It’s
early
2027.
Most
law
firms
and
in-house
legal
departments
are
rapidly
moving
to
OpenAI
Legal
which
launched
in
the
third
quarter
of
2026.
Most
of
them
cite
cost
since
OpenAI
Legal
is
still
just
$20
per
month.
They
are
also
confident
that
OpenAI
has
addressed
privacy
and
confidentiality
concerns,
and
that
its
new
automatic
cite-checking
ability
can
accurately
verify
all
outputs.
What’s
remarkable
about
the
shift
is
not
so
much
that
it
happened
but
the
speed
at
which
the
transition
was
made.
This
Is
Commoditization
The
above
hypothetical
is
what
happens
when
a
product
becomes
commoditized,
which
happens
often.
A
commoditized
product
is
one
that
has
become
so
commonplace
and
interchangeable
that
it
loses
its
uniqueness.
And
when
that
happens,
it
also
loses
its
pricing
power.
Why?
Once
commoditization
occurs,
users
see
little
meaningful
difference
between
the
various
vendor
options
other
than
price.
So,
sellers
can’t
charge
a
premium
for
what
they
provide,
particularly
when
the
lower
cost
option
provides
roughly
the
same
features,
quality,
and
performance.
Some
examples
include
things
like
economy
seats
on
airlines:
most
customers
shop
based
on
price
and
the
difference
in
service
is
relatively
small.
Another
example
is
cloud
storage
which
is
now
an
expected
feature
—
providers
are
interchangeable,
and
the
market
is
price-driven.
Commoditization
shows
up
in
legal
tech
if
tools
that
once
felt
novel
become
expected
infrastructure.
At
that
point,
lawyers
stop
asking
“what
does
this
do?”
and
start
asking
“why
does
this
cost
more
than
the
other
one?”
If
it
happens
to
GenAI,
it
will
have
direct
impact
on
legal
tech
vendors
whose
products
are
based
on
GenAI.
And
their
customers.
Indeed,
a
pretty
big
tech
player
may
be
betting
that
this
may
soon
happen
with
GenAI.
As
Chance
Miller
noted
in
a
recent
episode
of
the
daily
9to5
Daily,
citing
a
report
in
The
Information
by
Aaron
Tilley,
the
potential
for
commoditization
may
be
why
Apple
is
proceeding
cautiously
with
developing
its
own
GenAI
tools
and
it
could
foreshadow
what
may
happen
in
legal.
Tilley
says
(emphasis
added):
Apple
still
has
a
team
working
on
its
own
internal
models
that
it
could
take
advantage
of
in
the
future.
But
some
Apple
leaders
hold
the
view
that
large
language
models
will
become
commodities
in
the
years
to
come
and
that
spending
a
fortune
now
on
its
own
models
doesn’t
make
sense.
Here’s
what
Miller
concludes:
“If
Apple
leadership
truly
does
believe
LLMs
will
become
commodities,
then
the
company’s
AI
success
will
depend
less
on
bespoke
new
models,
and
more
on
its
ability
to
control
the
hardware,
software,
and
services
that
AI
runs
on.”
Commoditization
of
Legal
GenAI
Thus
far,
legal
GenAI
vendors
have
faced
little
competition
from
outside
the
legal
community.
But
what
would
happen
if,
say,
OpenAI
decided
to
target
the
legal
market
and
release
general
tools
offering
the
strong
privacy
protections,
enhanced
accuracy,
and
stronger
security
lawyers
and
legal
professionals
crave?
If
this
were
to
occur,
other
players
like
Google,
Anthropic,
and
Perplexity
might
follow.
The
greater
market
power
of
these
companies
could
shift
the
legal
GenAI
market
towards
commoditization,
where
price
becomes
the
primarily
criterion.
It
was
just
this
kind
of
thing
I
mentioned
in
my
post
about
a
Business
Insider
interview
of
the
founders
of
Harvey,
Winston
Weinberg
and
Gabe
Pereyra,
back
in
October.
At
that
point
I
noted
their
statements
to
the
effect
that
they
were
less
concerned
about
legal
tech
vendors
and
more
about
competition
from
OpenAI
itself.
Somewhat
candidly,
they
admit
that
OpenAI
could
enter
the
legal
tech
space
directly
and
cut
out
the
middleman
legal
tech
vendors.
These
statements
prompted
me
to
observe:
“[Weinberg
and
Pereyra]
admit
that
OpenAI
could
enter
the
legal
tech
space
directly
and
cut
out
the
middleman
legal
tech
vendors.
Moreover,
even
if
OpenAI
never
targets
the
legal
field
directly,
it
very
well
could
release
general
tools
offering
the
strong
privacy
protections,
enhanced
accuracy,
and
stronger
security
lawyers
and
legal
professionals
crave.
In
fact,
OpenAI recently
mentioned a
contract
review
tool
it
developed
and
is
using
internally.”
Today’s
Legal
AI
Marketplace
Today,
there
is
a
plethora
of
vendors
offering
all
sorts
of
GenAI
tools
at
a
fairly
high
price.
Their
argument
is
that
legal
is
a
specialized
market
due
to
a)
the
ethical
and
privacy
concerns
and
b)
the
need
for
accuracy.
They
go
on
to
say
that
only
they
can
offer
the
protections
the
specialized
market
requires
and
that
open
or
public
systems
like
ChatGPT,
Gemini,
Perplexity,
or
Claude
simply
can’t
meet
legal
demands.
Some
even
go
so
far
as
to
say
it’s
malpractice
to
use
the
open
systems.
And
when
it
comes
to
legal
research,
vendors
explain
that
only
they
have
the
data
to
make
the
systems
work
accurately
and
that
this
moat
protects
them.
But
the
moat
is
not
foolproof.
The
vendor
argument
ignores
that
the
moat-protected
legal
research
is
only
part
of
overall
legal
needs.
Moreover,
much
of
the
data
also
exists
within
client
databases
that
are
not
protected.
More
importantly,
big
players
like
Google
and
OpenAI
or
any
of
the
other
large
players
could
simply
license
or
acquire
the
data
themselves,
spreading
those
costs
across
far
more
customers
while
still
undercutting
specialized
vendors
on
price.
Also,
ignoring
for
the
moment
that
their
GenAI
tools
are
also
capable
of
making
mistakes
and
making
stuff
up,
a
characteristic
of
LLMs
that
is
intractable,
legal
tech
vendors
assume
that
just
because
the
open
systems
haven’t
made
the
case
that
their
products
can
meet
legal’s
requirements,
they
won’t.
Indeed,
many
of
the
vendor
products
depend
in
part
on
those
open
systems’
platforms
to
make
their
products
function.
And
OpenAI
at
least
is
an
investor
in
legal
vendors
like
Harvey.
And
as
far
as
the
hallucination
and
inaccuracy
problem
goes,
we
are
already
seeing
vendors
like
Clearbrief
offering
solutions
to
the
hallucination
problem
with
tools
that
automatically
verify
LLM
outputs
primarily
with
non-GenAI
tools.
That
potentially
solves
the
cost
of
verification
problem.
What
if
OpenAI
decided
to
do
the
same?
A
Reality
for
Legal
Could
GenAI
legal
tools
become
commoditized?
The
short
answer
is
yes.
The
open
GenAI
providers
have
vast
resources
and
capabilities.
There
is
little
to
stop
them
from
offering
the
privacy
and
confidentiality
protections
that
lawyers
demand.
There
is
little
to
prevent
them
from
offering
tools
like
that
being
offered
by
Clearbrief.
And
if
they
put
their
minds
to
it,
they
could
provide
many
of
the
same
tools
the
legal
tech
vendors
who
trumpet
their
uniqueness
do
now.
And
if
that
happens,
the
legal
GenAI
vendors
could
lose
their
uniqueness
and
pricing
power.
The
big
GenAI
players
would
be
forced
to
compete
primarily
on
price.
Legal
tech
vendors
may
not
be
able
to
legitimately
compete
on
that
basis:
they
have
neither
the
financial
staying
power
nor
resources.
The
bigger
players
can
spread
costs
across
many
more
customers,
legal
and
non-legal,
can
bundle
features
into
larger
platforms,
and
absorb
margin
pressure
longer
than
the
smaller
legal
vendors.
And
let’s
not
forget
many
lawyers
already
used
the
open
tools
to
do
all
sorts
of
things,
so
transitioning
to
relying
on
them
for
everything
would
be
neither
difficult
nor
time-consuming.
Thus
far,
the
open
GenAI
providers
have
been
content,
like
Microsoft,
to
merely
offer
their
tools
to
the
legal
tech
vendors
as
wrappers.
But
that
doesn’t
mean
the
open
systems
won’t
decide
to
compete
directly.
So,
What’s
Legal
to
Do?
It
would
be
easy
for
law
firms
to
just
throw
up
their
hands
and
just
ignore
the
commoditization
potential.
But
that’s
not
necessarily
correct.
In
fact,
law
firms
and
in-house
departments
can
do
some
things
to
better
prepare
for
what
may
be
the
inevitable
commoditization
of
GenAI
tools.
But
law
firms
typically
ignore
what’s
developing
in
the
tech
market
until
it
already
happens.
By
doing
so,
they
risk
waking
up
one
morning
locked
into
a
bunch
of
overpriced
technology
when
there
are
just
as
good
and
cheaper
products
suddenly
available.
Firms
can
avoid
this
by
paying
attention
to
what
is
going
on
in
the
marketplace
and
what
vendors
are
doing.
Indeed,
the
best
strategy
right
now
may
be
to
keep
their
powder
dry.
To
pay
attention
to
the
marketplace.
To
regularly
review
and
monitor
their
tech
stack
and
tech
contractual
commitments.
To
avoid
long-term
contractual
commitments
that
lock
them
in.
To
look
hard
at
things
like
termination
rights
and
obligations.
And
to
make
sure
they
have
an
exit
strategy
should
things
quickly
change.
Stephen
Embry
is
a
lawyer,
speaker,
blogger,
and
writer.
He
publishes TechLaw
Crossroads,
a
blog
devoted
to
the
examination
of
the
tension
between
technology,
the
law,
and
the
practice
of
law.