As
the
year
winds
down,
the
legal
profession
is
flooded
with
retrospectives:
the
growing
AI
adoption
rate
by
solos
and
smalls
(now
around 70%),
ways
that
AI
is leveling
the
playing
field between
large
and
small
firms
(including
on
the
hallucination
front where
large
firms
and
solos
are
equal
offenders)
and
the
familiar
observation
noting
the shift
from
chat-based
tools
to
agentic
systems.
Much
of
this
commentary
is
accurate
—
but
it’s
also
repetitive
and
boring.
Rather
than
regurgitate
what
most
lawyers
already
know
or
could
readily
learn
from
AI,
I’ll
take
a
different
approach
and
examine
five distinct
business
models
that
offer
new
opportunities
for
solo
and
small-firm
lawyers
in
the
AI
age.
Let’s
take
a
step
back.
According
to Wikipedia, a
business
model
describes
how
a
business
organization
creates,
delivers,
and
captures
value.
For
decades,
law
firm
business
models
have
been
downright
boring,
largely
based
on
selling
time
in
billable
increments.
That’s
changed
to
some
degree
in
recent
years
with
flat
fees
and
law
subscription
models
like
Mathew
Kerbis’s The
Subscription
Attorney,
but
these
approaches
—
along
with six
new
law
business
models that
I
imagined
years
ago
—
never
gained
any
real
traction.
In
AI
era,
all
of
that
may
change.
And
in
fact,
some
would
argue
that
it
has
to
change
since
with
AI
cutting
down
on
the
time
required
for
legal
tasks,
billable
revenue
is
bound
to
decline.
But
AI
can
also
power
new
business
models,
or
revive
traditional
ones.
Below
are
five
law
firm
business
models
for
the
AI
age
that
can
help
solo
and
small
law
firms
diversify
their
offerings.
1.
Artisanal
Legal:
“Good
Old-Fashioned
Law,”
Reimagined
The
first
model
may
seem
counterintuitive
in
an
AI-driven
era: Artisanal
Legal. This
is
the
deliberate
embrace
of
high-touch,
bespoke
legal
services
grounded
in
judgment,
strategy,
and
human
insight
—
augmented,
but
not
replaced,
by
AI.
In
this
model,
AI
operates
largely
behind
the
scenes.
It
supports
research,
drafting,
and
issue
spotting,
allowing
the
lawyer
to
focus
on
what
clients
value
most:
interpretation,
advocacy,
and
trust.
The
lawyer’s
brand
is
built
not
on
speed
or
scale,
but
on
craftsmanship.
Think
of
appellate
advocacy,
regulatory
counseling,
complex
negotiations,
and
niche
advisory
practices
where
outcomes
hinge
on
experience
rather
than
volume.
As
AI
commoditizes
routine
legal
outputs,
the
perceived
value
of
deep
expertise
and
individualized
counsel
will
increase,
not
decrease.
Clients
facing
high-stakes
matters
will
seek
lawyers
who
can
explain why a
strategy
works,
not
just
produce
a
document.
Artisanal
Legal
practices
will
likely
charge
premium
fees,
emphasize
reputation
and
referrals,
and
remain
relatively
small
by
design.
2.
Human-AI
Document
Review:
The
dott.legal
Model
At
the
opposite
end
of
the
spectrum
lies Human-AI
Document
Review,
exemplified
by
platforms
such
as dott.legal.
This
model
addresses
a
persistent
reality:
while
AI
is
exceptionally
good
at
sorting,
clustering,
and
flagging
documents, clients
and
courts
still
want
human
accountability.
As
part
of
this
model, clients
come
to
an
attorney
with
an
AI-generated
document,
and
the
attorney
steps
up
to
validate
and
certify
results.
This
model
requires
efficiency
and
subject
matter
familiarity.
Dott.legal
is
priced
at
$199
for
a
document
or
demand
letter
—
which
doesn’t
seem
workable
for
anything
longer
than
four
or
five
pages.
And
if the
document
is
a
real
clunker,
the
revisions
would
be
more
involved.
AI
can’t
solve
the
problem
because
the
model
promises
attorney
review.
Still
at
a
higher
price
point
at
scale
and
with
caveats
as
to
the
size
of
the
document,
this
model
may
have
legs.
3.
AI-Enabled
Contract
Lawyer
Services
(Shared
Access)
A
third
category
of
AI-enabled
legal
services
adapts
the
traditional
contract-lawyer
model
to
the
economics
of
modern
legal
technology.
As
the
cost
of
advanced
AI
research
and
discovery
tools
continues
to
rise
—
often
$1,000
per
month
or
more
—
many
solos
and
small
firms
cannot
justify
maintaining
subscriptions
for
occasional
use.
What
they can justify
is
paying
for
the
output
of
those
tools
when
a
matter
requires
it.
Under
this
model,
an
attorney
makes
the
upfront
investment
in
premium
AI-enhanced
platforms
—
such
as
comprehensive
Westlaw
products,
AI
research
tools,
or
enterprise
discovery
systems
—
and
offers
the
benefit
of
those
tools
to
other
lawyers
on
a
contract
basis.
The
service
is
sold
not
as
software
access,
but
as
lawyer-supervised
work
product,
preserving
ethical
compliance
and
professional
accountability.
For
example,
a
lawyer
with
a
full
Westlaw
AI
suite
could
provide
per-diem
or
project-based
services
such
as
50-state
surveys,
multijurisdictional
research
memoranda,
issue-spotting
analyses,
or
first-draft
briefs,
complete
with
supporting
authorities
and
research
trails.
The
hiring
firm
receives
high-quality,
defensible
work
product
without
incurring
ongoing
technology
costs,
while
the
providing
lawyer
monetizes
both
expertise
and
infrastructure.
The
same
model
applies
to
discovery
and
litigation
support.
A
lawyer
with
access
to
an
advanced
discovery
platform
can
manage
document
review,
privilege
analysis,
and
issue
tagging
for
other
firms,
using
AI
to
accelerate
review
while
maintaining
human
oversight.
Rather
than
each
firm
purchasing
and
mastering
complex
discovery
software,
discrete
litigation
functions
are
outsourced
to
a
specialist
who
already
has
the
tools
and
systems
in
place.
This
shared-access
approach
transforms
expensive
AI
platforms
into
revenue-generating
assets
and
creates
a
new
class
of
supercharged
contract
legal
services
—
faster,
more
scalable,
and
accessible
to
firms
that
do
not
need
full-time
ownership
of
advanced
legal
technology.
4.
Next-Generation
Law
Practices
Capturing
Older
Lawyer
Knowledge
One
of
the
most
underappreciated
opportunities
in
the
AI
age
is
the capture
and
reuse
of
institutional
legal
knowledge,
particularly
from
senior
and
retiring
lawyers.
Decades
of
expertise
—
how
to
handle
regulators,
negotiate
industry-specific
contracts,
or
manage
recurring
disputes
—
often
walks
out
the
door
when
a
lawyer
retires.
In
this
model,
law
practices
would
acquire
not
a
law
practice
but
senior
lawyers’
knowledge
which
could
be
encoded
into
AI
systems:
curated
document
libraries,
annotated
precedents,
decision
trees,
and
training
datasets.
These
systems
are
then
used
to
train
junior
lawyers,
support
client-facing
work,
or
even
generate
new
revenue
streams.
The
practice
becomes
not
just
a
provider
of
legal
services,
but
a knowledge
steward.
This
model
is
especially
powerful
in
niche
regulatory,
industry-specific,
or
regional
practices
where
tacit
knowledge
matters
more
than
published
law.
It
also
offers
a
compelling
succession
strategy.
Rather
than
selling
a
book
of
business,
older
lawyers
can
help
build
durable
systems
that
preserve
their
expertise
while
reducing
dependence
on
their
personal
availability.
5.
AI-Forward
Law
Firm
Offshoots
Another
emerging
model
is
the
creation
of
AI-forward
offshoots within
or
alongside
traditional
law
firms.
These
are
not
full-service
firms,
but
specialized
entities
focused
on
AI-enabled
services:
compliance
audits,
internal
investigations
support,
contract
analytics,
discovery
management,
or
regulatory
monitoring.
The
offshoot
structure
matters.
By
separating
these
services
from
the
core
firm,
lawyers
gain
flexibility
in
pricing,
staffing,
and
technology
adoption
without
disrupting
legacy
billing
models.
These
entities
may
employ
technologists,
project
managers,
and
non-lawyer
specialists
alongside
lawyers.
Clients
benefit
from
clarity:
they
know
they
are
buying
a
process-driven,
technology-enabled
service
rather
than
bespoke
legal
advice.
Firms
benefit
from
diversification
and
innovation
without
existential
risk
to
the
main
practice.
Over
time,
some
offshoots
may
grow
into
standalone
businesses
—
or
even
outpace
their
parent
firms
in
revenue.
Conclusion
The
AI
age
does
not
point
toward
a
single
future
for
law
practice
or
for
the
wholesale
extinction
of
lawyers.
Instead,
it
opens
multiple
viable
paths
—
each
with
different
tradeoffs
in
scale,
income,
identity,
and
impact.
Lawyers
who
focus
solely
on
AI
tools
without
thinking
about
the
underlying
business
model
risk
missing
the
larger
opportunity:
rethinking
how
legal
value
is
created
and
delivered.
Carolyn
Elefant
is
one
of
the
country’s
most
recognized
advocates
for
solo
and
small
firm
lawyers.
She
founded
MyShingle.com
in
2002,
the
longest-running
blog
for
solo
practitioners,
where
she
has
published
thousands
of
articles,
resources,
and
guides
on
starting,
running,
and
growing
independent
law
practices.
She
is
the
author
of
Solo
by
Choice,
widely
regarded
as
the
definitive
handbook
for
launching
and
sustaining
a
law
practice,
and
has
spoken
at
countless
bar
events
and
legal
conferences
on
technology,
innovation,
and
regulatory
reform
that
impacts
solos
and
smalls.
Elefant
also
develops
practical
tools
like
the AI
Teach-In to
help
small
firms
adopt
AI
and
she
consistently
champions
reforms
to
level
the
playing
field
for
independent
lawyers.
Alongside
this
work,
she
runs
the
Law
Offices
of
Carolyn
Elefant,
a
national
energy
and
regulatory
practice
that
handles
selective
complex,
high-stakes
matters.