we're going to make
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00:11:21,199 --> 00:11:27,019
the call. And now, if you add in
AI agents to that, the speed of
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exit, the beauty of what Randy
said, the beauty of it is we can
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execute with such speed and
precision. But the challenge is
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that you may be heading towards
a brick wall, except now we're
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just going to do it 100 miles an
hour.
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Randy Johnston: Yeah. Yeah, so
the question is, bugger
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windshield, huh?
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Eric Eager: Well, we're going to
make sure that here's the thing,
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and this is the missing piece. I
want to give people hope that
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this unbridled power, I, like,
you know, like spider man, with
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great power, comes right, great
responsibility. Here's the
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thing, that there is some
excitement and that you add the
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layer of decision intelligence.
This is why you see Gartner and
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everybody. You add that as a
layer to complement your AI. And
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it does is it continuously
monitors. It helps you see the
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emerging risk. It sees the
opportunities. And now it's an
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augmentation of decision
confidence. It helps the
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advisors and leaders prioritize
actions, what timing, and it
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doesn't replace it. Now turbo
charges the advisor and oh, by
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the way, it raises the
confidence level of the
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decisions, and now the agents
can execute. So this can really
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have the impact that I think
we've all been wanting to help
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businesses with. And we will, we
really do have a chance to
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change the profession.
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Brian F. Tankersley, CPA.CITP, CGMA: So
effectively, this is the human
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in the loop, the advisor that is
serving as those Spartans at
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Thermopylae that are preventing
the hordes of bad ideas from
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coming to reality bingo.
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Eric Eager: And this is where I
think the this we have always
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been business advisors that the
CPA profession has always we've
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been what I want to call
invisible advisors. And this is
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our opportunity to really
showcase where we have been.
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Always. A lot of people get in
the profession because we really
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want to help businesses, but we
got so bogged down into in my
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history, you know, I'm a tax
guy, I got so bogged down that
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by the time I got everything
finished, I didn't have any time
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left to really help people. And
now I really think this is
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elevating. It's the grand
promotion for everybody. Now, a
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lot of people listening are
probably going, I still don't
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understand what's the difference
between AI and decision
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intelligence. So there's a lot
of things. AI is reactive. It
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only reacts when you ask it a
question, and it will answer
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questions. It's really text
oriented. But here's the thing,
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it's probabilistic. So what that
means is, every time you ask it
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a question, you'll get a
different answer. But the
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things, the most important thing
that everybody needs to listen
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and I think everybody gets it
operates in a black box. You
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don't know. So if you're growing
an advisory firm and you're
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going AI first, the challenge
you've got is that you may have
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10 advisors ask the same
question and get 10 different
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answers and oh, by the way,
here's the other thing your
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clients can punch in the same
queue and same prompt into AI is
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your advisors, inner decision
intelligence, it is now
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proactive. It's constantly
probing and seeing the emerging
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risk. But it's what we call
deterministic. So what that
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means is that, depending on the
same input, you will get the
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same output, and it continuously
learns, we call this code. Five
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wisdom. So it's continuously
learning, but that's that human
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advisor in the loop. It
literally tracks, hey, what
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worked, what didn't, and it
keeps the advisor in the loop
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for a point of context. And last
but not least, it gives you a
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complete audit trail. It's
transparent of how those
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decisions and literally we can
get in, it literally creates
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decision tokens. So at any point
in the you know, things go by,
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you can see how the decisions
were made. This is why I think
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the accounting profession will
be so excited about this
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possibility, because it fits
within our audit ability and
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tracing, but also increases
confidence of what advice we're
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giving the client.
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Randy Johnston: Yeah, in fact,
Eric, when you first showed this
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to me and the audit trails and
how you could track how the AI
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was making decisions in the
platform, and how it was showing
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things over a longer period of
time and so on. It's like, this
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is really smart, and, more
importantly, it is reproducible.
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So you know, your whole codified
wisdom is, I've watched your
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journey on this, Eric, over the
last few years, because it was
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some years ago that you came up
with this business GPS idea and
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use the cockpit in the aircraft
system, which, again, makes
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great sense. If you've ever
flown an airplane in particular,
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it makes all the difference in
the world and the way the GPS is
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work. But this decision
intelligence engine has several
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different tricks, as I would see
it to it, it's, can you explain
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that to our listeners?
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Eric Eager: Sure. So the
difference between, like I said,
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the difference between AI and
decision intelligence is it is
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continuously monitoring so it
has your financial operational
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data, and what it does is it
looks for signals and trends.
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And it's not just on one plane.
And literally looks across
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multiple planes for signals, so
it can see things happening
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months at a time, so it begins
to uncover these emerging risk
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and opportunities. Because, just
to kind of backtrack a little
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bit, even while we started doing
all this, is that we were
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wondering we took on this
gigantic challenge of why
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businesses are failing at 50%
you know, 50% are going to fail
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in the first five years. We hear
this over and over again. So we,
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I went to Randy and said, this
has got to change. How in this
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world does this continue to
happen? Well, that sent off a
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journey of why businesses were
failing. Well, they were
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failing, you know. And I'm sure
that a lot of listeners can
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think, well, it's cash flow. It
really came down to and I'm glad
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everybody's sitting down or
driving your car. It was because
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we don't know what we don't
know. And what happens is that
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we have to see and the primary
reason is that business owners,
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we see the risk too late, and we
make decisions after the fact,
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and then we point on the wrong
things. So what decision,
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intelligence, or this codified
wisdom, is to monitor where
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you're at, see what the road
ahead looks like, and reroute
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you to the destination so see
what signals are coming, see the
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emerging risk. Have the GPS kind
of thing is recommend the best
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routes to take. But here's the
magic, you always have an
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advisor in the loop. You have an
advisor going, let me measure
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these things and make a
recommendation. You know, work
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with the business leader, but
now you got confidence of how
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you came to those things. And
then you begin to track what
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actions were executed. Because
the other thing Gartner pointed
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out is that 80% of decisions
that are executed never get
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measured. So you get this teams
you execute and you don't
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measure it. So you have this
closed loop of working with your
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advisor, measuring what you
know, basically dead,
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documenting what actions were
taken in the system, and
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continuously measure those
outcomes, and then you learn
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what worked best, and then it
creates this closed loop, and
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think about that at scale. So
now, as entrepreneurs and this,
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you know, guardians, we all
don't have to make the same dumb
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mistakes over and over again. I
am a I have a PhD in dumb things
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to do in business, and so this
helps elevate everybody across
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the board, and it continuously
gets smarter, and it
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continuously helps us, guide us
and our clients of what's
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working and What works best, if
that makes sense to everybody,
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yeah.
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Randy Johnston: So this whole
strategy of trying to help
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business proactively decide, and
I was reflecting on your mention
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of KPIs, because I've been a fan
of KPIs since Harvard introduced
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those back in 1992 but the KPIs
were often in. Correctly
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selected, not measured, not
really the right things. It took
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me better part of 10 years to
get the right KPIs for my own
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nmgi business, and now I'm
thinking about it, saying, I
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wonder if I've still got the
right KPIs. But in effect, this
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is not automatically, but it is
surfacing the right KPIs, the
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right actions, and then
monitoring those after the fact,
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which is all a pretty big deal.
So in effect, then you said,
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scale. So can you explain how
this allows advisory to scale?
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Eric Eager: Well, that's a great
question, because the other
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thing too is, you guys, you
pointed it out. We've been after
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this, solving this problem for
about, you know, going on about
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five years now. Well, what we
discovered in this process and
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journey, because we were just
dogmatic, we were going to fix
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this problem, we were going to
solve this problem, how to help
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our profession. What we realized
is that the the whole
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profession, the reason that
we're struggling with moving to
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advisory. It's what we call a
confidence gap. And it's really
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and it makes sense, when you
look at it, is that you've got,
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you know, we, most people,
realize this is 75% of the
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partners in the profession right
now are retirement age. There is
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going to be a massive brain
drain knowledge walking out the
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door at the same time, you've
got this next generation of
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people with advisors. Here's the
confidence gap problem. I'm a
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young advisor, and I want to
start doing advisory Well, I've
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got a major client, a major tax
or audit client, a lot of
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revenue to the firm. I'm afraid
to make the wrong decision. I
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don't know if I have the
confidence to make that call. At
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the same time, the senior
partners are going, I man, we
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can't risk this. And so you have
the partners that all the
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knowledge is tight, and so
everything's going to go through
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them. The younger staff are
going, I don't want to make the
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call. So this, I'm going to get
this documented and all over the
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place, so it creates this huge
gap of I can't move forward and
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enter now, the bigger risk is
that now, all of a sudden, you
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know, I don't have confidence. I
don't wanna do this. Here's the
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bigger issue, is false
confidence. Now the younger
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staff and everybody's relying on
AI to give me decisions, and
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it's got different answers.
Doesn't prioritize operating
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black box. This is a huge risk,
because now I'd rather have low
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confidence than false
confidence. Enter the world of
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decision intelligence and ran.
I'm sure you have some thoughts
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on that. What do you think in
the profession?
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Randy Johnston: You've got me
headed down all sorts of
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different paths with you here,
Eric, because I've said on this
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podcast before that for advisory
to work, I used to think it took
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gray hair. And fact, the matter
is, it's the right tools that
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really make the difference. Kind
of number one, observation
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number two, the risk of the
firm, as you pointed out, is
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very high when I see CPA and
accountants who have great
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advisory skills. It's a
beautiful thing, but there's so
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many that have been so focused
on tax and audit because that's
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where they were making the
money. Didn't really have time
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to do these other tasks. Now, if
we can do this at scale, that's
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also another huge opportunity.
Then third, it Brian and I will
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continue to talk to you about
different advisory approaches
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that are out there. In my mind
right now, for impact data has
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the most scalable, logical,
repeatable advisory offering in
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the market. And you know, things
are changing quickly, but I can
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tell you, there's a lot of
discussion around advisory, of
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which I have labeled fake
advisory, where people are doing
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client accounting services and
financial reporting and thinking
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it's advisory, and it's not that
at all, or the opposite end of
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the spectrum, They're doing CFO
services, and it's not really
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advisory, either. So you know,
this whole tipping point is upon
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us. And you know, Eric, you've
just toned it again with the
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shift in labor that's going to
happen and all this loss of so
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much knowledge. I'm really
concerned about that as well.
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Now I think you've written a
paper on this topic as well, and
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I might encourage our listeners
to try to pick up that paper.
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It's called Why decision
intelligence will power the next
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generation of Cavs. And you
know, it's almost like, I wish I
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could have you take CAS out of
the title, Eric, but I do that.
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You know, many of our firms have
just been building these client
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accounting services operations,
and they're trying to extend it
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with advisory. And CAS and
advisory are getting all mixed
381
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up in the terminology. We're
almost gonna have to invent a
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new term. But you know, for the
moment, I'm going to go with
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decision Intel. Budgets for
advisory.
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Eric Eager: I think I like that.
So I like that. I may have to
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modify the title there.
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Randy Johnston: So final,
parting thoughts you might have
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for our listeners today, Eric,
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Eric Eager: you know, here's the
thing. There's a couple things,
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and there is an approach where
there is a lot of nervousness in
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the profession that our
traditional, you know, service
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line offerings are becoming much
more automated. The margins
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we're starting to see shrink.
We're starting to have, you
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know, it's beginning to
commoditize. And I know that
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people have said, I've heard
that storm. We've weathered that
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storm years before and
everything, but I've had the
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chance to work with Randy and
Brian and, you know, Barry,
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Milan song and Gary, a lot of
the leading professions, and
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they are all saying the storm is
coming, and it can be gloom and
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doom or excitement. And I'm on
the abundant side and saying
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this is an exciting time for us.
There is now we can unleash the
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power of our advisory
capabilities, our impact. And
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I'm going to say boldly that you
know that the accounting
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profession is going to change
the world, and I want to believe
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that. And so for those who want
to join the movement and join
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the bandwagon of this is an
exciting time. You know,
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download the white paper. I'd
love to continue having
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conversations, because I'm
excited about the opportunities
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that lie ahead for the
profession, because I really
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think there's no other
profession globally that can
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change the odds and have such an
impact on so many businesses
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globally, we just had to wait
for the technology to catch up,
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to shine a spotlight on the true
work that we've been doing for
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decades. Yeah, and so I
appreciate your time, and thanks
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for letting me have a
conversation today. So Brian,
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Randy Johnston: you've been
awful quiet today. Any other
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parting thoughts from either
side?
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Brian F. Tankersley, CPA.CITP, CGMA: Well,
I think it's very important to,
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you know, to address this
confidence gap that we have
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between the experienced partners
that have taken risks and have
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learned from them, and the
junior staff that are just
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00:27:12,900 --> 00:27:15,180
trying to keep their, you know,
trying to figure out what their
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00:27:15,180 --> 00:27:18,480
career looks like. Okay? And the
thing I would say here is that,
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first off, I think you're
absolutely right, Eric, that
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validating the data that comes
out of AI and having that human
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in the loop is an essential part
here. And I think that is a
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significant definition of what
advisory looks like to me, you
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00:27:32,300 --> 00:27:34,880
know, because there is some
measurement here, you know, as
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00:27:34,880 --> 00:27:38,120
this goes back, I mean, I think
about, I think I was fortunate
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00:27:38,120 --> 00:27:41,620
enough to watch my great uncle
coach my father in
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00:27:41,620 --> 00:27:44,980
entrepreneurship when I was a
kid. And one of the things I
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00:27:44,980 --> 00:27:49,180
remember my great uncle saying
to my dad was, my great uncle
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00:27:49,180 --> 00:27:52,420
was a very successful
entrepreneur and engineer, and
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00:27:52,420 --> 00:27:55,480
has, you know, founded a
business that now has sales in
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00:27:55,480 --> 00:27:58,960
the hundreds of millions of
dollars. I will say that the
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thing that was so cool about
what he said was that he said
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00:28:02,640 --> 00:28:06,780
that, you know, if you make a
mistake, for God's sake, tell
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00:28:06,780 --> 00:28:10,020
everybody about it, because we
don't want to make the same old
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00:28:10,020 --> 00:28:13,980
mistakes. We want to make new
and interesting ones. And that's
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00:28:13,980 --> 00:28:17,160
the thing. I think that's
critical for this, because, you
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00:28:17,160 --> 00:28:21,440
know, you don't your part, your
partners are very quiet, and
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00:28:21,440 --> 00:28:25,160
they don't share where they took
risks and explain that, and
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00:28:25,160 --> 00:28:28,400
explain the thinking and explain
the calculus that's happening in
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00:28:28,400 --> 00:28:31,400
the background. And these staff
are sitting out here, and it
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00:28:31,400 --> 00:28:33,860
looks like, you know, the
partner is some Harry Potter
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00:28:33,860 --> 00:28:37,640
here. No, he's taken a lot of
small chances over the years,
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00:28:37,640 --> 00:28:41,200
increasingly bigger, and then
they, he or she's figured out
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00:28:41,380 --> 00:28:46,420
that this is how we make, this
is how we do here. And the
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00:28:46,420 --> 00:28:48,820
things is that we've all been
taught that accounting is black
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00:28:48,820 --> 00:28:53,140
and white, but the reality of it
is that there are gambles that
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00:28:53,140 --> 00:28:55,360
we have to take, just like when
you're playing chess, when
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00:28:55,360 --> 00:28:58,720
you're playing any kind of game
with anybody. You know there is
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00:28:58,720 --> 00:29:02,400
a risk associated with every
move you make, and the bet the
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00:29:02,400 --> 00:29:06,540
easiest way to lose is to stop
going forward altogether. So
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00:29:06,540 --> 00:29:10,080
very cool, Eric. I love what
you're doing, and I think it's I
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00:29:10,080 --> 00:29:12,240
agree with you. I think the
accounting profession is going
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00:29:12,240 --> 00:29:14,880
to change the world. I think
it's going to be different than
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00:29:14,880 --> 00:29:18,060
we all think it is. But at the
end of the day, somebody's got
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00:29:18,060 --> 00:29:22,160
to be like I said earlier, those
300 Spartans at Thermopylae that
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00:29:22,160 --> 00:29:24,920
keep the hallucinations from
going through and turning into
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00:29:24,920 --> 00:29:27,020
worse decisions than we could
ever dream
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00:29:27,020 --> 00:29:31,160
Randy Johnston: up as humans. So
Brian and Eric, such a pleasure
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00:29:31,160 --> 00:29:35,120
to spend time with you. So one
parting thought from my side
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00:29:35,120 --> 00:29:39,800
today, we recognize how much is
going to change on the
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00:29:39,800 --> 00:29:43,600
compliance side, and I can tell
you that this season just
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00:29:43,600 --> 00:29:48,700
completed on AI tax has been a
pretty significant move. We're
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00:29:48,700 --> 00:29:52,540
going to see transactions of all
kinds automated in client
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00:29:52,540 --> 00:29:56,560
accounting services, in audit
and in tax. And what that will
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00:29:56,560 --> 00:30:01,620
do for us is give us time for
these other. Activities, and to
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00:30:01,620 --> 00:30:06,480
me, that's a really big deal. So
you're going to see me continue
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00:30:06,480 --> 00:30:11,820
throughout the year to record my
recommend advisory platforms,
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00:30:12,120 --> 00:30:15,060
and you'll start hearing me talk
more about the interstitium,
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00:30:15,060 --> 00:30:18,060
because I think that's what the
accountants are to the
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00:30:18,060 --> 00:30:23,300
profession. A delight having you
here today, join us again for
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00:30:23,300 --> 00:30:25,760
another accounting Technology
Lab. Good day.
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00:30:31,100 --> 00:30:32,480
Brian F. Tankersley, CPA.CITP, CGMA: Thank
you for sharing your time with
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00:30:32,480 --> 00:30:35,960
us. We'll be back next Saturday
with a new episode of the
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00:30:35,960 --> 00:30:40,700
technology lab from CPA practice
advisor. Have a great week.
