The CFO’s role in the age of generative AI

CFOs
are
the
stewards
of
investment
capital,
orchestrating
a
movement
with
transformative
technology
and
innovation
to
evolve
businesses,
accelerate
revenue
streams
and
drive
meaningful
outcomes.

The
current
business
environment
has
CFOs
facing
headwinds
for
decision-making
in
less-than-ideal
conditions
with
rapidly
shifting
regulations,
tedious
reporting
standards,

ESG
requirements
and
inflationary
pressures;
however,
the
need
for
growth
and
profit
expansion
remains,
and
as
CEOs
look
for
ways
to
increase
productivity,
the
CFO
is
emerging
as
a
new
advisor
on
technology
and
innovation.
Despite
the
headwinds,
there
are
tailwinds
in
which
we
can
use
new
technology
to
enable
CFOs
to
perform
in
their
business
partnering
roles
and
drive
productivity,
cost
take
out,
accuracy,
control
and
business
value.

Through
new
approaches
to
financial
management
that
incorporate

generative
AI,
this
advanced
technology
can
help
CFOs
make
more
informed,
data-driven
decisions
for
their
organization
that
can
have
major
financial
implications.
The

IBM
Institute
for
Business
Value
CEO
study
on
decision-making
in
the
age
of
AI
found
the
top
priorities
for
CEOs
are
technology
modernization
and
productivity,
while
the
three
biggest
challenges
are
technology
modernization,
sustainability
and
security.
Enter
the
CFO,
whose
role
is
more
substantial
than
ever
to
unlock
value
and
to
scale
and
fund
a
technology
they
are
still
trying
to
fully
understand.

Read
the
report:
CEO’s
guide
to
AI
in
finance

Unlocking
the
value

CFOs
are
not
expected
to
be
technology
experts.
That
said,
they
do
need
to
understand
how
to
measure
the
business
value
created
from
generative
AI
across
the
organization
while
also
using
the
technology
to
augment
their
own
skills
and
capabilities.
This
new
technology
can
help
CFOs
do
their
job
better,
faster
and
smarter,
in
addition
to
increasing
productivity
and
opening
new
revenue
streams.

The
recent
IBM
Institute
for
Business
Value
report

CEO’s
Guide
to
Generative
AI
on
Finance
report
found
“success
depends
on
how
quickly
finance
can
turn
data
into
actionable
insights.”
Generative
AI
not
only
opens
the
door
to
other
revenue
streams
but
also
it
unlocks
value
for
the
finance
workforce.
The
IBM
report
found
that,
on
average,
AI
adopters
attribute
40%
of
finance
function
FTE
redeployment
to
AI.

Augmenting
our
day-to-day
lives
with
generative
AI
and
creating
a
digital
version
of
ourselves
allows
for
the
AI
to
essentially
become
our
assistant.
There
are
benefits
to
being
a
consumer
of
AI
but
far
greater
benefits
for
being
a
value
creator.
A
generative
AI
agent
or
assistant
can
ingest
and
summarize
structured
and
unstructured
data
from
internal
and
external
sources,
parse
through
it
and
generate
insights
and
patterns
for
financial
information
that
can
drive
business
value
and
potentially
identify
untapped
revenue
streams.
This
frees
up
a
significant
amount
of
time
where
finance
professionals
were
previously
knee
deep
in
spreadsheets.

Those
organizations
that
have
already
adopted
AI
have
helped
reduce
sales
forecast
errors
by
57%,
reduce
uncollectable
balances
by
43%,
and
cut
monthly
close
cycle
time
by
33%,
according
to

the
IBM
Institute
for
Business
Value
report.
By
embracing
these
technologies
CFOs
can
drive
efficiencies
and
better
user
experiences
for
internal
and
external
stakeholders.

New
operating
model,
skills
and
competencies

Generative
AI
is
changing
the
way
that
we
do
business.
The
office
of
the
CFO
needs
to
adapt
to
these
new
ways
of
working.
The
combination
of
a
human
and

digital
workforce
creates
a
new
operating
model
in
addition
to
new
skills
and
competencies
required
for
the
finance
organization.
CFOs
are
not
expected
to
be
data
scientists,
but
they
are
expected
to
understand
how
the
enablement
of
this
technology
can
drive
business
value.

While
finance
functional
skills
are
still
needed,
a
new
suite
of
skills
to
optimize
adoption
and
consumption
of
digital
services
are
also
required.
By
augmenting
the
workforce
with

virtual
assistants
that
free
up
capacity,
finance
professionals
can
focus
their
time
on
higher-skilled
capabilities.
Instead
of
spending
a
significant
amount
of
time
in
Excel
spreadsheets,
one
might
spend
some
of
their
time
building
AI
tools
that
help
derive
insights
and
provide
better
planning
and
forecasting.

The
good
news:
it
is
likely
easier
to
teach
a
finance
professional
how
to
use
the
technology
to
drive
value
than
it
is
to
teach
a
data
scientist
those
finance
skills.
The
finance
workforce
should
be
value
creators
and
experience
designers,
enhancing
their
analytical
and
technical
skills
to
be
able
to
train
and
prompt
their
assistants—fine-tuning,
adjusting
and
improving
the
digital
service.
In
addition,
senior
finance
executives
need
to
have
higher
communication
and
storytelling
skills
as
business
partners
for
CEOs.
 

Governance
and
controls

Trust
is
paramount
for
finance
leaders,
and
CFOs
must
be
able
to
trust
the
data
needed
to
make
critical
business
decisions
and
for
required
financial
and
ESG
reporting.
Technologies
like
generative
AI
can
spark
feelings
of
skepticism
or
mistrust
of
the
accuracy
of
data,
particularly
for
organizations
that
are
reliant
on
manual
processes.

Data
governance
is
crucial
to
ensuring
a
lack
of
bias
or

hallucinations,
establishing
greater
trust
in
data
and
giving
CFOs
the
assurance
needed
to
stand
behind
their
reporting.
The
findings
from
the
IBM
Institute
for
Business
Value
report
suggest
that
building
governance
structures
across
the
finance
organization
can
“[…]
bridge
governance
gaps
and
develop
ethical
guidance
that
will
support
the
ethical
adoption
of
generative
AI.”

No
matter
the
task,
organizations
that
embrace
generative
AI
should
know
that
with
the
right
governance
in
place,
CFOs
and
human
employees
can
free
up
their
time
to
embrace
innovation
instead
of
being
averse
to
the
changes
that
are
impending.

Getting
started
with
generative
AI

It’s
important
to
remember
that
many
organizations
are
still
in
early
adoption
stages
and
some
are
hesitant
to
dive
in.
But
research
shows
that
the
further
along
organizations
are
in
their
AI
journey,
the
more
value
that
is
delivered.

If
your
organization
is
looking
to
explore
generative
AI,
consider
starting
with
a
labor-intensive
task,
like
identifying
and
mitigating
errors
in
your
financial
reporting.
A
good
starting
point
is
from
a
hybrid
cloud
environment.
While
most
organizations
make
the
shift,
cloud
infrastructure
can
become
expensive;
but
with
enterprise-scale
generative
AI,
those
costs
might
be
compounded.
As
the
report
points
out,

FinOps,
or
financial
management
for
cloud-based
investments,
“[…]
should
play
a
big
part
in
generative
AI
investment
decisions.”

While
implementing
new
technologies
can
seem
overwhelming,
not
having
a
technology
strategy
in
place
or
avoiding
adoption
might
put
an
organization
at
risk
of
losing
the
competitive
business
advantage.
CFOs
are
the
strategic
transformation
partners
CEOs
need
to
ensure
swift
and
successful
generative
AI
adoption.

Get
the
book:
The
CEO’s
Guide
to
Generative
AI