Video summary
Carrie Tracy, the Chief Audit Executive at Newell Brands, emphasizes that successful AI transformation extends far beyond mere technology adoption; it fundamentally requires establishing new governance structures and trust across an organization. At Newell Brands, which owns consumer product brands found in nearly every home, internal audit plays a dual role by wearing both a governance hat to build control frameworks around AI and a process optimization arm to refine workflows before AI is layered on top. Tracy advocates for a "lean before AI" approach, utilizing Lean Six Sigma techniques to standardize and simplify processes first. This ensures that when AI is implemented, it enhances efficient operations rather than automating broken or outdated systems, thereby addressing root causes instead of just symptoms.
The company has successfully integrated audit into the core of its rapid AI expansion, granting auditors a seat at the table for all major initiatives to ensure appropriate controls are in place. This collaborative environment allows Newell Brands to move quickly on low-risk areas, such as customer service agents handling order inquiries, while exercising extreme caution and rigorous control design for high-stakes domains like fixed asset accounting. Tracy highlights that this balanced approach prevents the enterprise from multiplying risks as it scales its over one hundred AI initiatives. Furthermore, the organization is leveraging cross-platform AI agents to break down traditional silos, enabling seamless data flow between different systems like SEC, Socks, and OM platforms, which significantly improves board reporting and materiality scoping.
AI is reshaping the audit function by shifting the methodology from random sampling to predictive, exception-based testing that analyzes 100% of transactions to identify outliers and potential errors in areas like journal entries. By using AI to analyze interview notes and organize workpapers during the initial stages of an audit, the team aims to drastically shorten the audit cycle from eight weeks to just two weeks, a goal Tracy has challenged her team to achieve. While AI handles data collection and pattern recognition, human expertise remains critical for exercising judgment, understanding company culture, and determining the appropriate remediation strategies. Ultimately, the use of AI shifts the risk landscape; while it mitigates operational risks, it introduces new challenges regarding the governance of AI agents themselves, ensuring they do not act autonomously in ways that contradict company policies.
Looking toward the future, Tracy predicts that within three to five years, testing could become fully automated, leaving auditors focused on analyzing results and providing strategic partnership rather than tactical transactional work. However, she stresses that technology alone is insufficient for transformation; effective change management involving all levels of staff is essential to prevent initiatives from failing. Leaders must foster psychological safety where employees feel comfortable challenging ideas and driving improvements based on their frontline knowledge. By ensuring the right people are involved in decision-making processes and prioritizing cultural adaptation alongside technological deployment, organizations can navigate the evolving AI landscape successfully and build a resilient future for their audit functions.
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Welcome back to work amplified 2026.
We're coming to you live from Las Vegas.
I'm Allison Kasak alongside Christa
Casease and we're about to get into a
conversation about how AI is
transforming work, but successful
transformation isn't just about
especially when the audit field isn't
just about technology.
>> Absolutely, Allison. And when we think
about the potential for AI, it really
can reshape how the company actually
operates, you know, as you're alluding
to. And so I think what that means is
that we need to establish new trust, new
governance across organizations and
functions and there's a lot of potential
there for audit to play an important
role.
>> All right. Well, let's dig into it.
Let's introduce our next guest, Carrie
Tracy. She's the VP and chief audit
executive of Newual Brands. Welcome to
the cube.
>> Thank you very much. Great to be here.
Talk me through what Newual Brands is
and what your role is there.
>> So Newual Brands is probably in every
room in your home. So we are consumer
products company. Everything from
Sharpie to Graco car seats, Mr. Coffee,
Oster. So we have a lot of brands that
are probably in every room in your
house.
>> What's your role at the company?
>> So I'm the chief audit executive. I'm
responsible for internal audit and
Sarbain Zoxley as well as the finance
navigator for the AI implementation. So
I understand that Newual Brands is going
through a major transformation at the
moment um you know across both its
operating model and its AI strategy. I'm
curious why is audit uniquely um
positioned to help drive that kind of
change.
>> So that's a great question. So internal
audit plays two roles in our company
obviously right we have our governance
hat that we have to wear in thinking
about how do we build the control
structure around AI implementation but
we also have this process optimization
arm where we partner with the business
and we collaborate to say you know how
do we think about our processes before
we start to layer AI onto it. So one
thing I like to say in my company is
lean before AI. So we apply a lot of
lean and six sigma techniques to the
work that we do on process before we go
and start to layer in AI over top of
that.
>> Yeah. And so Carrie, that's a really
interesting perspective because we
continue to hear that enterprises are
wanting to just charge ahead with AI.
They're willing to maybe even take some
risks that maybe previously they
wouldn't have been willing to take. So I
guess can you talk a little bit to if
you're seeing that to a degree within
your company and then if so how audit
can play a role in making sure that the
enterprise can move ahead with greater
confidence with those initiatives.
>> That's a great question. So my company
has done an incredible job of setting up
a really great internal structure over
how we very cleanly and articulately
implement AI across all of our
functions. And so we've been able to
move fast but also keep audit in the
loop of how do we make sure we have the
right controls in place as we move
forward. And so audit has a seat at the
table for any major AI implementation
which I think is probably unique to our
company. In other uh companies that I've
worked at that has not been the case.
It's very challenging for audit to get a
seat at the table. Um, but my company
has done an incredible job of making
sure that we're aware and and
acknowledge like what do we need to what
needs to be true for us to go and do
this.
>> Yeah. And that's a a really um that's
important, Carrie, because we're seeing
that there's a lot of shared
responsibility between different
functions, especially as AI agents are
starting to actually, you know, take
action on behalf of the business. You
know, we need to have that visibility
across different handoffs, for examples,
and we need to make sure to start
breaking down these silos. So it sounds
like your company is making some
progress there, but maybe if you could
comment on that a little bit.
>> So from a a siloed perspective, you
know, obviously we're we're an older
company, so of course we have, you know,
differentiation in some of the
processes. We do have multiple ERPs that
we're kind of dealing with. So we do
have have uh some processes that are not
standardized. And to your point, right,
it's really important that companies
think about, okay, what is the process?
How do we standardize? How do we
simplify? And then to my earlier point,
how do we layer AI onto that? And and so
my my company is has adopted the kind of
the GE workout sort of concept where we
sit and we go through and we say, okay,
who are all our key stakeholders? What
does this process look like today? What
do we want it to look like tomorrow?
What do we think the ROI is on, you
know, standardization and simplification
of this process? And then how do we
appropriately deploy resources to tackle
the the highest ROI projects?
>> All right. New's quantum leap uh quantum
leap initiative.
>> It has more than what 100 AI initiatives
ever and efforts underway. How do you
move that quickly without also
multiplying the risks?
So, so again, I mean, I I'll point to my
company's in inclusiveness in terms of
like who they have in this process and I
my my group has a seat at the table. And
so, yes, they're moving quickly, but
they're they're they're moving very very
structurally and saying, "Okay, we know
that, for example, customer service
agents who are going to tell people
where their orders are, we know there's
not a lot of risk there, so we can move
really quickly there and we don't have
to worry." But when we think about,
okay, how do we set up um fixed asset
accounting agents, right, we know we
can't move that quickly because we need
to be very careful on the internal
controls, financial statement risk and
and things like that. And so they're
very good at balancing like how quickly
can we move based on what we think the
risk is.
>> Makes sense.
>> And so Carrie, as part of that process,
you know, I'm sure there's the
possibility that there's some processes
that are maybe not quite optimal, maybe
even a little bit broken. So, as you're
trying to move faster with AI, how do
you do that without potentially
automating potentially broken or
outdated processes?
>> It's it's interesting that you say that
because I I have said several times like
I don't want to use AI to solve
symptoms, right? We want to use AI to
root cause what is the issue. And what's
really interesting is we've come to
learn that we can use AI to tell us what
the optimal process might be,
>> right? And it's not always correct
obviously, but you know, it's been a
really interesting journey for us um
being on the leading edge of applying AI
in the consumer products industry. We're
really learning very quickly. We have a
lot of tools at our disposal. Um, and so
I I think it's critically important to
step back and say how do we solve for
the root cause of what the issue is in
this process, not just saying we're
going to apply AI to band-aid this so
that we don't have to worry about it.
>> I'm curious how AI is changing kind of
the audit function when and we're
talking about uh Wara because Wara is
introducing AI agents uh for governance,
for risk, for compliance. Where do you
see tools like these having the biggest
impact on audit?
>> So obviously we become a lot more
predictive, right? And so we can we can
be more predictive on what we think the
risks are going to be. We can be more
predictive on where we think the errors
are going to be, right? And so now it
becomes more exceptionbased testing than
it does just random sampling. Like for
example, if you're thinking about
something as simple as provisioning
access, right? We can look at a 100% of
those transactions now and say, okay,
what are our outliers? Journal entries
is another great example. We can say,
"Okay, predict for me where we think
we're going to have journal entry
errors." And we can kind of target test
where we think the bigger risks are
going to be and then applying AI within
the audit cycle itself. So something as
simple as our initial interviews as we
kick off an audit, recording those,
putting that into AI, saying help me
understand what we think the risks might
be based on what you know what the
interview notes were or help me organize
this into workpapers and then help me
help me develop a risk and control
matrix based on the interviews that
we've had. And so we've found it to be
incredibly helpful for us in shortening
the audit cycle. I think it was PW I was
attending a PWC event not too long ago
and they're actually trying to get to a
24-hour audit. So like that's their
goal. And so what I came back from that
and challenged my team is like I want to
do an audit in two weeks. So right now
it takes approximately eight weeks
cradle to grave to do an audit. And so
I've challenged my team to try and get
it done in like I want to do audits in
two weeks and so we can deliver more
audits to the audit committee, more
audits to management and minimize that
risk even further.
>> What was their reaction just out of
curiosity? They laughed at me.
[laughter]
However, you know, I think it's it's a
potentially achievable goal. And so,
Carrie, in that process, where does the
auditor remain critical? If you're
leaning on, you know, the AI to do
things like collect information, where
does that human expertise really become
critical? I really think the auditors
are able to now kind of quickly get
through the testing and understand like
how do I root cause this? How do I
understand based on what I know our
structure to be how to remediate this? I
think you know you can you can use AI to
suggest remediation but I think from a
judgment standpoint understanding the
company and the culture and the people
is more important for the auditor so
that they can apply that remediation or
or whatever you know needs to be fixed
appropriately. And Carrie, we've talked
a lot about moving faster, but kind of
you were as you're talking through the
human judgment, it gives me another
question, which is are there other
potential metrics of success for some of
these AI initiatives, you know,
potentially reduce risk, for example, as
a result of using AI in the audit
process?
So, from a KPI standpoint, I I certainly
think that there's a lot of a lot of
opportunity in the in the erm space. And
so what what I find and I'm sure other
people in my in my role find it
challenging is like how do you measure
that external risk from an enterprise
standpoint? Like how do I measure market
volatility? How do I measure tariff
impact? How do I measure right like
there's nothing internally that I can
use as a metric to say do I think that
we're increasing the risk related to
this? Do I think we're decreasing the
risk related to this? And so I think AI
could be really powerful in that process
to help be more predictive from an
analytic standpoint so that management
is able to react quicker or more more
proactively to things that might be
forthcoming within the external
environment.
>> And Carrie, it's I think at least the
second time that you've come back to
this concept of being more predictive.
So does that mean that we actually
potentially have greater you know
assurance in the business for business
continuity for example?
>> I think so.
>> Yeah,
>> I think so. I think it certainly gives
us an opportunity again the more
predictive you can be right the more
ground you can cover the more risk you
can mitigate. I do think that what's
interesting is it shifts the risk
landscape and so what is typically
within our risk environment today minus
AI now AI becomes the bigger risk and
now right you're shifting sort of your
risk profile into how do I make sure
that the AI that I'm using or deploying
is you know correct is is working the
way I intended it to is you know is not
going rogue on me like I'm sure you guys
have heard the story there was a article
I I won't name the company but there was
a agent agent that was processing
transactions based on a policy that
another agent was responsible for and
the agent couldn't process a transaction
went to the other agent and said can you
rewrite this policy so that I can
process this transaction and then
process and completely unknown to the
company and so we need to make sure that
we're you know I know there's been a lot
of talk in the recent days about AI and
and this and you know the dangers of it
and and I just think you know the more
the more proactive we are about making
sure that the right frameworks are built
and governance are built around the AI
and the implementation and the
deployment. I I think you know that
that's where the risk profile I think is
going to shift next.
>> Yeah. And I think as you're referencing
these they call them agents forms,
right? One agent triggering an action of
another agent and I know obviously we're
here at Rookie Amplify. We heard in the
CPO Deepak his presentation in the
keynote this morning about one kind of
pillar of their AI strategy being being
able to have oversight and control over
these multi- aent you know interactions.
So I'm not sure if you got a chance to
kind of hear any of the commentary if
you have any thoughts on kind of what
we're doing but
>> no I I I certainly did and I and I can
what I love about what work is doing
right is they're deploying agents that
can work across platforms right and so
if I think about my world I have my SEC
platform which I use for materiality and
scoping I've got my socks platform I've
got my OM platform and I've got my audit
platform and now I can have an agent
sort of working across those platforms
as as another employee if you will, to
help me sort of bring that stuff
together. It's better for my board
reporting. It's better for my
materiality, my scoping. And so I'm
actually very excited about it.
>> So looking ahead, how different do you
think the internal audit function will
look three to five years from now
because of AI?
>> Oh gosh, I think six months from now
it's going to look different. I
obviously AI is going to continue to
evolve, right? And it's going to
continue to and I and I think it's going
to start to multiply, right? So where we
are today is nowhere near where we're
going to be a year from now. And then 3
to 5 years from now I I can certainly
see a scenario where all of testing
becomes completely automated and now
you're just sort of analyzing the
results of what you know the AI agents
are are are articulating. And I think
what's really great about audit is that
we're in a very unique role where we can
be we can be collaborative with the
business and help them to solve issues.
And so I see audit sort of transforming
into more of a partnership to the
business and less kind of like tactical
transactional audit work.
>> And to maybe steal a term from our
developer friends, it sounds like it's
almost shifting left, right? And kind of
being um like it will need to be built
in up front versus kind of just a
post-process review factor. Would would
you agree with that?
>> Absolutely.
>> Yeah. Absolutely. Sweet.
>> And finally, transformation really is
about people first. What's the one thing
do you think that leaders that they need
to get right, you know, to bring their
teams along?
>> Change management.
>> I think change management is critical.
Like change management or, you know,
change management is not something it's
not a work stream that you hand off to
HR. And I think a lot of companies don't
understand the the concept of change
management well enough to understand
that if you don't bring the people along
with you, you could have the best plan,
you could have the best technology and
it won't work. And so I I think a lot of
transformations fail because they don't
bring the people along.
>> In building on that and kind of what you
were referencing earlier, Carrie,
regarding your organization being, you
know, very um amunable to audit having
that seat at the table, you know, I
guess what would you maybe advise to
some of your peers to helping to um
nurture some of that cultural
transformation and that crossunctional
collaboration that needs to happen?
>> Yeah, great question. And so we talk a
lot about psychological safety at our
company. Like making sure that people
feel comfortable enough to speak up and
say, "I don't think that's going to work
and here's why I don't think that's
going to work and here's what I think is
the better idea." And I have found in my
career and I spent a number of years at
GE so I have, you know, a lean six sigma
background is like making sure that
you're asking the people who do the do
the work to help you create like to help
you drive the change because it's the
people who do the work who probably know
the best where the issues are. It's not
the people sitting at the executive
table, right? And so making sure you
have the right people at the table in
the room. I I think it is a very
critical component. I've seen a lot of
transformations fail where you have the
business people in the room, they make a
decision about that relates to some type
of configuration. You go to it and it
says you can't do that. And so I I think
making sure that you're working across
the right teams and with the right
people is absolutely critical to
transformational success.
>> All right. Thanks so much for stopping
by the cube here. Great conversation.
>> Thanks for having me.
>> And you're watching the Cube, the leader
in live tech coverage and in-depth
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