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Welcome to Reinventing Professionals,
a podcast hosted by industry analyst
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Ari Kaplan, which shares ideas,
guidance, and perspectives from market
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leaders shaping the next generation
of legal and professional services.
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This is Ari Kaplan, and I'm speaking
today with Tony Muljadi, the General
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Manager of Large Law at LexisNexis.
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Hi, Tony.
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How are you?
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Hey, Ari.
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I'm great.
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Thank you so much for
having me on the podcast.
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It's my privilege.
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I'm looking forward to this conversation.
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So tell us about your background
and your role at LexisNexis.
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I grew up in Colorado but now I'm
a New Yorker, and started my career
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in management consulting and then
in internal strategy roles before
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coming to Lexis about six years ago.
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I started in our corporate strategy
group and then moved into our news
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and business division for a time where
I led strategy and customer success.
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And then I ended up on the legal side
of the house, which is actually the
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core business of LexisNexis legal
professional, and it's great to be here.
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I lead our large law segment.
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We define large law as any firm
with 50 attorneys or more in the US.
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I oversee all of go-to-market, so that's
sales, marketing, customer success and
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also inform our product strategy as well.
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How are law firms adapting
their AI strategy from
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experimentation to expectation?
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It's been an incredibly
fast transformation.
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Just a year ago, there was a lot
of talk of, should I be using
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AI or which AI should I use?
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At this point, all of the firms have
adopted one or more tools, so it's
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really about which ones am I going
to adopt more for which use cases?
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Where should I use different AI
tools in different parts of the firm?
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And also which firms are giving me the
most value in terms of both product
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but also the service that I'm receiving
from them, and how am I integrating my
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content, my know-how into the workflows
of AI, and what does that look like for
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my attorneys as they deliver client work?
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With access to different models no
longer being a factor, what is the
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differentiator in using these tools?
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The real differentiation
comes in a couple things.
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The first is the context, the second
is the harness, and the third is how
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you operationalize AI within your firm.
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So when we talk about the context,
that's really what goes into
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the model or the AI system.
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Obviously it's the firm's documents, but
it also could be proprietary content that
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a legal tech provider has, such as case
law or secondary content or even legal
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news as well as the firm's knowledge
and their ways of working and how they
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actually build that within the AI system.
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The second is what I call the harness.
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So this is the engineering that the
model has around it that can help it
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orchestrate, that grounds the answers,
that optimizes the actual output.
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It's in the way lawyers like to talk,
it's in the formats and even the font
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and the way it's set on the page.
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Those little things matter, and this
is where a lot of legal tech vendors
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play a role in terms of really honing
and tuning the model and also selecting
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the models for the best answer and
the best output for the attorney.
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And then the third part is the
operationalization, and that's really
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about how good the firm is in terms
of enabling their attorneys to use AI,
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making it easy to upload documents,
and this is where firms with strong
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KM groups, strong CIOs really thrive.
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As these AI capabilities begin to
converge why do authoritative legal
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content trust and integration into
those existing workflows matter?
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The model is just one layer of the cake.
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You need a full end product,
you need multiple layers
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and the filling in between.
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We believe, at least at LexisNexis,
that content and trust is absolutely
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for attorneys, and that's because
legal work has really asymmetric risk.
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You can't just be a little bit correct.
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Eighty/20 doesn't work like that in legal.
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When I was a management consultant,
we always talked about 80/20,
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and that's not the case in legal.
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There are sanctions.
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There's a lot of high risk
bet-the-farm-type transactions that
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are happening, so lawyers need to have
confidence in the answer being correct,
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that they have authority underneath it.
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And then also that trust
layers on into actual adoption.
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So if an attorney doesn't trust the output
that it's consistently getting from a
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tool, then the attorney's not gonna use
it, and so that is a major gap as well.
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And then lastly, the more you can
integrate the AI into the actual workflow
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of how the attorney may have done it
before or the best practice, and so that
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doesn't feel like it's moving away from
that process, but really integrating with
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the process that was being done or the
process that's best practice, that's where
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you see AI really be a multiplier versus
feeling like it's something completely
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different that needs to be relearned.
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Given the importance of collaboration,
what does a genuine strategic
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technology partnership look like today?
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It's been a change.
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It's no longer this vendor-customer
relationship where you're coming in with a
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sales team and just selling a subscription
and then seeing them again in three years.
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It's changed quite a bit.
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And admittedly, my business has
had to change how we operate and
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how we staff engagements, and so
it's really shared problem-solving.
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It's when the firm comes forward
with a real problem that they're
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trying to solve, maybe the partner
doesn't have an off-the-shelf solution
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for that, and so you need to come
together, you need to work that out.
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That might look like a different
account team than a salesperson
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and a customer success person.
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It might include those people, but
then more likely it will also include
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somebody that has a legal background.
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We call those people legal engineers.
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It might also include software
engineers that are front-end developers.
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That is a much more holistic account
team that's serving the client than
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you would have seen in the past.
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That's important because that helps
create the trust between the two.
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Both- sides are bringing
to bear lots of resources.
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This takes a lot of time and energy
from the firm as well, that you
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might be pulling away people who
are billable onto these projects
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to really invest in the future.
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And so that's a real strategic
partnership when both sides are
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putting skin in the game, and then
there's a feedback loop between the two
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where each side is learning from the
process and each side is benefiting.
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That's what I would say a true
partnership looks like these days.
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How do you define the role of a legal
engineer, and why is that becoming
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so important inside law firms today?
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It's the intersection of somebody with
strong legal domain expertise with
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more of a technical product-oriented
mindset helping to translate what is
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the attorney doing from a pure workflow
perspective, and then how do I translate
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that into a technical process that may
or may not involve AI-enabled steps.
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It's usually somebody with a JD
background that really can empathize
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with what the attorney is doing
with also that passion for AI, that
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understanding of technology and how
to break that into steps for the firm.
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And then the third part is actually
how do I enable that, knowing a lot
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of these people come from large law
firms, so they understand some of the
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barriers of adoption and how to convince
skeptical attorneys that this solution
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could really enhance their work.
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Where can legal engineers
create the most value?
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These are really high volume,
high friction workflows.
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Take an example of having to analyze
hundreds, maybe even thousands
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of contracts to compare them all.
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What would've taken hours and
maybe a human being would miss in a
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tabular view using AI could be done
in a matter of, less than an hour.
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So that's a great example where
an off-the-shelf AI capability, we
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call these skills at LexisNexis,
these skills can really just
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accelerate a process really quickly.
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I think the second area would be
where you're configuring something
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that's a little bit generic.
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Maybe it's a generic skill, but you're
configuring that specifically for the
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firm or for the person so that it fits
their way of doing things, it fits their
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voice, it fits their precedent documents.
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That would be a second area.
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And I think the third thing is
really back to general customer
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success of scaling what works.
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So finding what are the seeds that are
working, cultivating those seeds so they
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grow into workflows that are repeatable,
that can be scaled across the firm.
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That's really where the legal engineer
can see value because they're coming at
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it from a third party perspective and
able to see across different practice
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areas beyond what maybe an individual
attorney or a KM team might see.
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What are the most important questions a
law firm should ask a legal tech partner?
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Definitely what is your operating
model in terms of how are you gonna
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support us going into this initiative,
how are you gonna support us after?
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Understanding the full life cycle
of what this engagement could
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look like is immensely important.
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Having mutual understanding of metrics
and what does success look like at
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the end of this project or during
the project, what metrics will tell
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us that we're being successful.
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And then I think also understanding
what obviously are the technology
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components and products and
people to bear for the project.
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You wanna have trust that this partner has
access to the latest models, has access to
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the right content, has access to the right
people and experts to get the job done.
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What are the most important metrics that
a team should evaluate when determining
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whether they're having success with AI?
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I like to stay away from time
saved because it's really
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an input versus an output.
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Firms are still billing by the
hour, so it is something that is
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important to be aware of, but faster
is not always better in legal.
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You always want correct, you
want client satisfaction.
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I like to point to things
that are more around the end
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product, so client satisfaction.
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A little bit harder to measure,
but just the responsiveness, the
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ability to get back to customers.
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And also the depth of the relationships
you're building with them.
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These are all a little bit soft but if
I had to put more concrete metrics, I
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would look at the ability to take time
out, and is that fewer hours written off?
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Is it, higher value work that we're doing?
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Are we getting more
customers into the door?
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Are they more satisfied?
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Are we handling more
matters than we did before?
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Where do you expect the biggest
gap to emerge between AI leaders
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and firms that fall behind?
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It's definitely not gonna be around,
what technology they're using.
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These models are now available to
anybody willing to pay, so it's really
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around their organizational capability.
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Are they built to take on change?
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Are they built to really drive
adoption and think about their
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old ways of doing things, their
old workflows and redesign them?
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Firms that are reticent to take that
change on will fall behind in the gap.
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A second area would be their
ability to integrate their
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firm's knowledge and processes.
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If every firm is using the same technology
but not actually putting their unique
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thumbprint on their firm way of doing
things or their firm knowledge base, then
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you lose the differentiation completely.
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The firms that are able to integrate that
with AI will create a gap because that
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institutional knowledge will still show
up and create value for the firm even
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though technology has become an equalizer.
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I think the third thing would
be, and this probably is a couple
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years down the line, the firms that
actually change their business model.
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So maybe they change how
they staff their projects.
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Maybe they're able to hire more
rainmakers because the actual legal
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work being done is more efficient.
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Maybe they're able to price differently.
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Maybe they do value-based pricing or
non-billable not hour billable pricing.
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Perhaps they're faster
to respond to things.
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They're able to take on more of
a corporate legal department's
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full breadth of services.
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These are the things that will
really create a gap between
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firms that are adopting AI versus
those that are a lot slower.
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How do you see strong technology
partnerships empowering
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law firms in the future?
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The partnerships that are strongest
will show that they can continuously
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drive value for the firm and even drive
value for the legal tech providers.
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So the legal tech provider's learning as
well, may be able to scale to other firms.
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So they're continuously reinventing
the workflows rather than just
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implementing and then never looking
at it again continuously taking that
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feedback and improving together.
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And both sides are sharing in that
mutually beneficial learning where
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the technology partner gets more and
can really scale what they're doing
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for others and can really improve how
they're operating for their customer.
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But then also the firms are able
to gain a lot from the partner
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because the partner knows them.
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They're not having to reteach a different
partner every time in terms of how their
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firm operates and how to scale technology.
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This is Ari Kaplan speaking with
Tony Muljadi, the General Manager
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of Large Law at LexisNexis.
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Tony, thanks so very much.
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Thank you.
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I really appreciate it.
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Looking forward to connecting
when we see each other again.
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Thank you for listening to the
Reinventing Professionals podcast.
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Visit reinventingprofessionals.com or
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Welcome to Reinventing Professionals,
a podcast hosted by industry analyst
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Ari Kaplan, which shares ideas,
guidance, and perspectives from market
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leaders shaping the next generation
of legal and professional services.
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This is Ari Kaplan, and I'm speaking
today with Tony Muljadi, the General
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Manager of Large Law at LexisNexis.
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Hi, Tony.
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How are you?
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Hey, Ari.
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I'm great.
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Thank you so much for
having me on the podcast.
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It's my privilege.
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I'm looking forward to this conversation.
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So tell us about your background
and your role at LexisNexis.
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I grew up in Colorado but now I'm
a New Yorker, and started my career
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in management consulting and then
in internal strategy roles before
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coming to Lexis about six years ago.
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I started in our corporate strategy
group and then moved into our news
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and business division for a time where
I led strategy and customer success.
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And then I ended up on the legal side
of the house, which is actually the
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core business of LexisNexis legal
professional, and it's great to be here.
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I lead our large law segment.
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We define large law as any firm
with 50 attorneys or more in the US.
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I oversee all of go-to-market, so that's
sales, marketing, customer success and
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also inform our product strategy as well.
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How are law firms adapting
their AI strategy from
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experimentation to expectation?
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It's been an incredibly
fast transformation.
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Just a year ago, there was a lot
of talk of, should I be using
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AI or which AI should I use?
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At this point, all of the firms have
adopted one or more tools, so it's
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really about which ones am I going
to adopt more for which use cases?
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Where should I use different AI
tools in different parts of the firm?
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And also which firms are giving me the
most value in terms of both product
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but also the service that I'm receiving
from them, and how am I integrating my
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content, my know-how into the workflows
of AI, and what does that look like for
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my attorneys as they deliver client work?
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With access to different models no
longer being a factor, what is the
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differentiator in using these tools?
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The real differentiation
comes in a couple things.
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The first is the context, the second
is the harness, and the third is how
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you operationalize AI within your firm.
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So when we talk about the context,
that's really what goes into
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the model or the AI system.
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Obviously it's the firm's documents, but
it also could be proprietary content that
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a legal tech provider has, such as case
law or secondary content or even legal
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news as well as the firm's knowledge
and their ways of working and how they
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actually build that within the AI system.
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The second is what I call the harness.
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So this is the engineering that the
model has around it that can help it
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orchestrate, that grounds the answers,
that optimizes the actual output.
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It's in the way lawyers like to talk,
it's in the formats and even the font
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and the way it's set on the page.
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Those little things matter, and this
is where a lot of legal tech vendors
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play a role in terms of really honing
and tuning the model and also selecting
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the models for the best answer and
the best output for the attorney.
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And then the third part is the
operationalization, and that's really
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about how good the firm is in terms
of enabling their attorneys to use AI,
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making it easy to upload documents,
and this is where firms with strong
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KM groups, strong CIOs really thrive.
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As these AI capabilities begin to
converge why do authoritative legal
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content trust and integration into
those existing workflows matter?
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The model is just one layer of the cake.
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You need a full end product,
you need multiple layers
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and the filling in between.
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We believe, at least at LexisNexis,
that content and trust is absolutely
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for attorneys, and that's because
legal work has really asymmetric risk.
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You can't just be a little bit correct.
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Eighty/20 doesn't work like that in legal.
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When I was a management consultant,
we always talked about 80/20,
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and that's not the case in legal.
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There are sanctions.
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There's a lot of high risk
bet-the-farm-type transactions that
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are happening, so lawyers need to have
confidence in the answer being correct,
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that they have authority underneath it.
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And then also that trust
layers on into actual adoption.
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So if an attorney doesn't trust the output
that it's consistently getting from a
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tool, then the attorney's not gonna use
it, and so that is a major gap as well.
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And then lastly, the more you can
integrate the AI into the actual workflow
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of how the attorney may have done it
before or the best practice, and so that
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doesn't feel like it's moving away from
that process, but really integrating with
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the process that was being done or the
process that's best practice, that's where
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you see AI really be a multiplier versus
feeling like it's something completely
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different that needs to be relearned.
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Given the importance of collaboration,
what does a genuine strategic
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technology partnership look like today?
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It's been a change.
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It's no longer this vendor-customer
relationship where you're coming in with a
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sales team and just selling a subscription
and then seeing them again in three years.
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It's changed quite a bit.
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And admittedly, my business has
had to change how we operate and
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how we staff engagements, and so
it's really shared problem-solving.
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It's when the firm comes forward
with a real problem that they're
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trying to solve, maybe the partner
doesn't have an off-the-shelf solution
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for that, and so you need to come
together, you need to work that out.
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That might look like a different
account team than a salesperson
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and a customer success person.
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It might include those people, but
then more likely it will also include
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somebody that has a legal background.
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We call those people legal engineers.
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It might also include software
engineers that are front-end developers.
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That is a much more holistic account
team that's serving the client than
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you would have seen in the past.
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That's important because that helps
create the trust between the two.
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Both- sides are bringing
to bear lots of resources.
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This takes a lot of time and energy
from the firm as well, that you
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might be pulling away people who
are billable onto these projects
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to really invest in the future.
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And so that's a real strategic
partnership when both sides are
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putting skin in the game, and then
there's a feedback loop between the two
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where each side is learning from the
process and each side is benefiting.
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That's what I would say a true
partnership looks like these days.
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How do you define the role of a legal
engineer, and why is that becoming
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so important inside law firms today?
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It's the intersection of somebody with
strong legal domain expertise with
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more of a technical product-oriented
mindset helping to translate what is
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the attorney doing from a pure workflow
perspective, and then how do I translate
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that into a technical process that may
or may not involve AI-enabled steps.
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It's usually somebody with a JD
background that really can empathize
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with what the attorney is doing
with also that passion for AI, that
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understanding of technology and how
to break that into steps for the firm.
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And then the third part is actually
how do I enable that, knowing a lot
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of these people come from large law
firms, so they understand some of the
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barriers of adoption and how to convince
skeptical attorneys that this solution
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could really enhance their work.
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Where can legal engineers
create the most value?
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These are really high volume,
high friction workflows.
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Take an example of having to analyze
hundreds, maybe even thousands
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of contracts to compare them all.
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What would've taken hours and
maybe a human being would miss in a
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tabular view using AI could be done
in a matter of, less than an hour.
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So that's a great example where
an off-the-shelf AI capability, we
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call these skills at LexisNexis,
these skills can really just
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accelerate a process really quickly.
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I think the second area would be
where you're configuring something
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that's a little bit generic.
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Maybe it's a generic skill, but you're
configuring that specifically for the
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firm or for the person so that it fits
their way of doing things, it fits their
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voice, it fits their precedent documents.
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That would be a second area.
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And I think the third thing is
really back to general customer
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success of scaling what works.
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So finding what are the seeds that are
working, cultivating those seeds so they
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grow into workflows that are repeatable,
that can be scaled across the firm.
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That's really where the legal engineer
can see value because they're coming at
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it from a third party perspective and
able to see across different practice
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areas beyond what maybe an individual
attorney or a KM team might see.
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What are the most important questions a
law firm should ask a legal tech partner?
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Definitely what is your operating
model in terms of how are you gonna
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support us going into this initiative,
how are you gonna support us after?
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Understanding the full life cycle
of what this engagement could
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look like is immensely important.
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Having mutual understanding of metrics
and what does success look like at
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the end of this project or during
the project, what metrics will tell
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us that we're being successful.
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And then I think also understanding
what obviously are the technology
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components and products and
people to bear for the project.
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You wanna have trust that this partner has
access to the latest models, has access to
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the right content, has access to the right
people and experts to get the job done.
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What are the most important metrics that
a team should evaluate when determining
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whether they're having success with AI?
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I like to stay away from time
saved because it's really
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an input versus an output.
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Firms are still billing by the
hour, so it is something that is
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important to be aware of, but faster
is not always better in legal.
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You always want correct, you
want client satisfaction.
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I like to point to things
that are more around the end
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product, so client satisfaction.
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A little bit harder to measure,
but just the responsiveness, the
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ability to get back to customers.
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And also the depth of the relationships
you're building with them.
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These are all a little bit soft but if
I had to put more concrete metrics, I
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would look at the ability to take time
out, and is that fewer hours written off?
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Is it, higher value work that we're doing?
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Are we getting more
customers into the door?
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Are they more satisfied?
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Are we handling more
matters than we did before?
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Where do you expect the biggest
gap to emerge between AI leaders
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and firms that fall behind?
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It's definitely not gonna be around,
what technology they're using.
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These models are now available to
anybody willing to pay, so it's really
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around their organizational capability.
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Are they built to take on change?
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Are they built to really drive
adoption and think about their
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old ways of doing things, their
old workflows and redesign them?
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Firms that are reticent to take that
change on will fall behind in the gap.
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A second area would be their
ability to integrate their
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firm's knowledge and processes.
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If every firm is using the same technology
but not actually putting their unique
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thumbprint on their firm way of doing
things or their firm knowledge base, then
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you lose the differentiation completely.
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The firms that are able to integrate that
with AI will create a gap because that
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institutional knowledge will still show
up and create value for the firm even
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though technology has become an equalizer.
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I think the third thing would
be, and this probably is a couple
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years down the line, the firms that
actually change their business model.
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So maybe they change how
they staff their projects.
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Maybe they're able to hire more
rainmakers because the actual legal
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work being done is more efficient.
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Maybe they're able to price differently.
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Maybe they do value-based pricing or
non-billable not hour billable pricing.
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Perhaps they're faster
to respond to things.
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They're able to take on more of
a corporate legal department's
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full breadth of services.
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These are the things that will
really create a gap between
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firms that are adopting AI versus
those that are a lot slower.
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How do you see strong technology
partnerships empowering
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law firms in the future?
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The partnerships that are strongest
will show that they can continuously
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drive value for the firm and even drive
value for the legal tech providers.
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So the legal tech provider's learning as
well, may be able to scale to other firms.
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So they're continuously reinventing
the workflows rather than just
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implementing and then never looking
at it again continuously taking that
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feedback and improving together.
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And both sides are sharing in that
mutually beneficial learning where
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the technology partner gets more and
can really scale what they're doing
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for others and can really improve how
they're operating for their customer.
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But then also the firms are able
to gain a lot from the partner
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because the partner knows them.
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They're not having to reteach a different
partner every time in terms of how their
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firm operates and how to scale technology.
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This is Ari Kaplan speaking with
Tony Muljadi, the General Manager
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of Large Law at LexisNexis.
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Tony, thanks so very much.
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Thank you.
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I really appreciate it.
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Looking forward to connecting
when we see each other again.
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Thank you for listening to the
Reinventing Professionals podcast.
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Visit reinventingprofessionals.com or
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