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How long has Intralinks been developing AI solutions?
In 2018, we began investing in developing of our own proprietary AI infrastructure and solutions.
Do you use ChatGPT? Do you partner with an external party?
No. Having invested in developing organic AI solutions for over five years, we do not rely on or ship data to third-party providers.
How do you manage data security and privacy?
We curate several of our own models, and customer data never leaves our environment. Our strict, multi-layer customer data security practices are continually enforced.
What large language models (LLMs) do you use?
We manage several of our own LLMs, ensuring that customer data never leaves the virtual data room (VDR). Additionally, we rigorously enforce our strict security practices regarding data tenancy.
How many models do you use? How do you select models?
We deploy a constellation of models. Each model is selected for a specific purpose on our platform. The selection process starts with a benchmark study for proof of efficacy in our lab environment before proceeding to further, more in-depth training.
Do you use my data to train, re-train or improve your models?
No, we never use any customer data to train, re-train or improve our models. Your data is always safe and protected within our ecosystem.
Do other customers see my information?
We have implemented safeguards to ensure that models only respond to content a customer has access to. This eliminates the possibility of another customer viewing your information.
How do you train your models?
We use various generally accepted methods to enhance the models we select, including techniques like few-shot learning and reinforcement learning.
Do the models get better over time?
Yes. Thanks to a variety of methods we deploy along with ongoing technological advancements, the models are designed to continually improve over time.
What is the accuracy of the models?
Through a rigorous selection process and validation within our lab environments, we routinely achieve accuracy rates exceeding over 95 percent. However, due to the inherently non-deterministic nature of artificial intelligence compared to traditional software, the learning aspect of our models ensures they are continuously evolving for the better.
How will AI change the M&A job market?
Watch Intralinks’ Ronjohn Dadd discuss how AI is transforming M&A and the dealmaking job landscape with
ACG's GrowthTV.
View Transcript
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Welcome back to Growth TV. I'm Carolyn
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Vallejo.
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Joining me here is Ron John Dad, principal
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product manager at SSNC Intralinks,
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to explore how AI is changing the dealmaking
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space, including job roles within M&A.
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Ronan, welcome to Growth CB.
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Thanks for having me.
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So first, I want to talk about some of the challenges
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in the dealmaking process that firms are hoping
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AI can really help solve.
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Yeah, I mean there are
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endless problems that happen in
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in M&A deal execution process
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that you could
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look to solve and and a lot of technologies
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out there are solving today, you
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know, our
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organization, we are positioned to
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talk to a lot of clients that are in,
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you know, focus on the diligence part of
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deal making.
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And the diligence part of deal making is what ends
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up taking a lot of the time
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throughout these processes that take years,
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months, however long.
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Over the past you know few years we
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have seen with COVID and
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a number of, you know, other just market
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issues going on that deals are taking longer
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they stall and
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time kills all deals
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so a lot of the.
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M&A professionals that we've been talking to have really
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been focused on just driving efficiency
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in the core
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due diligence tasks and jobs that
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their bankers or you know the
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their teams are working on on a regular
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basis so simple things of
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spending, you know, less time
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making changes to documents
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preparing them to be.
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You know, viewed by potential buyers
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and, you know,
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more time spent actually with our clients
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understanding them and then, you know, moving
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forward in the deal process.
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I think their main focus is
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there's a lot that can be done within with
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an AI. I always say you can probably
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think of and do anything with
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AI,
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but right now it's like how do I just
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get my job done faster with less
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resources.
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Right, that makes sense. And as you just emphasized,
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there is so much potential in AI, but actually
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putting it into practice is kind of a different matter.
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Can you get us up to speed on what some of the early
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adopters of AI in the dealmaking community
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have done in terms of really using the
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technology to its full advantage right now?
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Yeah, I think everyone you
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talk to, they
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pretty much everyone talked to it. They've put together an
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AI committee or something
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to start looking into it and where I've
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seen people be early adopters
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and and start to make a difference early
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on
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is
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not just, you know, putting together these committees,
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go look at a bunch of different products, what
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else is out there, how are other people utilizing
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it, but actually doing.
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In internal reflection of
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their own organizations and saying
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all right based on what we do, whatever
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our niche is, you know what
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we're providing to our clients
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where are the different jobs and tasks
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that that our teams are doing
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and even if they're easy ones that.
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Don't need fixing, getting all those
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on the paper and then identifying OK
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not only where there are
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there's a lot of time lost but
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how frequently are those tasks
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that are losing time happening
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then not only you know how many times
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that it's happening but
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how painful it is,
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how
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costly it is if a mistake is made.
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And then I think the final point, which
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I think is really important for people to look
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at is if I were to fix this,
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how much of a competitive differentiation
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does that give my organization in firm
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because even if you do fix it
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and you know it helps cut down
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on time or processes if it's not helping
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deliver to your ROI,
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get more customers,
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make customers, you know, happier
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or position, you know, my
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team as a knowledge expert that we'd have clients
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come to us rather than others.
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Then you know you're just solving some of the
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bare minimum pieces, so.
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It's actually not like the people
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that go out and can
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find every single AI tool out
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there and figure out
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all the things that they can do, but more so, let's
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internally reflect
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where the biggest areas they're gonna produce the
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most return if we fix them and then
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you can go and start that process
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outside looking at what else is is out
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there. So
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internal reflection I think is one of
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the most important pieces so
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that when you do have conversations and.
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When I have conversations with people, they, they
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fully know, hey, these are the this is the problem
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we're trying to solve. This is what we're looking to get out of it.
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And then you have a much more pointed focus
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as to the solutions and areas
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that you go to look at.
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OK, so dealmakers want to solve problems. They
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want to make their jobs more efficient, but of
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course, one of the biggest fears that we're hearing,
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uh, kind of in every industry is that AI
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is going to come after their job.
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Um, when it comes to deal makers, what can
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we expect AI to have an
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impact on in terms of the labor market?
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Yeah, I think um I'm
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a little bit more optimistic in in this
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sense, you know,
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yes, the, I even said it
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before that.
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You want to do more with less
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resources. That doesn't always mean people though,
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and you know, a lot of the things that people
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are looking to solve
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are not necessarily,
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you know, the
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individuals are, you know, constantly
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spending time on minuscule
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manual tasks, and we would rather not have
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people do that.
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But it's more so that typically
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in this industry, the people they hire are
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very smart individuals. They went to great
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schools or highly intelligent
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and their skills and benefits
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are
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used or more useful in the,
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you know, more high intelligent, high profile
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tasks that that have to be done, you know,
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creating financial models. Models the
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you know actual analysis of companies
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helping understand strategy set direction
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for the companies that they're working with. So
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in my view, you know,
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maybe we will have to have
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less people, you know,
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working on a single pitch deck
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to remove comments all night, but that
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gives them actually the ability to
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really
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jump start their career earlier on
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focus on high value tasks, high profile
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tasks and become.
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Better
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advisors, better
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vendors, better lawyers
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earlier on with their clients because they're spending more
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time with them rather than just sitting by
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themselves in a queue
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knocking things out of a spreadsheet.
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Um, and more time really doing what
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they've been hired for in their intellect, their
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strategy, their decision making, so
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I think it we'll see it changes
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absolutely where
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you're the jobs that people
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come into are less a manual
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process and grunt work that takes all night
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but allows them to be much more
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focused on how they can help their
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clients and be strategic earlier on,
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not just waiting until you get to that.
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You know, senior partner manager
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level, right, yeah, so you're
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calling some fears here, which is great to hear. Um,
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thank you so much for joining Growth TV. AI is
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such a timely topic right now in the dealmaking community,
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so we really appreciate it. Absolutely, happy
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to be here.
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