AI
is
transforming
the
legal
industry,
but
how
can
lawyers
use
it
effectively
while
avoiding
ethical
pitfalls?
In
a
recent
episode
of
“Be
That
Lawyer,”
Jay
McAllister,
founder
of
Paragon
Tech
Inc.,
joins
host
Steve
Fretzin
to
discuss
the
rapid
advancements
in
AI,
its
impact
on
legal
workflows,
and
what
the
future
holds
for
law
firms
adapting
to
this
technology.
Here
are
three
insights
from
their
conversation.
Overcoming
Inertia
Like
any
business,
lawyers
can
be
skeptical
about
the
benefits
of
emerging
tools.
Here,
Jay
discusses
how
his
own
focus
on
measurable
results
drove
his
entry
into
legal
tech.
Getting
Started
With
AI
One
starting
point
for
onboarding
AI
can
be
in
your
marketing
efforts.
Here’s
how
you
can
leverage
it
in
business
development
while
paving
the
way
for
broader
uses.
ChatGPT
and
Hallucinations
Does
ChatGPT
deserve
its
bad
reputation?
Can
AI
be
trusted
in
legal
work?
Here,
Jay
shares
his
views.
Steve
Fretzin
is
a
bestselling
author,
host
of
the
BE
THAT
LAWYER
Podcast,
and
business
development
coach
exclusively
for
attorneys.
Steve
has
committed
his
career
to
helping
lawyers
learn
key
growth
skills
not
currently
taught
in
law
school.
His
clients
soon
become
top
rainmakers
and
credit
Steve’s
program
and
coaching
for
their
success.
He
can
be
reached
directly
by
email
at [email protected].
Or
you
can
easily
find
him
on
his
website
at www.fretzin.com or
LinkedIn
at https://www.linkedin.com/in/stevefretzin/.
I’m
going
to
offer
some
advice
to
liberals
that,
at
first
blush,
may
grate
but
you
need
to
check
out
Reason.
The
libertarian
blog
features
a
piece
by
Ilya
Somin
that
slaps
back
at
the
idea
that
birthright
citizenship
as
extended
under
the
Fourteenth
Amendment
can
be
undone
by
executive
order.
Which
isn’t
some
wild,
far-left
theory
—
indeed,
conservative
darling
Judge
Jame
Ho
wrote
that
birthright
citizenship
can
only
be
undone
by
constitutional
amendment
(of
course,
that
was
before
birthright
citizenship
became
the
hobby
horse
of
the
Trump
administration
and
Ho
cravenly
changed
his
tune
on
that
one).
Donald
Trump
issued
just
such
an
EO
on
his
first
day
back
in
office,
and
his
administration
is
now
dealing
with
multiple
pieces
of
litigation
as
a
result.
In
furtherance
of
this
Trump
administration
policy,
law
professors
Randy
Barnett
and
Ilan
Wurman
took
to
the
pages
of
the
New
York
Times
Op
Ed.
column
to
lend
the
academic
credibility
of
their
positions
to
the
Trumpian
power
grab.
Barnett
and
Wurman
rely
primarily
on
an
“allegiance-for-protection”
theory
that
predicates
citizenship
on
a
trade
of
one
for
the
other
they
trace
to
an
1862
opinion
by
Attorney
General
Edward
Bates.
Yes,
history
buffs,
you’ll
note
the
date
of
that
opinion
limiting
birthright
citizenship
to
those
who
have
traded
allegiance
for
protection
is
BEFORE
the
passage
of
the
Fourteenth
Amendment
(that,
of
course,
being
the
amendment
that
created
the
birthright
citizenship
right).
Which
seems
like
a
pretty
freakin’
big
red
flag.
And
Somin
further
illustrates
how
dumb
it
is
to
use
this
theory
to
interpret
the
Fourteenth
Amendment:
There
are
several
flaws
in
Barnett
and
Wurman’s
“allegiance-for-protection”
theory.
The
biggest
is
that,
if
consistently
applied,
it
would
undermine
the
central
purpose
the
Citizenship
Clause:
extending
citizenship
to
recently
freed
slaves
and
their
descendants.
Slaves
born
in
the
United
States
(and
their
parents,
who
were
also
usually
slaves)
obviously
weren’t
part
of
any
social
compact
under
which
they
traded
allegiance
for
protection.
Far
from
protecting
them,
state
and
federal
governments
facilitated
their
brutal
oppression
at
the
hands
of
their
masters.
This
situation
changed,
to
an
extent,
with
the
abolition
of
slavery
through
the
Thirteenth
Amendment.
But
the
“subject
to
the
jurisdiction”
language
of
the
Citizenship
Clause
refers
to
people
subject
to
that
jurisdiction
at
the
time
they
were
born.
For
example,
the
child
of
a
foreign
diplomat
doesn’t
get
birthright
citizenship
if
her
parents
later
lose
their
diplomatic
immunity.
If
being
subject
to
US
jurisdiction
requires
a
compact
trading
allegiance
for
protection,
former
slaves
obviously
didn’t
qualify.
Thus,
the
Barnett-Wurman
theory
would
defeat
the
central
purpose
of
the
Citizenship
Clause.
That
alone
is
reason
to
reject
it.
Really
though,
the
Barnett/Wurman
piece
is
a
bit
of
a
feat
as
it’s
brought
together
legal
scholars
of
all
stripes
to
condemn
it.
Like
conservative
professor
Michael
Ramsey,
who
has
written
extensively
about
birthright
citizenship,
who
says
(pithily,
imho)
that
the
Bates
opinion
that
the
Barnett/Wurman
theory
is
based
upon
is
of
“only
marginal
relevance”
to
the
analysis
of
originalism
and
the
Fourteenth
Amendment.
Oh,
and,
Barnett/Wurman
misread
Bates.
A
more
liberal
law
professor,
Jed
Shugerman,
also
has
a
lot
to
say
about
the
Barnett/Wurman
piece.
He
dug
into
the
primary
source
in
the
article
(the
Bates
opinion)
and
found
Bates
concluded
in
favor
of
birthright
citizenship,
“The
most
important
point
is
that
Bates
did
not
propose
anything
like
an
allegiance
theory
for
granting
citizenship,
and
he
actually
endorsed
the
birthright
basis
–
explicitly,
and
citing
a
half-dozen
sources
for
the
rule.”
Now
you
might
think
that
this
is
an
awful
lot
of
attention
paid
to
this
1862
Bates
opinion
in
the
rebuttal
of
the
Barnett/Wurman
piece
—
but
that’s
the
thing,
that’s
the
primary
historical
source
in
the
article.
Oh,
and
they
also
cite
Blackstone’s
Commentaries
in
support
of
their
position.
But
Shugerman
really
nails
them
on
this
source
—
one
of
the
“half-dozen
sources”
Bates
cites
in
support
of
the
idea
of
birthright
citizenship
IS
BLACKSTONE.
In
the
last
few
years,
Blackstone
has
been
cited
by
both
sides
of
this
debate.
Barnett
and
Wurman
claim
Blackstone
here
for
their
allegiance-for-protection
theory.
But
their
own
American
source
from
the
mid-19th
century
contradicts
their
use
of
Blackstone.
Not
only
did
Bates
endorse
birthright
citizenship,
he
also
told
us
that
he
considered
Blackstone
an
authority
for
that
position,
too.
It
is
more
important
in
an
originalist
debate
to
understand
how
Americans
of
the
1860s
understood
Blackstone,
and
it
turns
out
that
Bates
is
at
least
a
data
point
that
Americans
thought
it
was
clear
that
Blackstone
supported
birthright
citizenship.
But
Barnett
and
Wurman
do
not
tell
the
reader
that
Bates
not
only
rejected
their
theory,
he
also
rejected
their
interpretation
of
Blackstone.
LOLZ.
Barnett
has
indicated
on
social
media
that
he
has
MOAR!
evidence
to
support
his
point,
but,
I’ll
leave
it
(again)
to
Shugerman
to
state
the
obvious.
None
of
this
is
great
for
the
academic
credibility
of
Barnett
and
Wurman.
But
it
could
easily
result
in
an
opportunity
in
Trumpland
—
they
need
folks
willing
to
go
the
extra
mile
to
make
their
harebrained
legal
theories
stick.
Kathryn
Rubino
is
a
Senior
Editor
at
Above
the
Law,
host
of
The
Jabot
podcast,
and
co-host
of
Thinking
Like
A
Lawyer.
AtL
tipsters
are
the
best,
so
please
connect
with
her.
Feel
free
to
email
her
with
any
tips,
questions,
or
comments
and
follow
her
on
Twitter
@Kathryn1 or
Mastodon
@[email protected].
It
doesn’t
just
mean
people
with
the
biggest
books
of
business,
but
the
ones
who
can
get
the
most
out
of
the
power
of
the
blend.
That
blend
together
is
going
to
be
more
than
the
sum
of
its
parts.
If
you’re
a
tough
firm
with
sharp
elbows,
bringing
on
a
[different
type
of]
group
…
might
not
be
the
right
fit
for
you.
If
you’re
like
us,
who
like
to
focus
a
lot
on
being
energized
at
work
and
having
happy
teams,
we
put
a
higher
value
on
the
individual’s
personality.
Are
they
nice,
are
they
humble,
are
they
collaborative?
Those
are
important
characteristics
for
us.
— Ira
Coleman,
chairman
of
McDermott
Will
&
Emery,
in
comments
given
to
the
American
Lawyer,
on
why
it’s
just
as
important
to
find
lateral
partner
candidates
who
fit
in
with
a
firm’s
business
model
and
culture
as
it
is
to
find
lateral
partner
candidates
with
big
books
of
business.
McDermott
made
40
lateral
partner
additions
over
the
course
of
the
2024.
Staci
Zaretsky is
a
senior
editor
at
Above
the
Law,
where
she’s
worked
since
2011.
She’d
love
to
hear
from
you,
so
please
feel
free
to
email
her
with
any
tips,
questions,
comments,
or
critiques.
You
can
follow
her
on Bluesky, X/Twitter,
and Threads, or
connect
with
her
on LinkedIn.
Judge
Ana
Reyes
heard
the
challenge
to
Trump’s
transgender
service
member
ban.
It
did
not
go
well
for
the
DOJ.
Technically,
it
wasn’t
a
“ban”
but
an
executive
order
titled
“Prioritizing
Military
Excellence
and
Readiness.”
Though
instead
of
canceling
the
F-35
or
anything
that
might
actually
improve
military
readiness,
the
order
calls
out
“gender
identity
inconsistent
with
an
individual’s
sex”
as
incompatible
with
military
service
because
it
would
violate
“a
soldier’s
commitment
to
an
honorable,
truthful,
and
disciplined
lifestyle,
even
in
one’s
personal
life.”
This
screwball
honor
code
articulation
represents
the
work
of
Trump’s
remedial
school
attorneys
to
circumvent
the
legal
obstacles
of
a
ban.
It’s
like
Orwellian
newspeak
but
much
more
stupid.
Judge
Reyes
did
not
appreciate
this
coy
effort
to
disguise
the
ban
as
something
else,
noting
that
if
the
infamously
unable
to
shut
up
president
were
asked
directly
if
this
was
intended
as
a
ban
on
transgender
service
members
he’d
say
“of
course,
it
is”
—
a
phrasing
that’s
probably
too
coherent
for
him,
but
the
sentiment
is
what
matters.
As
the
hearing
continued
to
plummet
into
lunacy,
Judge
Reyes
questioned
how
the
government
thought
it
could
avoid
showing
“animus”
by
recasting
the
ban
as
a
matter
of
the
service
members’
honor.
Of
all
the
roundabout
efforts
to
get
this
ban,
basing
it
on
accusations
of
dishonor
and
lying
seems
the
least
likely
to
get
there.
That
brought
us
to
the
following
exchange
(image
hat
tip
to
Michael
Paulauski
on
Bluesky):
See,
in
that
scenario,
I
would
simply
curl
up
into
a
ball
and
asked
to
be
left
at
the
defense
table
to
die.
This
whole
“being
Trump’s
personal
lawyer”
thing
isn’t
working
out
too
well
for
DOJ
staff.
I
know
the
job
market
is
flooded
with
DOJ
resignations
right
now,
but
it
might
be
time
to
get
out
of
this
case
before
the
stench
of
this
representation
hangs
onto
his
career
forever.
When
Kafka
wrote
Before
the
Law,
he
meant
to
describe
the
surreal
hellscape
of
standing
“before”
the
law,
not
the
surreal
hellscape
of
applicants
“before”
they
become
lawyers.
Yet
the
powers-that-be
have
transformed
the
February
administration
of
the
California
bar
exam
into
a
farce
that
would
make
Kafka
blush.
Beset
with
nightmarish
twists
and
turns
throughout
the
process
and
with
the
exam’s
start
date
looming
on
February
25,
the
Bar
has
offered
full
refunds
to
all
5,600
applicants
out
of
an
abundance
of
generosity/desperate
necessity.
This
unprecedented
move
comes
after
multiple
blunders
left
test-takers
bewildered
at
the
prospect
of
staking
their
career
on
an
exam
that
resembled
building
an
airplane
mid-flight
except
the
plane
is
a
Boeing
and
it’s
taking
direction
from
Trump’s
air
traffic
controllers.
From
scheduling
nightmares
to
broken
practice
exams
to
a
dearth
of
accessible
test
centers,
the
Bar’s
partnership
with
Meazure
Learning
has
left
a
lot
to
be
desired.
As
the
state
bar
examiners
put
it
in
their
refund
email,
the
experience
has
generated
a
lot
of
“frustration,
confusion,
and
anxiety.”
We
are
extremely
sorry
for
how
the
administration
of
the
February
2025
Bar
Exam
has
been
rolling
out.
We
understand
that
scheduling
challenges,
poor
communication,
and
inconsistent
messaging
between
the
State
Bar
and
Meazure
Learning
have
caused
a
lot
of
frustration,
confusion,
and
anxiety.
As
a
result,
we
are
offering
all
applicants
who
wish
to
withdraw
from
the
February
exam
a
full
refund
(less
bank
fees).
To
qualify,
you
need
to
withdraw
before
the
exam
by
submitting
your
request
to
withdraw
through
the Applicant
Portal.
We
know
many
applicants
do
not
have
the
option
of
withdrawing,
and
we
are
committed
to
making
the
exam
the
best
experience
we
can.
Everything
about
this
process
has
been
cursed.
California
got
to
this
point
after
its
bar
exam
lurched
into
the
red
and
rather
than
swiftly
plotting
out
a
graceful
transition,
detractors
held
up
the
prospect
of
reform
until
the
11th
hour.
Honestly,
the
decision
to
employ
questions
from
Kaplan
Exam
Services
and
offer
multiple,
more
convenient
facilities
and
remote
administration
is
a
pretty
good
one!
The
NCBE’s
antiquated
requirements
were
inconvenient
for
applicants
and
only
succeeded
in
making
the
ostensible
non-profit
very,
very
rich
and
the
new
regime
promised
to
save
upwards
of
$4
million
annually.
Instead,
trying
to
force
the
change
in
a
matter
of
months
to
meet
the
February
exam
resulted
in
multiple
disasters
including
a
projected
budget
overrun
—
with
an
expected
extra
million
required
for
the
upcoming
July
test.
The
Bar’s
offer
of
an
$830
refund
(minus
bank
fees,
naturally)
serves
as
a
fitting
coda
to
this
tragicomedy.
But
deferring
the
exam
isn’t
an
option
for
many
applicants
who
need
to
pass
this
test
to
keep
their
jobs.
For
those
folks,
the
examiners
offer
more
practice
questions,
a
few
more
testing
locations,
and
importantly
a
redline
of
the
Student
Guide
so
everyone
can
easily
figure
out
where
the
rules
have
changed
midstream.
Someday,
California’s
new
look
bar
exam
will
deliver
solid
results
in
a
convenient
and
cost-effective
manner.
That
day,
however,
is
not
today.
Another
sign
that
the
Trump
II
administration
is
taking
a
sharper
turn
to
the
right
than
his
previous
time
in
office
happened
on
Friday
when
the
Federal
Trade
Commission
Chair
Andrew
Ferguson
announced
the
agency
was
over
the
American
Bar
Association.
Specifically,
the
new
policy
“prohibits
FTC
political
appointees
from
holding
leadership
roles
in
the
American
Bar
Association
(ABA),
participating
in
ABA
events,
or
renewing
their
ABA
memberships.
Additionally,
the
FTC
will
no
longer
use
its
resources
to
support
any
employee’s
ABA
membership
or
participation
in
ABA
activities.”
As
a
reminder,
the
ABA
is
a
nonpartisan
organization,
and
the
country’s
largest
voluntary
bar
association.
The
letter
—
available
in
full
below
—
has
big
got-a-C-in-contracts-gunner
energy.
Ferguson
accuses
the
ABA
of
a
“long
history
of
leftist
advocacy”
and
“recent
attacks
on
the
Trump-Vance
Administration’s
governing
agenda.”
He
continues:
The
President
of
the
ABA
recently
issued
a
statement
accusing
the
Trump-Vance
Administration
of
“wide-scale
affronts
to
the
rule
of
law.”
What
followed
was
a
breathless
screed
leveled
against
President
Donald
J.
Trump’s
swift
and
tireless
delivery
on
his
promises
to
the
American
people
to
confront
our
existential
immigration
crisis
and
end
waste,
fraud,
and
abuse
in
the
federal
government.
This
statement
was
not
a
sober
assessment
of
the
law.
It
was
a
collection
of
Democrat
political
talking
points
with
the
ABA’s
logo
affixed
at
the
top.
Ah
yes,
the
“collection
of
Democrat
political
talking
points”
that
quotes
*checks
notes*
a
Reagan
judge.
Hm.
Maybe
the
ABA’s
position
isn’t
as
one-sided
as
Ferguson
would
like
to
pretend
it
is.
The
letter
also
slams
the
ABA
for
being
in
bed
with
Big
Tech.
Listen,
there
are
legitimate
concerns
about
the
revolving
door
between
government
and
private
sector
—
just
ask
Ed
Martin
—
yet
this
perennial
issue
doesn’t
feel
like
the
motivating
factor
behind
the
FTC’s
petty
move.
Even
the
specific
evidence
Ferguson
uses
to
extend
his
case
is
from
2022,
when
the
ABA
Antitrust
Section
opposed
the
American
Innovation
and
Choice
Online
Act,
sponsored
by…
Democratic
Senator
Amy
Klobuchar.
Sigh.
There
appears
to
be
more
than
a
little
bit
of
tension
between
Ferguson’s
first
and
second
argument.
The
Trump
administration
has
proven
in
the
less-than-a-month
it’s
been
back
in
charge
they’re
willing
to
go
scorched
earth.
The
ABA
smacked
at
the
administration,
so
now
the
FTC
won’t
pay
their
employees’
$195
membership
fee.
I’m
sure
this
isn’t
the
last
tit-for-tat
we’ll
see
out
of
the
Trump
II
reign.
Kathryn
Rubino
is
a
Senior
Editor
at
Above
the
Law,
host
of
The
Jabot
podcast,
and
co-host
of
Thinking
Like
A
Lawyer.
AtL
tipsters
are
the
best,
so
please
connect
with
her.
Feel
free
to
email
her
with
any
tips,
questions,
or
comments
and
follow
her
on
Twitter
@Kathryn1 or
Mastodon
@[email protected].
In
our
forthcoming
Spring
2025
publication,
“Fighting
the
Hypothetical:
Why
Law
Firms
Should
Rethink
the
Billable
Hour
in
the
Generative
AI
Era,”[1]
we
hypothesize
that
Generative
AI
(GenAI)
technology
will
change
forever
how
legal
services
are
delivered
and
will
force
law
firms
to
re-engineer
their
legacy
economic
model.
The
legal
industry
stands
at
a
critical
inflection
point,
because
GenAI
now
can
automate
many
routine
legal
tasks
that
have
been
handled
for
decades
by
junior
professionals
at
premium
hourly
rates.
The
GenAI
phenomenon
puts
the
much-maligned
billable
hour
revenue
model
squarely
in
the
crosshairs.
As
this
model
ceases
to
be
the
predominant
way
that
law
firms
are
compensated,
legal
professionals
will
need
to
develop
new
ways
to
demonstrate
the
value
of
their
services
that
align
with
a
modified
revenue
model.
Though
the
imperative
to
adapt
is
clear,
firms
that
try
to
implement
a
new
strategy
for
the
GenAI
era
without
first
analyzing
their
historical
data
and
putting
in
place
a
data-driven
strategy
will
risk
making
poorly
informed
decisions
that
could
threaten
their
financial
stability.
The
Fundamental
Challenge
The
traditional
pyramid
model
relies
heavily
on
junior
professionals
handling
routine,
high-volume
work
at
substantial
hourly
rates,
consistently
generating
handsome
profits
per
partner
for
the
world’s
largest
law
firms.
However,
the
pyramid
model
faces
an
existential
threat,
because
GenAI
can
perform
many
routine
legal
tasks
with
equal
or
superior
accuracy
in
a
fraction
of
the
time.
That
time
savings
will
leave
clients
and
others[2]
wondering
why
they
should
pay
$500
per
hour
or
more
for
a
BigLaw
associate
to
handle
a
task
that
can
be
automated
and
completed
in
minutes,
not
days.
Consider
our
hypothetical:
When
a
corporate
in-house
lawyer
needs
to
produce
an
everyday
agreement
(e.g.,
an
NDA
or
a
simple
license
agreement)
or
a
routine
court
filing
(e.g.,
a
pro
hac
vice
motion),
they
now
face
two
radically
different
options.
The
traditional
path
involves
calling
a
law
firm
partner,
who
assigns
an
associate
to
do
the
first
draft,
resulting
in
a
$2,000
bill
for
approximately
four
hours
of
work—mainly
research,
drafting,
and
revision—at
a
weighted
rate
of
$500
per
hour.
Option
2
involves
a
GenAI
tool
producing,
in
20
seconds
(at
a
miniscule
fraction
of
a
$20
monthly
subscription),
a
commendable
draft
with
accuracy
rates
approaching
90%.
A
more
senior
in-house
lawyer
can
then
easily
edit
and
deliver
the
draft
less
than
an
hour
after
typing
the
initial
GenAI
prompt.
GenAI
for
basic
drafting
saves
considerable
time
and
money
(those
are
often
the
same
thing
in
the
legal
industry),
and
an
entirely
acceptable
work
product
was
delivered
without
any
costly
back-and-forth
between
the
inside
counsel
and
an
outside
law
firm.
This
dramatic
efficiency
gain
threatens
to
eliminate
substantial
billable
hours
at
law
firms,
particularly
at
the
junior
level
where
much
of
a
law
firm’s
profitability
is
generated.
This
hypothetical
is
now
beginning
to
become
a
reality,
prompting
several
critical
questions:
What
tasks/workstreams
should
we
decline
to
handle
because
they
are
unprofitable?
What
tasks
should
be
automated
versus
completed
by
humans?
What
is
a
reasonable
human/technology
task
allocation
of
work
input?
How
must
we
adjust
our
rate
structure
to
account
for
the
changed
cost
model?
How
must
our
workforce
and
personnel
mix
change
for
optimal
profitability?
In
a
GenAI-enabled
legal
industry,
law
firm
leaders
must
address
these
fundamental
questions
strategically.
The
consequences
of
ignoring
this
new
reality
for
any
law
firm
leader
are
likely
to
be
disastrous.
Equally
perilous,
however,
is
trying
to
address
this
tricky
situation
without
fully
understanding
the
scope,
facts,
or
economics
of
this
new
legal
industry
economic
paradigm.
That’s
the
practical
point
of
our
piece.
The
Critical
Role
of
Historical
Analysis
Before
implementing
a
GenAI
strategy,
law
firm
leaders
must
develop
a
deep
understanding
of
their
exposure
to
the
appurtenant
economic
risk
through
careful
analysis
of
historical
billing
data.
This
analysis
should
focus
on
three
key
areas
that
will
shape
the
firm’s
transition
to
AI-augmented
legal
practice.
Task
Classification
and
Workflow
Analysis
A
meaningful
understanding
of
the
current
work
distribution
across
a
firm’s
legal
professionals
begins
with
comprehensive
task
/
timekeeper
identification.
Firms
must
examine
their
billing
records
to
identify
patterns
in
the
types
of
work
performed
most
frequently
across
different
practice
areas
by
different
levels
of
legal
professionals.
This
analysis
should
reveal
not
just
what
work
is
being
done,
but
who
typically
handles
different
aspects
of
each
of
the
sub-tasks
(e.g.,
original
drafting
vs.
editing
vs.
final
review).
For
instance,
this
type
of
data
analysis
would
likely
illustrate
that
junior
associates
spend
a
significant
portion
of
their
time
on
document
review,
legal
research,
and
initial
draft
preparation
–
precisely
the
tasks
that
are
most
vulnerable
to
AI
automation.
Beyond
simple
task
identification,
firms
need
to
understand
the
time
input
patterns
in
both
routine
and
complex
work.
This
analysis
often
reveals
surprising
insights
into
how
professionals
at
different
levels
spend
their
time.
Senior
legal
professionals,
for
example,
might
be
spending
more
time
than
realized
on
routine
tasks
that
could
be
automated,
freeing
them
for
higher-value
work.
Where
the
same
tasks
or
deliverables
are
handled
by
different
professionals,
it
is
critical
to
scrutinize
the
related
workflows.
Legal
work
often
involves
complex
handoffs
between
different
professionals,
with
junior
work
product
feeding
into
senior-level
analysis
and
strategy.
Understanding
the
task
dependencies
and
workflow
progression
is
crucial
for
identifying
where
the
presence
or
absence
of
GenAI
automation
might
create
bottlenecks
or
disruptions,
or
the
serendipitous
converse:
potential
accelerations
in
established
workflows.
Firms
must
also
examine
areas
that
frequently
require
significant
revision
or
rework.
These
patterns
often
indicate
inefficiencies
in
current
processes
that
could
be
addressed
through
GenAI
implementation,
but
they
might
also
highlight
areas
where
human
judgment
and
experience
remain
critically
important.
When
identifying
the
legal
tasks
ripe
for
automation,
firms
should
distinguish
between
routine
low-value,
low-risk
routine
work
that
can
be
readily
automated
and
high-value
work
that
requires
specialized
human
expertise.
The
task
classification
and
workflow
analysis
may
seem
like
a
daunting
task,
but
firms
can
classify
tasks
by
using
legal
spend
data
analytics
software
tools,
like
those
offered
by
Legal
Decoder[3],
which
automatically
categorize
each
time
entry’s
component
parts
by
phase/task
into
a
taxonomy
based
on
area
of
law.
Then
the
taxonomy
permits
deep
analysis.
Without
this
necessary
data-driven
analysis,
law
firms
simply
engage
in
guesswork—the
same
type
of
guesswork
that
can
come
into
play
when
a
client
asks,
“how
much
will
this
cost?”
But
there’s
a
better
way
with
data
categorization:
Tasks
Suitable
for
Automation
Tasks
Requiring
Human
Expertise
Document
review
and
initial
screening
in
due
diligence
Complex
strategic
advice
and
counseling
Basic
contract
drafting
from
templates
and
citation
checking
Crisis
management
and
sensitive
client
communications
Legal
research
for
straightforward
questions
High-stakes
negotiations
Document
summarization
and
extraction
of
key
terms
After
the
task
classification
and
workflow
analysis
is
completed,
it
becomes
possible
to
build
out
a
comparative
economic
model
showing
the
financial
impact
and
opportunities
presented
by
GenAI
technologies.
A
deep
understanding
of
the
levers
pushing
and
pulling
on
these
financial
models
is
important,
as
those
levers
will
inevitably
reshape
law
firms’
financial
structure,
particularly
where
clients
insist
on
using
these
tools
in
service
delivery.
The
following
analysis
examines
the
quantitative
impact
on
a
mid-sized
practice
group,
comparing
traditional
operations
with
a
GenAI-augmented
model.
Without
question,
it
is
a
simplified
comparison
of
two
financial
models,
but
the
core
principles
and
outcomes
underlying
each
are
meant
to
be
illustrative,
comporting
with
principles
underlying
a
more
sophisticated
financial
analysis.
Consider
a
typical
mid-sized
practice
group’s
current
state.
In
the
traditional
model,
four
partners
billing
1,800
hours
at
$1,000
per
hour,
eight
senior
associates
at
$650
per
hour,
and
twelve
junior
associates
at
$450
per
hour
generate
approximately
$29
million
in
total
revenue.
The
traditional
model
is
essentially
a
“business-as-usual”
approach
under
a
billable
hour
revenue
model.
The
GenAI
model
incorporates
the
strategic
insights
unearthed
through
the
“Task
Classification
and
Workflow
Analysis”
with
tasks
and
workflows
altered
and
augmented
as
a
result
of
GenAI
usage
in
place
of
human
input.
In
this
regard,
the
GenAI
model
makes
several
reasonable
assumptions:
(a)
a
percentage
of
low-value
billable
hours
will
be
displaced
by
GenAI;
(b)
headcount
at
the
Junior
Associate
Level
can
be
reduced
as
a
result
of
GenAI
usage
for
low-level
tasks;
(b)
the
hourly
rate
in
the
GenAI
model
can
increase
because
more
senior
legal
professionals
now
are
handling
only
high-value
work,
thereby
justifying
the
higher
hourly
rate;
and
(d)
there
are
GenAI
costs
–
both
hard
costs
(licensing
fees)
and
soft
costs
(training,
change
management,
and
so
forth).
At
a
macro
level,
the
table
above
shows
that
the
financial
model
shifts
positively
with
strategic
GenAI
implementation.
Hourly
rates
at
all
levels
should
increase
to
reflect
the
enhanced
value-add
work
completed
by
the
more
senior
legal
professionals,
but
there
would
be
a
concomitant
reduction
in
hours
and
headcount
as
routine
tasks
are
automated.
These
changes
ripple
through
the
entire
financial
structure
of
the
group.
Although
overall
revenue
modestly
decreases,
the
composition
of
that
revenue
shifts
significantly
toward
higher-value
work,
resulting
in
a
more
profitable
organization.
A
paradigm
shift
to
the
financial
model
is
predicated
on
a
data-driven
task
classification
and
workflow
analysis,
followed
by
an
ongoing
monitoring
of
the
analysis
to
maintain
profitability
while
adapting
to
new
service
delivery
models.
Recent
reports
show
that
significant
changes
to
legal
personnel
strategies
are
already
happening,
accompanied
by
higher
rates.[5]
Legal
Professional
Impact
Analysis
Partner
Level
Evolution
The
partner
tier
demonstrates
remarkable
resilience
in
the
face
of
technological
transformation,
with
strategic
adjustments
enhancing
both
efficiency
and
value
delivery.
Partners
experience
a
modest
5%
reduction
in
billable
hours,
primarily
through
the
automation
of
routine
oversight
functions.
This
reduction,
however,
is
more
than
offset
by
a
50%
increase
in
hourly
rates,
reflecting
the
enhanced
value
that
the
partners
can
deliver
in
the
GenAI-enabled
environment.
Partners
now
will
focus
more
intensively
on
strategic
counseling
by
leveraging
GenAI-driven
work
product
to
provide
sophisticated
guidance
on
complex
legal
matters.
Their
capacity
for
complex
matter
supervision
expands
significantly
as
routine
tasks
are
streamlined,
allowing
them
to
manage
larger
portfolios
more
effectively
and
originate
additional
business.
Perhaps
most
important,
partners
can
be
more
involved
in
developing
innovative
legal
solutions
that
combine
traditional
legal
expertise
with
AI-enabled
capabilities,
creating
new
value
propositions
for
clients.
Senior
Associate
Adaptation
The
senior
associate
level
undergoes
a
nuanced
transformation
that
preserves
headcount
while
fundamentally
altering
work
patterns.
These
practitioners
remain
essential
to
the
firm’s
operation,
but
we
imagine
that
their
role
shifts
significantly
toward
quality
control
and
supervision.
Senior
associates
become
the
critical
bridge
between
AI-generated
work
product
and
final
deliverables,
ensuring
maintenance
of
the
firm’s
high
standards
while
leveraging
new
technological
capabilities.
Although
senior
associates
experience
a
15%
reduction
in
billable
hours,
their
work
becomes
more
sophisticated
and
valuable,
thereby
justifying
a
50%
higher
hourly
rate.
Their
time
shifts
away
from
routine
reviews
toward
more
strategic
activities.
They
take
on
enhanced
responsibilities
(often
non-billable)
in
training
and
supervising
junior
staff
in
the
effective
use
of
AI
tools,
while
managing
increasingly
complex
matter
workflows.
Client
relationship
development
becomes
a
bigger
part
of
their
role,
as
they
help
clients
understand
and
benefit
from
the
firm’s
enhanced
capabilities.
Junior
Associate
Transformation
The
most
profound
changes
manifest
at
the
junior
associate
level,
where
the
impact
of
GenAI
creates
a
fundamental
restructuring
of
both
headcount
and
work
patterns.
The
50%
reduction
in
junior
associate
positions
reflects
the
extensive
automation
of
tasks
that
traditionally
formed
the
foundation
of
junior
associate
work.
We
don’t
foresee
the
elimination
of
the
junior
ranks
altogether
because
of
the
need
for
law
firm
continuity
and
support;
however,
there
will
be
a
repurposing,
which
junior
legal
professional
likely
will
embrace.
No
longer
will
junior
legal
professionals
be
subjected
to
the
monotony
of
document
review
and
adaptation
of
templates
and
legal
forms
into
deliverables.
Indeed,
routine
document
review,
basic
legal
research,
and
initial
drafting
of
standard
documents
can
easily
transition
to
AI
systems,
requiring
fewer
but
more
technically
skilled
junior
attorneys.
The
remaining
junior
associates
experience
a
40%
reduction
in
billable
hours
per
matter,
but
their
work
becomes
more
intellectually
engaging
and
valuable
to
the
firm.
Associate
happiness
and
professional
gratification
should
increase.
Document
processing
accelerates
dramatically
through
AI
assistance,
while
research
capabilities
expand
through
sophisticated
natural
language
processing
tools.
Rather
than
spending
hours
on
grunt
work,
junior
associates
will
focus
on
refining
AI-generated
content
and
handling
the
more
complex
aspects
of
each
matter
that
require
human
judgment
and
creativity.
The
streamlined
review
processes
allow
them
to
handle
a
larger
number
of
matters
simultaneously,
developing
broader
experience
more
rapidly
than
in
the
traditional
model.
Ancillary
Effects
of
GenAI
Adaptation
The
transition
to
GenAI
requires
a
comprehensive
strategic
response
across
multiple
dimensions.
Firms
must
fundamentally
reimagine
their
service
delivery
model
while
maintaining
profitability
during
the
transition.
This
transformation
presents
opportunities
to
develop
new
revenue
streams
through
AI-enabled
service
packages
that
leverage
increased
processing
capacity,
rapid
response
capabilities
and
self-service
options.
Forward-thinking
firms
are
already
positioning
themselves
to
their
clients
for
things
like
eDiscovery,
offering
process
optimization,
and
other
advisory
services
that
extend
beyond
traditional
legal
counsel.
Cost
management
becomes
particularly
crucial
during
this
transition.
The
reduction
in
junior
staff
headcount,
while
potentially
challenging
from
a
cultural
perspective,
offers
significant
cost
savings.
This
shift
also
creates
opportunities
to
rethink
office
space
requirements,
as
automated
processes
and
remote
work
capabilities
reduce
the
need
for
traditional
physical
infrastructure.[6]
The
implementation
of
automated
administrative
functions
and
streamlined
workflow
processes
further
contributes
to
operational
efficiency
and
cost
reduction.
The
elusive
concept
of
“value”
represents
perhaps
the
most
nuanced
aspect
of
the
legal
industry’s
strategic
response
to
the
GenAI
threat.
Firms
must
balance
the
efficiency
gains
from
GenAI
against
client
expectations
for
cost
savings.
This
balance
can
be
achieved
through
innovative
pricing
models
that
benefit
both
the
firm
and
its
clients.
Premium
pricing
for
ultra-strategic
services,
gainsharing
arrangements,
outcome-dependent
pricing,
and
rapid
services
delivery
premiums
should
become
more
prevalent
in
the
GenAI
era.
Also,
volume-based
pricing
models
will
be
more
attractive,
as
firms
can
handle
significantly
larger
workloads
with
the
same
personnel
and
infrastructure.
Technology-enabled
fixed
fee
arrangements
can
provide
predictability
for
clients
while
allowing
firms
to
capture
the
value
of
their
technology
investments.
Whatever
the
structure,
the
emergence
of
GenAI
will
allow
for,
or
perhaps
mandate,
engagements
with
more
creative,
client-friendly
revenue
models.
Strategic
Resource
Reallocation
Understanding
historical
work
patterns
via
timekeeping
data
enables
firms
to
make
informed
decisions
to
maximize
revenue.
But
that
same
analysis
informs
headcount
needs
and
resource
allocation
in
the
GenAI
era
as
well.
With
the
benefit
of
technology-enabled
task
classification
and
workflow
analysis
of
billing
data,
law
firms
can
identify
which
practice
areas
face
the
greatest
disruption
from
AI
automation
and
how
that
disruption
affects
resource
allocation,
headcount
needs,
and
workflow.
Aspects
of
certain
practice
areas,
such
as
due
diligence
in
transactional
work
and
document
review-heavy
litigation,
may
require
significant
restructuring.
Other
areas
that
involve
complex
advisory
work,
like
regulatory
advice
or
tax
structuring,
might
need
only
minimal
adjustments
to
personnel,
resources,
or
workflow.
Firms
must
develop
more
concrete
plans
for
resource
reallocation,
because
legal
professionals
will
be
working
differently
in
the
future.
Professionals
whose
current
roles
face
significant
automation
should
be
retrained
and
redirected
toward
higher-value
work
that
leverages
their
legal
knowledge
in
new
ways.
Some
legal
professionals
can
transition
into
new
roles
managing
and
optimizing
GenAI
systems
and
the
workflow
generated
by
them.
Still
others
might
focus
on
developing
deeper
subject-matter
expertise
in
areas
resistant
to
automation.
The
Dangers
of
Flying
Blind
Many
firms
are
trying
to
capitalize
on
GenAI
solutions
without
first
mapping
their
current
operations,
creating
several
serious
risks
that
threaten
both
operational
efficiency
and
long-term
profitability.
In
the
initial
instance,
firm
mustn’t
take
shortcuts
when
it
comes
to
the
task
classification
and
workflow
analysis.
This
analysis
captures
and
quantifies
vital
information,
sets
a
baseline,
and
can
be
measured
and
remeasured
over
time.
After
all,
it
is
impossible
to
manage
what
you
cannot
measure.
This
step
makes
all
the
difference
between
success
and
failure.
The
second
major
risk
involves
misaligned
automation,
where
firms
invest
in
AI
solutions
for
tasks
that
aren’t
actually
the
best
candidates
for
automation.
This
misalignment
can
disrupt
efficient
workflows
while
failing
to
address
the
areas
where
AI
could
provide
the
greatest
benefit.
An
informed
task
classification
and
workflow
analysis
negates
this
risk.
A
third
critical
risk
involves
overlooked
dependencies
in
legal
workflows.
Without
a
thorough
understanding
of
how
different
tasks
and
professionals
interact,
firms
may
implement
automation
that
disrupts
critical
quality
control
mechanisms
or
creates
bottlenecks
in
service
delivery.
These
disruptions
can
damage
both
client
relationships
and
work
product
quality.
Resource
mismanagement
represents
another
significant
risk.
Without
clearly
identifying
which
professionals
will
be
most
affected
by
AI
automation,
firms
cannot
effectively
plan
for
retraining
and
reallocation
of
their
talent.
This
can
demoralize
and
under-utilize
the
skills
of
professionals
who
are
inclined
towards
sophisticated
work.
Mismanagement
also
leads
to
both
understaffing
in
critical
areas,
talent
and
proficiency
gaps,
and
retention
problems
as
professionals
become
uncertain
about
their
future
roles.
In
the
end,
all
risks
and
the
return
on
investment
calculation
point
back
to
the
fact
that
firms
implementing
AI
without
proper
baseline
analysis
can’t
accurately
measure
their
return
on
investment.
Without
clear
metrics
for
current
performance,
it
becomes
impossible
to
quantify
the
benefits
of
AI
implementation
or
identify
areas
where
the
technology
isn’t
delivering
expected
results.
Required
Actions
for
Success
Success
in
the
GenAI
era
will
require
fundamental
changes
in
how
law
firms
approach
pricing,
resource
allocation,
and
service
delivery.
Change
is
complex
and
normally
unwelcomed,
particularly
in
the
case
of
the
legal
industry.
But
change
strikes
us
as
inevitable
here.
Quite
simply,
the
traditional
hourly
billing
model
must
evolve
into
more
sophisticated
approaches
that
capture
value
rather
than
simply
time
spent.
These
new
pricing
models
should
share
efficiency
gains
with
clients
while
still
rewarding
the
expertise
and
judgment
that
remain
uniquely
human
contributions.
Pricing
models
must
also
create
greater
predictability
for
both
firms
and
clients,
moving
away
from
the
uncertainty
of
purely
time-based
billing.
Service
delivery
must
also
evolve
significantly.
Firms
need
to
standardize
routine
tasks
to
take
full
advantage
of
AI
capabilities
while
maintaining
mechanisms
for
integrating
human
expertise
where
it
adds
the
most
value.
This
requires
new
quality
control
mechanisms
and
often
means
significantly
accelerated
delivery
timelines,
as
AI
reduces
the
time
required
for
many
tasks.
As
with
any
organizational
change,
success
depends
upon
a
structured
approach
that
involves
thorough
strategic
analysis,
stakeholder
buy-in,
careful
implementation
and
execution,
and
conscientious
monitoring.
Firms
that
are
new
to
data-driven
analysis
should
leverage
knowledgeable,
data-savvy
external
resources
to
facilitate
the
initiative.
With
the
right
data
analytics
tools,
the
initial
analysis
phase
should
take
six
to
eight
weeks
of
a
comprehensive
review
of
historical
billing
data
to
understand
current
work
patterns
and
revenue
generation.
The
strategy
development
phase,
which
usually
takes
about
a
month,
focuses
on
modeling
the
potential
impact
of
GenAI
implementation
across
different
practice
areas
and
work
types.
This
modeling
includes
developing
recommendations
for
workflow
redesign,
planning
for
resource
reallocation,
and
creating
new
pricing
models
that
reflect
the
changed
economics
of
AI-augmented
legal
work.
The
implementation
planning
phase
then
addresses
the
practical
aspects
of
transformation,
including
systemically
implementing
AI
solutions,
developing
comprehensive
training
programs
for
professionals
at
all
levels,
creating
clear
client
communication
strategies
about
changes
in
service
delivery,
and
establishing
robust
frameworks
for
monitoring
performance
and
results.
Development
of
new
service
lines
should
proceed
based
on
market
opportunities
identified
during
the
early
phases.
The
implementation
period
establishes
the
foundation
for
the
firm’s
long-term
competitive
position
in
a
technology-enabled
legal
services
market.
After
initial
implementation,
the
next
phase
should
center
on
evaluation
and
refinement,
using
careful
analysis
of
pilot
program
results,
with
particular
attention
to
both
quantitative
metrics
and
qualitative
feedback
from
attorneys
and
clients.
Pricing
models
require
iterative
refinement
based
on
actual
usage
patterns
and
client
response.
Technology
adoption
should
expand
beyond
the
pilot
groups,
incorporating
lessons
learned
and
addressing
implementation
challenges
identified
in
the
initial
phase.
The
Path
Forward
As
with
most
of
our
works
of
authorship,
we
tend
to
make
intrepid
predictions.
In
this
case,
our
predictions
are
not
particularly
complex.
Law
firms
face
three
possible
responses
to
this
disruption,
each
with
significantly
different
implications
for
their
future
success.
The
first
option
–
resisting
change
and
maintaining
traditional
staffing
and
billing
models
–
leads
inevitably
to
declining
profitability
and
increasing
client
pressure
as
competitors
adopt
more
efficient
approaches.
The
second
option
–
making
only
incremental
adjustments
while
hoping
to
preserve
as
much
of
the
current
model
as
possible
–
merely
delays
the
inevitable
while
potentially
putting
firms
at
a
competitive
disadvantage.
The
third
path
–
proactively
embracing
transformation
by
developing
new
business
models
that
combine
human
expertise
with
technological
efficiency
–
offers
a
sustainable
way
forward.
Firms
that
successfully
navigate
this
transition
will
emerge
stronger,
with
more
sustainable
profit
margins
and
greater
competitive
advantages.
They
will
be
better
positioned
to
attract
and
retain
top
talent,
as
professionals
seek
firms
that
offer
clear
paths
forward
in
the
AI
era.
Most
important,
they
will
be
able
to
deliver
improved
client
satisfaction
through
more
efficient,
responsive
service
delivery.
Conclusion
The
AI
revolution
in
legal
services
demands
a
data-driven
response.
The
future
of
legal
services
has
arrived.
Though
the
short-term
challenges
are
significant,
firms
that
use
data
to
guide
their
transformation
can
create
sustainable
competitive
advantages.
The
key
is
to
move
quickly
but
thoughtfully,
using
analytics
to
inform
each
step
of
the
journey.
Understanding
historical
workflows
and
billing
patterns
is
crucial
for
identifying
which
aspects
of
practice
face
AI
disruption
and
how
to
transform
these
challenges
into
opportunities.
Success
requires
immediate
action
to
embrace
change
while
maintaining
their
commitment
to
excellence
in
legal
service
delivery—using
AI
to
augment,
rather
than
replace,
human
expertise.
[1]
Nancy
B.
Rapoport
and
Joseph
R.
Tiano,
Jr.,
Fighting
the
Hypothetical:
Why
Law
Firms
Should
Rethink
the
Billable
Hour
in
the
Generative
AI
Era
(December
31,
2024).
20
Washington
Journal
of
Law,
Technology
&
Arts
____
(forthcoming
Spring
2025)
(currently
available
at
SSRN:
https://ssrn.com/abstract=5080449).
With
the
reduction
in
headcount,
there
will
also
be
concomitant
reductions
in
related
expenses
like
allocated
administrative
overhead,
office
space,
allocated
technology,
and
training.
We
suspect
that
the
ongoing
debate
regarding
remote
working
versus
return
to
the
office
will
be
influenced
by
the
capabilities
of
GenAI
and
resource
adjustments.
Nancy
B.
Rapoport
is
a
UNLV
Distinguished
Professor,
the
Garman
Turner
Gordon
Professor
of
Law
at
the
William
S.
Boyd
School
of
Law,
University
of
Nevada,
Las
Vegas,
and
an
Affiliate
Professor
of
Business
Law
and
Ethics
in
the
Lee
Business
School
at
UNLV.
After
receiving
her
B.A.,
summa
cum
laude,
from
Rice
University
in
1982
and
her
J.D.
from
Stanford
Law
School
in
1985,
she
clerked
for
the
Honorable
Joseph
T.
Sneed
III
on
the
United
States
Court
of
Appeals
for
the
Ninth
Circuit
and
then
practiced
law
(primarily
bankruptcy
law)
with
Morrison
&
Foerster
in
San
Francisco
from
1986-1991.
Her
specialties
are
bankruptcy
ethics,
ethics
in
governance,
law
firm
behavior,
artificial
intelligence
and
the
law,
and
the
depiction
of
lawyers
in
popular
culture.
Joseph
R.
Tiano
Jr.,
Esq.
is
Founder
and
Chief
Executive
Officer
at
Legal
Decoder.
After
practicing
law
for
nearly
20
years,
Joe
founded
Legal
Decoder
because
he
saw
that
clients
lacked
the
analytic
tools
and
data
to
effectively
price
and
manage
the
cost
of
legal
services
delivered
by
outside
counsel.
Joe
set
out
to
build
an
intelligent,
data
driven
technology
company
that
would
revolutionize
the
way
that
legal
services
from
outside
counsel
are
priced
and
economically
evaluated.
Legal
Decoder’s
data
analytics
technology
is
used
in
law
firms
of
all
sizes
from
Am
Law
50
law
firms
to
boutique
firms;
Fortune
500
legal
departments
and
in
major
Chapter
11
bankruptcy
cases
(PG&E,
Purdue
Pharma,
Toys
R
Us,
and
others).
As
Elie
Mystal
mentioned
on
Thinking
Like
A
Lawyer’s
400th
episode,
we’re
still
wading
in
the
wake
of
what
SFFA
v.
Harvard
will
mean
for
well…
everyone.
That
said,
we’ve
definitely
made
some
predictions
about
what
will
be
next
on
the
chopping
block.
We’re
starting
to
get
some
answers.
Our
speculation
has
largely
been
focused
on
what
admissions
in
higher
ed
would
look
like
—
because
that’s
what
the
case
was
about
—
but
a
recent
letter
shows
we
should
be
just
as
interested
in
what’s
happening
in
K-12
education.
On
Valentine’s
Day,
the
Department
of
Education’s
Office
for
Civil
Rights
dropped
a
Dear
John
letter
telling
all
schools
interested
in
keeping
federal
aid
to
break
up
with
any
use
of
discrimination
by
race
or
its
proxies:
Although
some
programs
may
appear
neutral
on
their
face,
a
closer
look
reveals
that
they
are,
in
fact,
motivated
by
racial
considerations.
And
race-based
decision-making,
no
matter
the
form,
remains
impermissible.
For
example,
a
school
may
not
use
students
personal
essays,
writing
samples,
participation
in
extracurriculars,
or
other
cues
as
a
means
of
determining
or
predicting
a
student’s
race
and
favoring
or
disfavoring
such
students…Relying
on
non-racial
information
as
a
proxy
for
race,
and
making
decisions
based
on
that
information,
violates
the
law.
That
is
true
whether
the
proxies
are
used
to
grant
preferences
on
an
individual
basis
or
a
systematic
one.
While
the
word
choice
here
was
“determining”
and
“predicting,”
the
real
concern
is
seeing
how
long
it
takes
for
the
government
to
punish
“acknowledging
the
mention
of
race”
or
some
other
protected
characteristic
by
proxy.
And
it
might
not
seem
like
much
of
a
chilling
effect
for
now,
but
when
losing
federal
funding
is
on
the
line,
is
it
really
worth
a
school
risking
accepting
an
applicant
with
a
background
that
could
be
read
as
having
anything
to
do
with
diversity?
Would
a
school
risk
their
funding
for
accepting
a
student
who
talked
about
how
formative
participation
in
the
Urban
Debate
League
was
to
them
because
they
know
they
might
get
accused
of
using
“Urban”
as
a
proxy
for
Black?
Even
if
the
applying
student
happened
to
be
white?
If
a
student
applying
to
North
Carolina
Agricultural
and
Technical
State
University
has
her
application
rejected,
does
the
school
risk
losing
funding
because
her
application
*mentioned*
that
the
study
habits
and
leadership
skills
she
picked
up
as
a
Girl
Scout
in
her
writing
sample
and
Girl
Scouts
are
predominately
white?
Even
if
the
applicant
was
Black,
who
is
to
say
that
the
school
did
or
didn’t
discriminate
against
her
because
they
assumed
she
was
white?
The
problem
with
defending
against
“taking
a
closer
look”
rhetoric
is
that
once
the
seer
assesses
the
wrongdoer’s
“true
intentions”
and
flips
the
burden
of
proof,
good
luck
with
proving
the
negative.
Chris
Williams
became
a
social
media
manager
and
assistant
editor
for
Above
the
Law
in
June
2021.
Prior
to
joining
the
staff,
he
moonlighted
as
a
minor
Memelord™
in
the
Facebook
group Law
School
Memes
for
Edgy
T14s.
He
endured
Missouri
long
enough
to
graduate
from
Washington
University
in
St.
Louis
School
of
Law.
He
is
a
former
boatbuilder
who
is
learning
to
swim, a
published
author
on
critical
race
theory,
philosophy,
and
humor,
and
has
a
love
for
cycling
that
occasionally
annoys
his
peers.
You
can
reach
him
by
email
at [email protected] and
by
tweet
at @WritesForRent.
The
first
installment
of
The
General
Counsel
Report
2025
reads
like
something
Indiana
Jones
dusted
off
from
an
ancient
tomb.
A
relic
of
a
long,
lost
civilization
known
as
the
In-House
Lawyers,
circa
the
summer
of
2024.
The
report,
put
together
by
FTI
Consulting
and
Relativity
based
on
interviews
conducted
by
Ari
Kaplan
Advisors
and
surveys
by
Censuswide,
gathered
insights
from
corporate
legal
leaders
from
July
to
September
2024.
It’s
a
slice
of
life
detailing
the
hopes
and
fears
of
legal
officers
concerned
about
heightened
regulation,
the
growing
importance
of
ESG
initiatives,
and
navigating
investigations.
Seems
as
though
they
might
have
different
concerns
in
February
2025.
A
mere
month
into
Trump
II:
Muskrat
Love,
the
administration
has
moved
swiftly
to
gut
regulatory
oversight,
reverse
diversity
initiatives,
and
publicly
retreat
from
white-collar
criminal
probes
(except
to
prosecute
companies
for
diversity,
that
is).
While
the
report
includes
a
few
nods
toward
the
risk
of
a
changing
environment,
the
respondents
by
and
large
describe
a
sliding
doors
world
of
continued
cautious
regulation
in
a
steadily
growing
economy.
Regulation:
From
“Overload”
to
Open
Season
When
surveyed
last
summer,
41
percent
of
GCs
ranked
regulatory
compliance
as
their
number
one
risk.
While
it’s
the
second
year
in
a
row
that
regulation
topped
their
concerns,
the
figure
still
reflected
a
sharp
increase
from
30
percent
the
year
before.
Trump
rolled
back
—
or
at
least
attempted
to
roll
back,
depending
on
your
sense
of
the
judiciary’s
willingness
to
enforce
the
Administrative
Procedure
Act
—
100
or
so
regulations
on
his
first
day.
Since
then,
he
hasn’t
stopped
with
everything
from
environmental
to
labor
to
basic
occupational
safety
getting
the
(attempted)
ax.
Additionally,
when
asked
about
what
areas
of
work
have
increased
in
volume,
new
regulations
and
laws
requiring
policy
refreshes
and
headcount
topped
the
list,
with
74%
listing
this
as
an
area
of
increased
work.
Comparatively,
the
quantitative
survey
asked
respondents
to
rank
the
top
five
areas
that
require
the
most
time
from
legal
departments;
26%
included
compliance
monitoring
and
25%
said
regulatory
investigations.
But
all
this
regulatory
chaos
presents
its
own
risk.
Policy
refreshes
don’t
just
mean
new
rules
—
they
also
mean
deleting
the
old
ones
at
breakneck
speed.
Any
legal
team
that
prepped
for
an
onslaught
of
new
regulations
faces
the
new
compliance
nightmare
of
dealing
with
evaporating
rules.
Blunting
these
concerns
is
the
continued
existence
of
the
overseas
markets
committed
to
running
21st-century
economies
even
while
Trump
wants
to
party
like
it’s
1899
when
child
labor
was
booming
and
tariffs
fueled
America’s
routine
financial
panics.
ESG:
From
Compliance
Risk
to
Political
Target
Environmental,
Social,
and
Governance
compliance
rated
as
a
top-five
legal
risk
for
respondents,
with
more
than
35
percent
placing
it
in
the
top
tier.
According
to
the
report
many
expected
the
area
to
remain
a
complex,
moving
target
with
investors
maintaining
pressure
upon
companies
to
live
up
to
their
pledges
while
noting
some
nascent
pushback.
As
a
result,
there
is
no
way
to
fully
ensure
readiness.
Another
general
counsel
explained,
“We
are
getting
better
and
continue
to
hire
outside
specialists
in
recognition
of
the
need
to
improve.
Most
organizations
are
prepared…However,
we
are
starting
to
see
a
backlash
against
ESG…if
you
recognize
something
other
than
a
commercial
or
economic
value,
you
are
not
necessarily
acting
in
the
best
interests
of
your
shareholders.”
It’s
an
inversion
of
corporate
risk.
Companies
that
previously
feared
liability
for
not
doing
enough
on
ESG
now
risk
scrutiny
for
doing
too
much.
It
was
already
a
moving
target,
now
it’s
more
Whac-a-Mole
as
law
departments
face
corporate
governance
strategies
that
were
best
practice
six
months
ago
becoming
potential
legal
liabilities.
Investigations:
The
Unexpected
Pivot
The
report
identifies
internal
investigations
as
one
of
the
most
time-consuming
and
high-risk
areas
for
legal
teams.
Nearly
one-third
of
GCs
reported
a
rise
in
disputes
and
civil
litigation,
while
35
percent
flagged
internal
investigations
as
the
top
trigger
for
legal
action.
The
General
Counsel
Report
2025
isn’t
much
of
a
roadmap
at
this
point
as
much
as
a
faded
treasure
map
leading
straight
into
a
booby-trapped
regulatory
hellscape.
But
it
does
highlight
that
the
biggest
challenge
for
in-house
counsel
right
now
is
agility.
Between
the
radical
shift
in
priorities
and
the
administration
committing
to
a
speedrun
to
reverse
decades
of
regulatory
framework
(courts
and
statutes
be
damned),
corporate
legal
has
to
move
fast.
While
slashing
regulation
might
sound
like
it
takes
a
load
off
corporate
legal,
the
sudden
absence
of
guardrails
is
just
as
much
a
legal
migraine
—
especially
when
the
rest
of
the
world
isn’t
racing
to
see
how
fast
they
can
torpedo
corporate
governance.
How
do
AI-driven
legal
research
platforms
—
specifically
those
that
provide
direct
answers
to
legal
questions
—
stack
up
against
each
other?
That
was
the
question
at
a
Feb.
8
meeting
of
the
Southern
California
Association
of
Law
Libraries,
where
a
panel
of
three
law
librarians
reported
on
their
comparison
of
the
AI
answers
delivered
by
three
leading
platforms
–
Lexis+AI,
Westlaw
Precision
AI,
and
vLex’s
Vincent
AI.
While
all
three
platforms
demonstrated
competency
in
answering
basic
legal
research
questions,
the
panel
found,
each
showed
distinct
strengths
and
occasional
inconsistencies
in
their
responses
to
the
legal
queries
the
librarians
put
to
them.
But
after
testing
the
platforms
using
three
separate
legal
research
scenarios,
the
panelists’
broad
takeaway
was
that,
while
AI-assisted
legal
research
tools
can
provide
quick
initial
answers,
they
still
should
be
viewed
as
starting
points
rather
than
definitive
sources
for
legal
research.
“This
is
a
starting
point,
not
an
ending
point,”
said
Mark
Gediman,
senior
research
analyst,
Alston
&
Bird,
who
was
one
of
the
three
panelists,
stressing
the
continued
importance
of
using
traditional
legal
research
skills
to
verify
the
AI’s
results.
Evaluating
Three
Legal
Questions
I
did
not
attend
the
panel.
However,
I
was
provided
with
an
audio
recording
and
transcript,
together
with
the
slides.
This
report
is
based
on
those
materials.
In
addition
to
Gediman,
the
other
two
law
librarians
who
compared
the
platforms
and
presented
their
findings
were:
Cindy
Guyer,
senior
knowledge
and
research
analyst,
O’Melveny
&
Myers.
Using
each
of
the
platforms,
they
researched
three
questions,
all
focused
on
California
state
law
or
federal
law
within
the
9th
U.S.
Circuit
Court
of
Appeals,
which
covers
California:
What
is
the
time
frame
to
seek
certification
of
an
interlocutory
appeal
from
the
district
court
in
Ninth
Circuit?
Is
there
a
private
right
of
action
under
the
California
Reproductive
Leave
Loss
for
Employees
Act?
What
is
the
standard
for
appealing
class
certification?
(California)
They
evaluated
the
results
delivered
by
each
platform
using
six
factors:
Accuracy
of
answer.
Depth
of
answer.
Cited
primary
sources.
Secondary
sources
cited.
Format
of
answer.
Iterative
options.
First
Question:
Appeal
Timeframe
For
the
first
question,
regarding
the
timeframe
for
interlocutory
appeal
certification
in
the
Ninth
Circuit,
all
three
platforms
identified
the
correct
answer,
which
is
10
days
after
entry
of
the
certification
order.
The
answer
given
by
Lexis+
AI
properly
included
a
citation
to
the
controlling
federal
statute,
as
well
as
related
case
law,
and
put
the
citations
directly
in
the
text
of
the
answer,
as
well
as
listing
them
separately.
When
the
panelist
asked
it
a
follow-up
question
about
how
the
10
days
is
calculated,
it
gave
what
she
considered
to
be
a
good
explanation.
Westlaw
Precision
AI
performed
pretty
much
the
same
as
Lexis,
answering
the
question
correctly
and
providing
the
answer
in
substantially
the
same
form
and
citing
substantially
the
same
authorities.
It
also
included
the
citations
directly
within
the
text
of
the
answer.
Vincent
AI,
while
also
providing
the
correct
answer,
cited
different
cases
than
the
Lexis
and
Westlaw.
It
also
showed
some
inconsistency
in
how
it
presented
authorities,
with
the
key
governing
statute
appearing
in
the
answer
but
not
in
the
accompanying
list
of
legal
authorities.
Second
Question:
Private
Right
of
Action
The
second
question,
concerning
private
a
right
of
action
under
California’s
2024
Reproductive
Leave
Loss
Act,
revealed
more
significant
differences
among
the
platforms.
This
question
was
particularly
challenging,
panelist
Gediman
said,
in
that
it
involved
legislation
that
took
effect
just
over
a
year
ago,
on
Jan.
1,
2024.
Lexis+
AI
and
Westlaw
Precision
AI
reached
similar
conclusions,
both
finding
no
explicit
private
right
of
action.
However,
Vincent
AI
reached
the
opposite
conclusion,
finding
that
there
is
a
private
right
of
action.
Notably,
it
found
a
relevant
regulatory
provision
that
the
other
platforms
missed.
In
arriving
at
its
answer,
it
also
interpreted
statutory
language
in
a
way
that
the
panelist
said
was
“an
arguable
assumption
but
not
explicitly
stated.”
“Now
that
does
not
mean
that
Westlaw
and
Lexis
were
wrong
and
Vincent
was
right
or
vice
versa,”
Gediman
said.
“It
just
points
out
the
fact
that
AI
is
tricky,
and
…
it
doesn’t
matter
…
how
many
times
you
put
a
question
in,
each
answer
is
going
to
be
a
little
bit
different
each
time
you
get
it,
even
if
it’s
on
the
same
system.”
Still,
Gediman
was
impressed
with
Vincent’s
performance
on
this
question,
finding
relevant
language
in
a
regulation
that
was
not
specific
to
the
law
in
question.
“It
managed
…
to
find
relevancy
in
a
slightly
broader
frame
of
reference
to
apply,
and
I
thought
that
was
pretty,
pretty
cool,”
Gediman
said.
“I
wouldn’t
have
found
this
on
my
own,
quite
honestly,
and
I
like
to
think
I’m
a
pretty
decent
researcher.”
Third
Question:
Standard
of
Appeal
For
the
third
question,
regarding
the
standard
for
appealing
class
certification
in
California,
all
three
AI
tools
correctly
identified
the
abuse
of
discretion
standard,
but
their
presentations
varied
significantly.
A
key
difference
among
them
related
to
something
called
the
“death
knell”
doctrine,
which
requires
denials
of
class
actions
in
California
to
be
appealed
immediately.
On
this
question,
Lexis+
AI
provided
the
correct
answer
as
to
the
standard,
and
Guyer,
the
panelist
who
tested
it,
thought
the
first
paragraph
of
its
answer
did
a
good
job
of
setting
out
the
important
information,
including
the
factors
courts
look
to
in
determining
abuse
of
discretion.
But
she
thought
subsequent
paragraphs
became
redundant,
citing
the
same
cases
multiple
times.
Importantly,
however,
the
Lexis+
AI
answer
did
not
mention
the
“death
knell”
issue
regarding
the
need
to
file
an
immediate
appeal.
“That
was
kind
of
important
to
me,”
Guyer
said.
Westlaw
Precision
AI
also
got
the
standard
right
and
included
the
crucial
warning
about
the
immediate
appeal
requirement.
But
Guyer
took
issue
with
the
way
it
presented
its
answer
in
a
list
format
that
could
have
been
confusing
to
a
researcher
and
might
not
have
alerted
them
about
the
death
knell
issue.
She
also
found
that
many
of
the
secondary
sources
cited
in
support
of
the
answer
were
not
relevant,
often
drawing
on
federal
law
when
the
question
involved
a
state
statute.
Vincent
AI
offered
perhaps
the
most
well-rounded
response,
Guyer
thought,
calling
it
a
“great
answer.”
It
provided
both
a
concise
initial
answer
and
a
detailed
explanation,
including
a
unique
“exceptions
and
limitations”
section
reminiscent
of
practice
guides
that
highlighted
the
death
knell
warning.
Although
Vincent’s
initial
answer
also
cited
to
some
irrelevant
secondary
sources,
Guyer
liked
that
Vincent
has
a
feature
whereby
the
researcher
can
check
boxes
next
to
sources
and
eliminate
them,
and
then
regenerate
the
answer
based
only
on
the
remaining
sources.
“I
love
that
control
that
they
give
the
user
to
be
part
of
this
gen
AI
experience
in
terms
of
what
you
want,”
she
said.
Guyer
also
liked
that
the
Vincent
AI
answer
could
be
exported
and
shared
for
collaboration
with
others.
Provided
they
also
have
a
Vincent
AI
subscription,
they
can
click
on
a
link
and
go
in
and
view
the
full
AI
answer,
as
well
as
manipulate
and
regenerate
the
query.
Summing
It
All
Up
The
panelists
summed
up
their
evaluation
of
the
three
platforms
with
the
chart
you
see
below,
evaluating
each
of
the
six
factors
I
listed
above.
In
general
terms
across
all
three
questions,
each
platform
demonstrated
distinctive
strengths
in
how
they
presented
and
supported
their
answers,
the
panelists
said.
Lexis+
AI
consistently
showed
strong
integration
with
Shepard’s
citations
and
offered
multiple
report
formats.
Westlaw
Precision
AI’s
integration
with
KeyCite
and
clear
source
validation
tools
made
verification
straightforward,
though
the
platform’s
recent
shift
to
more
concise
answers
was
notable
in
the
responses.
Vincent
AI
stood
out
for
its
user
control
features,
allowing
researchers
to
filter
sources
and
regenerate
answers,
as
well
as
its
unique
relevancy
ranking
system.
For
the
panelists,
the
variations
in
responses,
particularly
for
the
more
complex
questions
and
recent
legislation,
underscored
that
these
AI
answer
tools
should
be
viewed
as
starting
points
rather
than
definitive
sources.
On
the
topic
of
vendor
transparency,
the
panelists
said
that
none
of
the
vendors
currently
disclose
which
specific
AI
models
they
use.
While
vendors
may
not
share
their
underlying
technology,
they
have
been
notably
responsive
to
user
feedback
and
quick
to
implement
improvements,
the
panelists
said.
The
panel
emphasized
that
despite
advances
in
AI
technology,
these
tools
require
careful
oversight
and
validation.
“Our
users
tend
to
think
that
AI
is
the
solution
to
all
of
their
life’s
problems,”
said
panelist
Livshits.
“I
spent
a
lot
of
time
explaining
that
it’s
a
tool,
not
a
solution,
and
explaining
the
limitations
of
it
right
now.”
Said
Gediman:
“Whenever
I
give
the
results
to
an
attorney,
I
always
include
a
disclaimer
that
this
should
be
the
beginning
of
your
research,
and
you
should
review
the
results
for
relevance
and
applicability
prior
to
using
it,
but
you
should
not
rely
on
it
as
is.”
Kathryn
Joe
