September 15, 2025 • 35 mins
In this special Reality Bytes, the team sits down with Matt Rose, Product Marketing Manager at Nexthink, to talk about the just-announced AI Drive. Matt breaks down how AI Drive helps organizations finally make sense of their scattered AI landscape—bringing visibility, usage insights, guidance, and measurable impact into one place inside the Nexthink Infinity platform. He also shares early customer feedback, the future roadmap, and why AI adoption has become a critical competitive differentiator.
If you’ve wondered how to move beyond AI experimentation to true business value, this is an episode you need to hear.
Learn more about AI Drive here
Book your tickets for Nexthink Experience (Boston or London) here: https://nexthink.com/experience
Get the latest edition of the Gartner Magic Quadrant here (https://nexthink.com/gartner-magic-quadrant-dex) Â
If you’ve wondered how to move beyond AI experimentation to true business value, this is an episode you need to hear.
Learn more about AI Drive here
Book your tickets for Nexthink Experience (Boston or London) here: https://nexthink.com/experience
Get the latest edition of the Gartner Magic Quadrant here (https://nexthink.com/gartner-magic-quadrant-dex) Â
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Transcript
Episode Transcript
Available transcripts are automatically generated. Complete accuracy is not guaranteed.
Speaker 1 (00:00):
Hello, change makers. Tom McGrath here just wanted to take
a moment of your time before we get on with
today's fantastic show to give a big, resounding plug two
the world's biggest digital employee Experience event, which is of
course next Thing's experience, or should I say events, since
there are two. There is one this month starting this
(00:21):
month for thirtieth of September in London at the Intercontinental
that's on the thirtieth of September and the first of October.
And there is one for our for all of our
friends in North America at the Omni Boston Hotel at
the Seaport in Boston that's on the fourteenth and fifteenth
of October. They're both two day events. They both host
(00:43):
appearances from many of full world's biggest brands and best
digital workplaces that are incredible networking and learning and training
opportunities throughout the two locations. You'll even be joined by
the likes of Gartner and in Boston, nildegrat Tyson and
last but not least, the Deck Show itself. Tim and
I and many of our show colleagues will be at
(01:07):
the events. We'll be doing a live presentation, a live
show at London and at Boston, so do come and
say hello if you're there, and we look forward to
it very very very much. So thank you so much
and on with your show.
Speaker 2 (01:21):
Bye.
Speaker 3 (01:26):
Welcome it, change Makers to the Deck Show with Tim
Flower and Tom McGrath. Let's get into it.
Speaker 1 (01:35):
Hello, change Makers, Welcome back to the Deck Show. Show
within a show within a show. You know what it is,
it's those episodes of reality bites. We have a panel
and myself get to interview another fascinating next thinker and
we've got to believe a first time fascinating next thinker
on the show with us today. But I have to
just add as well as I should mention of our
(01:57):
favorite Stena and Tim. Hi, guys, But I should just
add that one of the joys of reality bias is
not only that we get to welcome so many fascinating
next thing because there are so many to talk to,
but what we work for an organization, but it is
so relentlessly creative and innovative, and it gives us so
much to talk to them about. And today is absolutely
(02:20):
no exception. It is the opposite of an exception. Is
a case in point, which is because we are announcing
an amazing, fascinating new next thing product today. It's called
AI drive. Might not be today this week, Madd'll tell
us and Matt Matt Rose is the product marketing manager
here at Next Think and is leading the charge around
(02:41):
AI drive, so let's welcome him to the show. First
of all, welcome along, Matt.
Speaker 2 (02:46):
Tom, thanks very much, great to be here.
Speaker 1 (02:49):
And how wrong am I about the dates? What is
the official date? Remind us?
Speaker 2 (02:53):
Yeah, of course, so we've actually got customers utilizing AI
drive right now. On September fifteenth will be the biggernouncement,
and then a couple of weeks after that everybody will
be able to jump in, give it a try and
start making some great progress with their with their AI strategy.
Speaker 1 (03:12):
What wonderful timing, ladies and gentlemen. But look, welcome Matt,
and first of all, let's tell us a little bit
about yourself to begin with, sir.
Speaker 2 (03:20):
Yeah, of course, So Matt Rose, based out of Boston.
I've been with Next Think for closing in on three
years now in the product marketing space. Have a myriad
of different responsibilities, but I think a few that as
listeners and potentially Next Think power users that you may
(03:40):
have leveraged in the past, would be most recently Next
Think assist in the continued enhancements that we're making there,
and really a lot of the other I have my
hand in a lot of the other AI capabilities that
that Next Think is working to to continue to evolve
and unlock for everybody.
Speaker 1 (03:59):
Fantastic. And I have to say, of all the innovation
that's come out of Next Thing cover of the last
year or so, maybe AI drive is the thing I'm
most excited about. And before we get into why that
is and what it does, set the stage for us, Matt,
how do you see the current corporate landscape when it
comes to shall we say, AI driven digital transformation over
(04:21):
the coming year or three. What are the big forces
of play right now as you see them?
Speaker 2 (04:26):
Yeah, so I think, you know, I think a lot
of people say, oh, we're at the beginning stages, but
I would say we're past the beginning. We're more kind
of at the early stages. Right. It's no secret that
there's billions of dollars of investment that are taking place
each year in terms of AI implementation at every single organization.
(04:47):
So I think the realization and understanding of heye AI
is extremely necessary and we need to make investments there
and we need to get everybody leveraging and utilizing it.
Has pushed us past the kind of initial beginning stage
of how do we justify this and how do we
ensure that you know, this is something that we want
to put our money and dollars behind, And now we're
(05:09):
into kind of the early stages, right, how are we
actually kind of putting processes in place to getting AI
up and running and running efficiently for every single employee
throughout the organization. So I would say we're we're still
kind of early days, but it's moving quickly. To avoid
the cliche, if you know, everything's moving faster than ever before,
(05:31):
but it really is. I mean, I think there's so
much adoption that's continuing to happen, and now that there's
some checkboxes that have been kind of put in place
with many different organizations, we're making some great progress. Right
first and foremost, I think I think about AI governance.
It's always the hot button topic. I'm not going to
spend a lot of time talking about it here today,
(05:53):
but it's a box that's necessary and needs to be checked.
Many organizations have already put in place, you know, these
different committees to ensure that things are being run through
the right protocols and that everything is going to be
safe and secure for their organization, that data isn't going
to leak, and people are utilizing AI in the wrong way,
so on and so forth. And now it's really about
(06:13):
how do we unlock value from the sheer amount of
tools that are out there? Right? How do we find
what's right for each single task at hand and then
integrate it throughout our entire kind of digital ecosystem.
Speaker 1 (06:27):
And when you think about the distinction between winners and
losers of the coming years, what do you think separates
the two categories?
Speaker 2 (06:37):
To me, I think it's really about a balance of
structure and flexibility, right. I don't think you can swing
too far in either direction. I think is there a
set of tools that employees can choose from that they
can utilize for the tasks that they have at hand, right,
not pigeonholing people into you must utilize this thing every
(06:57):
single time for this particular way of working. Now, certainly
are there kind of going to be some mandates and
parameters put around that. Yes, And there's going to be
certain industries that have more rules and regulations than others.
But the hope, I think is that you don't have
to stray too far any of the direction. That there's
(07:18):
going to be many, many, many AI tools that are
deployed throughout every single organization. It's just finding which ones
are right for which employee, and then how do we
drive kind of adoption of them. I think about this
like even just a few years ago, with what happened
in the communication collaboration space, right think about Zoom and
how that took off. That Zoom wasn't anywhere and then
(07:40):
all of a sudden everybody utilized it in their personal life,
and then all of a sudden it took off inside
of every single organization. Is a great tool that needs
to be invested in and something that people feel comfortable
with utilizing. They know how to use it, and they
know how to get the value from it. And I
think that can be kind of similar here in terms
of you've got AI tools that people are utilizing in
(08:04):
their personal life, how do we put the right structure
and parameters around them so that people feel comfortable and
utilizing AI in the workplace as well, and making sure
that you know they're able to get the value out
of that they need in order to get their job
done faster than ever before.
Speaker 4 (08:21):
Hey, Matt, well, come on the show. It's always good
to see you.
Speaker 2 (08:24):
Great to be here. Great to see you too too.
Speaker 4 (08:26):
So let's get into some details. I think it's pretty
apparent that I talked to a ton of people around
the world, our customers, prospective customers, everybody that I talked
to about AI is still trying to get a handle
on it. Right, you talk about the need for some
governance and some controls, but I think they've had, in
(08:46):
my experience, they've had a tough time articulating what the
problem really is. Right. They'll talk about risk, they'll talk
about security. They're not quite sure what a solution looks
like us. What exactly is AI drive. I look at
it as AI for AI, But what problem does it solve?
(09:08):
And what's the vision and the value problem?
Speaker 2 (09:11):
Yeah, so I think I'll start with the latter and
kind of vision. I think what we see as an
organization and our feel is really strongly about it is
almost like flipping the script. I think there's the whole
notion out in the market of you know, how do
we ensure that we are making our business the most
(09:32):
you know, cost effective or doing more with less and
things along those lines by by leveraging artificial intelligence. But
I think really what we are finding, what we are
trying to kind of push and showcase, is that you
can make your workforce so much more productive by having
them leverage artificial intelligence. And that's really how you're going
to be able to get ahead of the competition, how
(09:53):
you're going to ensure you're not going to be left
behind in you know, the industry that you work. So
how do we make sure that you know, AI is
being pushed to the forefront and that we're driving we
flip the script to really working towards productivity. I think
what we know right is that today over seventy five
(10:13):
percent of people are actually already utilizing artificial intelligence, but
it's highly distributed across many different tools. It's potentially the
things that they're bringing into it to bring your own AI.
So what really AI drive does is it can it
consolidates you know, all of this different fragmented AI activity
into what we're calling a quantifiable business impact. Right, We're
(10:35):
going to be able to centralize AI visibility of the
different tools that are out there. How they're being utilized,
the how do we guide people to actually utilize it
more effectively and adopt it better? And then how do
we measure all of these things into this kind of
like single actionable vantage point inside the next thing infinity platform,
(10:55):
so that people can really drive impact throughout end productivity
throughout their organization.
Speaker 4 (11:02):
I think that's an important part to highlight, which is
that AI can bring tremendous benefits, but it's not an
easy button and you can't just roll out an AI
solution to your employees and say here, go use this
and automatically they're going to be more productive. I think
a lot of reports right now are saying people are
less productive because they've got all this new learning curve.
(11:24):
Things are changing so quickly. But get into a little
bit more detail, break down some of the key capabilities
and possibilities for Yeah.
Speaker 2 (11:33):
So I had kind of just alluded to what we're
calling almost like four different pillars of when AI drive
represents right, And the first one is along the lines
of visibility. How do we first and foremost get an
understanding of what are the tools that are actually being
utilized in every single organization's environment. Are they the ones
that are corporate approved. Are they the ones that are
(11:57):
most effective in terms of of making sure that people
have the right tool for the right kind of thing.
Visibility around the actual departments of people that are utilizing them.
Are there certain groups that are utilizing AI more than
others and which and if so, which tools are they?
So I think visibility is kind of a key core
(12:20):
starting place to make sure that you have kind of
a bird's eye view of what your digital landscape looks like,
similar to what we do on the deck side kind
of today. Right. The second one is around usage. The
visibility is great, but if you're only getting you know,
data around, hey, here are the tools that are actually
being deployed throughout your organization, it doesn't take you as
(12:43):
far as you need to be in order to like
get to where we were just saying with the driving
of the productivity element. So how do we look at usage?
How do we say that there are you know, x
amount of people in your organization that are really AI champions,
They're utilizing AI a lot, they're finding value from it.
And how do we drive almost like the ball down
(13:04):
the hill or some forward momentum right and ensure that
you're you're you're utilizing the champions in the organization to
push forward the AI adoption and and highlight the value
that they're getting from AI through to all the you know,
other people in the organizations that may be you know,
just gabbling in AI at this point in time. And similarly,
(13:28):
on the usage side of the house, how do we
look at the actual kind of prompts and things like
that that are being pushed into place so that we
can say, okay, you know what, here are the most
common ways that people are generating value from AI, whether
it's something as basic as you know, crafting an email
to something more in depth like creating code. So I
(13:51):
think the usage element is kind of that second core
key pillar that we look at. Following that at a
guidance is number three. How do we ensure that we're
creating action points to drive additional pieces of adoption throughout
looking at not only just hard metrics, but also getting
(14:13):
insight into employee sentiment.
Speaker 4 (14:15):
Right.
Speaker 2 (14:15):
That's and sentiment has always been a core part of
the next Thing platform. It's something that is key in
terms of pushing everybody forward in terms of driving adoption.
So what happens if you know people are struggling with
you know, certain rules or policies or not having access
and you may not have ever seen that before, but
all of a sudden, if you have contextual sentiment pieces
(14:37):
that are coming into play, now, all of a sudden,
you're able to put in place the programs, the trainings,
the communications that are necessary in order to drive adoption
through of AI throughout the organization and with the right
tools that maybe people are asking for because you have
their actual sentiment that they feel around it. And then finally,
(14:58):
is the measurement kind of piece, right, what are the
key metrics that organizations can leverage to be able to
do Provide a roll up to the executive leadership team
and make sure that they're saying, hey, here's you know,
the amount of active users and the trend of active
usage for AI and the different tools across our organization.
(15:19):
We're making great progress here. We're seeing, you know, an
uptick in the actual number amount of engage time with
artificial intelligence across each user. And now all of a sudden,
we can find out, you know, what is the value
or the time saved by utilizing AI, and gain context
by really benchmarking that against other organizations which I think
(15:39):
is a key piece because without that kind of benchmarking
and context, you're just measuring against yourself, and with something
so new in the industry, there's really no kind of
internal comparison that you can have, So those are kind
of key pieces.
Speaker 4 (15:56):
There's a lot there. I think that it high lights,
and we talked about it a little bit. The vision
that next think has our ability to execute being being
developed on a foundation of an AI platform. It allows
us to move quickly in doing these things. What's being used,
who's using it, how is it being used, where is
(16:19):
it successful versus where is it struggling. How do we
share those best practices with the rest of our enterprise
and help people come up to speed. I think are
all things that in our vision and our ability to
execute that others aren't able to do. Using AI inside
the platform to help manage AI outside the platform is
(16:41):
something that no one else has, and I think lots
of people share our excitement on this AI drive coming
out to help really manage this transformational change in it
to a different level. Do you see it as a
natural extension of what we've been doing all along in
our core dex principles that are now just reaching into
(17:03):
some new apps and new technologies, or is it the
flip of that where it's fun fundamentally new approach tailored
to the wave of AI.
Speaker 2 (17:13):
I think it's actually closer to the former. I think
what we want to make sure that we're doing is
keeping structure and process the same. Right, we've had customers
with us for so long they've been able to see
value out of and great value out of the next
in infinity platform. We don't need to reinvent the wheel
(17:33):
on that front, but we do need to ensure that
we're continuing to move forward to innovate to be to
provide the right resources to be the most beneficial kind
of DEX platform for every single customer you know out there.
And really, I think that's an extension of the core
kind of DEX principles that you know you've been seeing.
(17:53):
I think you've probably if you're listening, you've probably heard
us talk about ce diagnosed and fix so many times.
And I think there's a natural kind of extension of
how that comes into play even here, right we talked
about visibility, see diagnose, usage and guidance and making sure
and fix kind of all coming into play there where
(18:15):
it's now you know what's going on in the environment.
You're able to understand what are the great things that
are happening, and how can I kind of extrabulate that
but also fix some of the kind of issues that
people may be having from an adoption standpoint or from
a measurability standpoint. So and ultimately it all stems back
to our greater goal of creating a better digital employee experience.
(18:38):
If you're able to utilize the latest technology because organizations
feel like they have the visibility and foresight and control
over it, then now you're providing not only a better
digital employee experience, but a more productive workforce as well.
So certainly extension and I think there's kind of continued
(18:59):
ways that decks and AI will continue to come together
and we'll push push the industry forward. Here, Hi'm Matt Dina.
Speaker 5 (19:07):
Here. Have you had early feedback from customers or prospects
on AI drive and what would be the thing that
resonates the most with them?
Speaker 2 (19:18):
Yeah, so we have And hello Dina, how are you
the thing that we hear most as of right now
from a lot of the customers that have been leveraging
AI drive for I guess a couple of months now
in preview mode has been really all about adoption, adoption, adoption, right.
(19:39):
I think I started off the top of the call
by saying, everybody's investing in artificial intelligence. That's the case,
the numbers don't lie, and we've heard that from all
the different customers that have been utilizing AI drive to date.
But they're really kind of stuck at a point of
how do I ensure that I'm driving adoption of artificial
intelligence in the right way? I think Tim you might
(19:59):
have alluded to it that you know, AI is only
as good as the proficiency of the workforce utilizing it.
So how do we ensure that we're training people up
the right way? How do we ensure people aren't going
around in circles, which is pretty easy to do with
AI if you're continuing prompting and prompting and prompting, waiting
to get to the answer that you are hoping for.
So what are the best practices for kind of changing
(20:22):
things together and moving that forward? So adoption is probably
number one, and then measurement is number two, right, especially
with some of the customers that we work with that
may have been a little that may be a little
bit more mature in nature in terms of their AI strategy.
You know, maybe they've been able to see to a
certain extent what tools have been out there. Maybe they've
seen some success with driving the adoption of some of
(20:45):
the corporate owned tools or corporate mandated tools that they're
they're uh, put a bit put in place inside their organization,
but they don't know how to continue to make sure
that they're unlocking the insight into how much did that
actually save me? How much? Why has this been so important?
(21:06):
And why should I articulate this as a great outcome
that I can then push to the other people throughout
the organization that may not have adopted that now have
a real sense of Look at my colleagues who are
seeing all this value and time saved and productivity and
things along those lines.
Speaker 5 (21:26):
Fantastic. It feels like a cornerstone product with a big,
big future. What can you share about the roadmap in
general for AI drive over the next couple of years.
Speaker 2 (21:36):
Well, the one thing that I will say is there
will be continued investment here. I'm on the product marketing side,
so roadmaps a little bit out of my full jurisdiction.
But what I will say, is that we know that
we want to continue to invest in this product, that
there's going to be continued evolution of it that as
(21:58):
we hear more and more from customers about you know,
the AI value gap that you know Gardner has coined,
and how we can best represent the data to be
able to showcase how that can be unlocked the better.
And we're going to continue to leverage you know, a
lot of the different dex capabilities that we have and
infuse them in there to make sure that you know,
(22:20):
we're taking full advantage of the Infinity platform, you know
that's already out there because there are so many kind
of tie ins, right I alluded to some of the
engagement pieces before, but there's so much more than that,
especially as it relates to some of the digital adoption
pieces as well. So continued investment, continued breadth of scope
(22:41):
across the platform, and ultimately continued learnings for for our
customers as well.
Speaker 5 (22:49):
Great does AI drive itself? Leverage AI today and how
do you see that evolving in the future more less?
Speaker 2 (22:57):
Yeah, multiple different facets actually, So as of right now,
there's functionality in there that makes it extremely easy to
be able to As I mentioned, kind of ladder up
success in the status. Right, we're leveraging our own artificial
intelligence to scan across the next in coffinity platform and
(23:18):
gain learnings from what the data is saying. Right, how
do I quickly, if I'm managing the next Thing platform,
get a read from our official intelligence on you know,
here's the progress that was made week over week. Here
are some of the action items that we should take
to continue to drive more productivity and drive more kind
(23:40):
of active usage, and then summarize that and be able
to provide it up the ladder without even really having
to spend too much time kind of analyzing everything that's
going on inside the AI drive dashboard, because it's already
been there and correlated against, like I was mentioning before,
the benchmarks of other organizations out there, so that they
can gain some context. The other one that I think
(24:02):
is extremely important on the AI front is we had recently,
I guess it was a few months ago now launch
AI sentiment analysis as part of our kind of employee
engagement campaigns. And so now all of a sudden, this
becomes this key way of leveraging AI for you know,
AI purposes. If I send a survey out that is
(24:25):
tailored to each individual AI application and get you know,
thousands upon thousands of responses back. How do we leverage
AI to culminate all of those things, find trends, find categories,
and then make recommendations on ways to actually improve some
of the processes that are out there. If everybody's saying, hey,
(24:45):
you know what, I have been utilizing chat GPT, but
I'm willing to make the move over to Microsoft Copilot
if you know, we can do X, y and Z
with it, and that becomes something that has been said,
you know, ten times, one hundred times, two hundred times.
Now in your your large organization. Now you've got some
backing and some guidance as to how you can kind
(25:08):
of better make an approach to providing that shift in
the organization and driving additional AI adoption. So yeah, multipleffer,
multiple different levels of AI within AI drive today.
Speaker 5 (25:22):
Definitely that the insight that you would get back to
your point of thus you diagnose fix with the power
of AI drive gives you a lot of actionable information
that would really help with the decision making based off
of data. Not just that, but also the analysis that
you do from the engage campaigns alluding to that how
(25:45):
might the roadmap intersect with other nexting solutions like assist
or adult in the future.
Speaker 2 (25:50):
Yeah, so I think assist is already live and well
today right in terms of how these two kind of
pieces come together. If I'm utilized in the next Thing
platform and i have a question about the artificial intelligence
tools that are deployed throughout my organization, I'm going to
be able to ask Assist and it's going to be
(26:11):
able to provide answers for me based on the data
that we're already collecting. It's part of the big benefit
of AI drive being embedded inside of the Infinity platform
and coming standard kind of out of the box. Is
now all of a sudden, all of the different additional
pieces of data that are nicely collected, that are nicely
displayed and easy to read, are already kind of being surfaced,
(26:34):
and Assist is reading into all those things, and you're
going to be able to effectively ask additional questions on
top of what's already displayed on screen to get additional insights.
So Assist is out there, and the assist also has
engagement campaign creation capabilities as well, which is nice. So
while we're coming with pre configured AI engage campaigns for
(27:00):
or specific tools you know you could there's nothing stopping
for you from asking assists to create an additional one
and continue to get you know, quick value and be
able to see things progress forward. On the adopt side
of the house, this is another one that I'll just
lightly touch on now, but I think the correlation is
(27:22):
certainly there. Right, we talked about guidance as that third pillar,
and there are many many different things that you can
do with AI drive out of the box from a
guidance perspective, but the layering addition of adopt on there
takes that one step further. Right, think about custom guides
that you could put in top of AI tools through next,
(27:43):
think adopt and be able to effectively have you know,
these in real time, contextually relevant guided ways to not
only you know, push people to the right tools, but
also have them utilize those tools most effectively because we
have you know, the guys set up for every single
(28:04):
employee to be able to do so so and customize
for that particular tool to make sure that the user
experience is the most intuitive possible. So I think we
touched upon you know, breath. The next thing platform and
continued intersection of AI Drive, and that's no different for
what we're doing with Assistant Adopt and AI Drive as well.
Speaker 4 (28:28):
So, Matt, I think many others are like me with
the art of the possible spinning through their head, the
breadth of our platform and where this might apply itself.
Let's let's hone in on for our listeners, who in
an organization should be paying the closest attention to AI
(28:49):
drive right now? So a role or some specific priorities.
Where does it serve itself best? And what are the
risks if this kind of arena is ignored, and what's
the best way to learn more? Especially how much does
it cost?
Speaker 2 (29:08):
All right, well, you know what, let's start and reverse
because it's the question that everybody always asks, how much
does it move? And we shouldn't have kept everybody waiting
till the end. But AI drive is available for free
for everybody as part of the next Think Infinity platform.
So if you are utilizing next Think Infinity today, in
a few weeks time, you'll see AI drive roll out
(29:31):
to your particular instance, which is great because I think
it's a key, as I think we said, cornerstone of
you know, driving digital employee experience forward is the you know, visibility,
adoption and value that's garnered from artificial intelligence. So having
AI drive available to everybody will go a long way,
(29:52):
and there's no need to even have to further justify
additional expense in terms of you know, who should be
paying closest attention to this. I think it's it's threefold,
if you will. So one is it's no secret that
end user computing teams are the teams that are utilizing
(30:14):
Next Think Infinity the most as of right now, right
and I don't anticipate that on changing, but I think
there is a major tie in between what AI drive
can do and the value that end user computing teams
can see. And it can be as simple as, hey,
(30:36):
you know, you've just been responsible for deploying a whole
bunch of AI tools across the organization. Aren't you curious
about how they're being adopted, what the actual kind of
number of people are in terms of utilizing them, how
what are they utilizing them? And then ultimately are there
things that we may need to roll back? Right like
are there particular tools, I think tools that can be
(30:59):
you know, positioned as Hey, this was a pilot. But
the pilot, you know, didn't didn't surface the value that
we were looking for, So let's try something else. That's
the thing with AI. There's so many tools out there
that it's going to be a trial error run for
a lot of organizations in terms of what are the
most effective ones for their organizations. So how do you
(31:19):
reallocate and repurpose a lot of the different kind of
budgetary components that may be invested in one place and
repurpose them in another in order to ensure you're finding
overall efficiency. And I think a lot of that kind
of falls back into the hands of end user computing
teams having full kind of knowledge and scale over what
their environment entails. The other two I think in some
(31:40):
organizations AI centers of excellence, right, those are people who
are putting in place, here's what the rules of the
laws of the land are in terms of the AI
tools that we'd like to use. So having them have
the visibility and understanding of you know, what are our
people actually utilizing the tools that we're recommending, are they
(32:03):
utilizing them effectively? And how can we drive continued adoption
of them? Because they're the ones that are kind of
wanting to put them in place is key for them
to continue to provide learnings back to the organization. And
then finally it's all the way up the ladder, right.
It's no secret that every single organization has AI top
(32:23):
of mind on their kind of strategy planning sessions each
and every single quarter in year. So how do we
ensure that C suite has visibility over these kind of
key components as well and really be able to provide
that information all the way up to be able to say, Yep,
here's the impact that it's making and here's how we're
driving our organization forward, because we don't want to be
(32:45):
left behind by not utilizing AI to its fullest potential phenomenal.
Speaker 1 (32:51):
And I have to say that before we leave AI
drive behind and take our leave. I really loved what
you said Tim about using AI inside the platform to
help manage AI outside the platform. It's such a cool
way to put it, really succinctly articulate. It's not just
AI drive, but I think that the total next thing
strategy around AI adoption and transformation very very cool breakdown
(33:16):
as well, and Matt really really appreciate it. And look,
before you go, sometimes we have our guests on reality bites,
and I dust off this question usually because I'm genuinely
curious about it in the individual case, and there's somebody
who works with you, I'm genuinely curious to know your answer, Matt,
What do what do? What do you most like about
(33:37):
being a next thing or what's top of your list?
Speaker 2 (33:40):
Yeah? Two four. One, of course, is working with both
perspective and current clients on a regular basis. Understanding, you know,
what they've got going on, their environment, the challenges they're facing,
and how can we continue to help and propel them
forward is one, and then two is really long lines
(34:00):
of uh, making impact right and understanding of hey, here's
the things that you know we're hearing from our customers
and how do we ensure that we're taking that back
to you know, product and engineering teams and say, you know,
these are the things that we need to develop. And
I feel, I guess in the role that I currently have,
that I have an opportunity to be you know, voice
(34:22):
of the customer in terms of being able to relay
that back and ensure that we're building the things that
are going to be the most impactful for every single
one of our customers, like I said, to propel their
organization forward and get the most out of digital employee
experience platform like next Think.
Speaker 1 (34:39):
Well said Matt, and thank you so much about breakdown.
Of course, interested listeners can learn more about AI drive
by looking at the show notes. We'll have links to
all kinds of resources and places you can get a
bit more information inside and even perhaps make contact with
somebody to discuss it in your account. Thank you Matt
for joining us, for telling us about this amazing, amazing
(35:00):
new product.
Speaker 2 (35:00):
Man really appreciate it.
Speaker 3 (35:03):
To make sure that you never miss an episode, subscribe
to the show in Apple Podcasts, Spotify, or your favorite
podcast player, And if you're listening on Apple podcasts, make
sure to leave a rating of the show. Just tap
the number of stars you think the podcast deserves. If
you'd like to learn more about how next Think can
help me improve your digital employee experience, head over to
next think dot com. Thank you so much for listening.
(35:26):
Until next time,
Hello, change makers. Tom McGrath here just wanted to take
a moment of your time before we get on with
today's fantastic show to give a big, resounding plug two
the world's biggest digital employee Experience event, which is of
course next Thing's experience, or should I say events, since
there are two. There is one this month starting this
(00:21):
month for thirtieth of September in London at the Intercontinental
that's on the thirtieth of September and the first of October.
And there is one for our for all of our
friends in North America at the Omni Boston Hotel at
the Seaport in Boston that's on the fourteenth and fifteenth
of October. They're both two day events. They both host
(00:43):
appearances from many of full world's biggest brands and best
digital workplaces that are incredible networking and learning and training
opportunities throughout the two locations. You'll even be joined by
the likes of Gartner and in Boston, nildegrat Tyson and
last but not least, the Deck Show itself. Tim and
I and many of our show colleagues will be at
(01:07):
the events. We'll be doing a live presentation, a live
show at London and at Boston, so do come and
say hello if you're there, and we look forward to
it very very very much. So thank you so much
and on with your show.
Speaker 2 (01:21):
Bye.
Speaker 3 (01:26):
Welcome it, change Makers to the Deck Show with Tim
Flower and Tom McGrath. Let's get into it.
Speaker 1 (01:35):
Hello, change Makers, Welcome back to the Deck Show. Show
within a show within a show. You know what it is,
it's those episodes of reality bites. We have a panel
and myself get to interview another fascinating next thinker and
we've got to believe a first time fascinating next thinker
on the show with us today. But I have to
just add as well as I should mention of our
(01:57):
favorite Stena and Tim. Hi, guys, But I should just
add that one of the joys of reality bias is
not only that we get to welcome so many fascinating
next thing because there are so many to talk to,
but what we work for an organization, but it is
so relentlessly creative and innovative, and it gives us so
much to talk to them about. And today is absolutely
(02:20):
no exception. It is the opposite of an exception. Is
a case in point, which is because we are announcing
an amazing, fascinating new next thing product today. It's called
AI drive. Might not be today this week, Madd'll tell
us and Matt Matt Rose is the product marketing manager
here at Next Think and is leading the charge around
(02:41):
AI drive, so let's welcome him to the show. First
of all, welcome along, Matt.
Speaker 2 (02:46):
Tom, thanks very much, great to be here.
Speaker 1 (02:49):
And how wrong am I about the dates? What is
the official date? Remind us?
Speaker 2 (02:53):
Yeah, of course, so we've actually got customers utilizing AI
drive right now. On September fifteenth will be the biggernouncement,
and then a couple of weeks after that everybody will
be able to jump in, give it a try and
start making some great progress with their with their AI strategy.
Speaker 1 (03:12):
What wonderful timing, ladies and gentlemen. But look, welcome Matt,
and first of all, let's tell us a little bit
about yourself to begin with, sir.
Speaker 2 (03:20):
Yeah, of course, So Matt Rose, based out of Boston.
I've been with Next Think for closing in on three
years now in the product marketing space. Have a myriad
of different responsibilities, but I think a few that as
listeners and potentially Next Think power users that you may
(03:40):
have leveraged in the past, would be most recently Next
Think assist in the continued enhancements that we're making there,
and really a lot of the other I have my
hand in a lot of the other AI capabilities that
that Next Think is working to to continue to evolve
and unlock for everybody.
Speaker 1 (03:59):
Fantastic. And I have to say, of all the innovation
that's come out of Next Thing cover of the last
year or so, maybe AI drive is the thing I'm
most excited about. And before we get into why that
is and what it does, set the stage for us, Matt,
how do you see the current corporate landscape when it
comes to shall we say, AI driven digital transformation over
(04:21):
the coming year or three. What are the big forces
of play right now as you see them?
Speaker 2 (04:26):
Yeah, so I think, you know, I think a lot
of people say, oh, we're at the beginning stages, but
I would say we're past the beginning. We're more kind
of at the early stages. Right. It's no secret that
there's billions of dollars of investment that are taking place
each year in terms of AI implementation at every single organization.
(04:47):
So I think the realization and understanding of heye AI
is extremely necessary and we need to make investments there
and we need to get everybody leveraging and utilizing it.
Has pushed us past the kind of initial beginning stage
of how do we justify this and how do we
ensure that you know, this is something that we want
to put our money and dollars behind, And now we're
(05:09):
into kind of the early stages, right, how are we
actually kind of putting processes in place to getting AI
up and running and running efficiently for every single employee
throughout the organization. So I would say we're we're still
kind of early days, but it's moving quickly. To avoid
the cliche, if you know, everything's moving faster than ever before,
(05:31):
but it really is. I mean, I think there's so
much adoption that's continuing to happen, and now that there's
some checkboxes that have been kind of put in place
with many different organizations, we're making some great progress. Right
first and foremost, I think I think about AI governance.
It's always the hot button topic. I'm not going to
spend a lot of time talking about it here today,
(05:53):
but it's a box that's necessary and needs to be checked.
Many organizations have already put in place, you know, these
different committees to ensure that things are being run through
the right protocols and that everything is going to be
safe and secure for their organization, that data isn't going
to leak, and people are utilizing AI in the wrong way,
so on and so forth. And now it's really about
(06:13):
how do we unlock value from the sheer amount of
tools that are out there? Right? How do we find
what's right for each single task at hand and then
integrate it throughout our entire kind of digital ecosystem.
Speaker 1 (06:27):
And when you think about the distinction between winners and
losers of the coming years, what do you think separates
the two categories?
Speaker 2 (06:37):
To me, I think it's really about a balance of
structure and flexibility, right. I don't think you can swing
too far in either direction. I think is there a
set of tools that employees can choose from that they
can utilize for the tasks that they have at hand, right,
not pigeonholing people into you must utilize this thing every
(06:57):
single time for this particular way of working. Now, certainly
are there kind of going to be some mandates and
parameters put around that. Yes, And there's going to be
certain industries that have more rules and regulations than others.
But the hope, I think is that you don't have
to stray too far any of the direction. That there's
(07:18):
going to be many, many, many AI tools that are
deployed throughout every single organization. It's just finding which ones
are right for which employee, and then how do we
drive kind of adoption of them. I think about this
like even just a few years ago, with what happened
in the communication collaboration space, right think about Zoom and
how that took off. That Zoom wasn't anywhere and then
(07:40):
all of a sudden everybody utilized it in their personal life,
and then all of a sudden it took off inside
of every single organization. Is a great tool that needs
to be invested in and something that people feel comfortable
with utilizing. They know how to use it, and they
know how to get the value from it. And I
think that can be kind of similar here in terms
of you've got AI tools that people are utilizing in
(08:04):
their personal life, how do we put the right structure
and parameters around them so that people feel comfortable and
utilizing AI in the workplace as well, and making sure
that you know they're able to get the value out
of that they need in order to get their job
done faster than ever before.
Speaker 4 (08:21):
Hey, Matt, well, come on the show. It's always good
to see you.
Speaker 2 (08:24):
Great to be here. Great to see you too too.
Speaker 4 (08:26):
So let's get into some details. I think it's pretty
apparent that I talked to a ton of people around
the world, our customers, prospective customers, everybody that I talked
to about AI is still trying to get a handle
on it. Right, you talk about the need for some
governance and some controls, but I think they've had, in
(08:46):
my experience, they've had a tough time articulating what the
problem really is. Right. They'll talk about risk, they'll talk
about security. They're not quite sure what a solution looks
like us. What exactly is AI drive. I look at
it as AI for AI, But what problem does it solve?
(09:08):
And what's the vision and the value problem?
Speaker 2 (09:11):
Yeah, so I think I'll start with the latter and
kind of vision. I think what we see as an
organization and our feel is really strongly about it is
almost like flipping the script. I think there's the whole
notion out in the market of you know, how do
we ensure that we are making our business the most
(09:32):
you know, cost effective or doing more with less and
things along those lines by by leveraging artificial intelligence. But
I think really what we are finding, what we are
trying to kind of push and showcase, is that you
can make your workforce so much more productive by having
them leverage artificial intelligence. And that's really how you're going
to be able to get ahead of the competition, how
(09:53):
you're going to ensure you're not going to be left
behind in you know, the industry that you work. So
how do we make sure that you know, AI is
being pushed to the forefront and that we're driving we
flip the script to really working towards productivity. I think
what we know right is that today over seventy five
(10:13):
percent of people are actually already utilizing artificial intelligence, but
it's highly distributed across many different tools. It's potentially the
things that they're bringing into it to bring your own AI.
So what really AI drive does is it can it
consolidates you know, all of this different fragmented AI activity
into what we're calling a quantifiable business impact. Right, We're
(10:35):
going to be able to centralize AI visibility of the
different tools that are out there. How they're being utilized,
the how do we guide people to actually utilize it
more effectively and adopt it better? And then how do
we measure all of these things into this kind of
like single actionable vantage point inside the next thing infinity platform,
(10:55):
so that people can really drive impact throughout end productivity
throughout their organization.
Speaker 4 (11:02):
I think that's an important part to highlight, which is
that AI can bring tremendous benefits, but it's not an
easy button and you can't just roll out an AI
solution to your employees and say here, go use this
and automatically they're going to be more productive. I think
a lot of reports right now are saying people are
less productive because they've got all this new learning curve.
(11:24):
Things are changing so quickly. But get into a little
bit more detail, break down some of the key capabilities
and possibilities for Yeah.
Speaker 2 (11:33):
So I had kind of just alluded to what we're
calling almost like four different pillars of when AI drive
represents right, And the first one is along the lines
of visibility. How do we first and foremost get an
understanding of what are the tools that are actually being
utilized in every single organization's environment. Are they the ones
that are corporate approved. Are they the ones that are
(11:57):
most effective in terms of of making sure that people
have the right tool for the right kind of thing.
Visibility around the actual departments of people that are utilizing them.
Are there certain groups that are utilizing AI more than
others and which and if so, which tools are they?
So I think visibility is kind of a key core
(12:20):
starting place to make sure that you have kind of
a bird's eye view of what your digital landscape looks like,
similar to what we do on the deck side kind
of today. Right. The second one is around usage. The
visibility is great, but if you're only getting you know,
data around, hey, here are the tools that are actually
being deployed throughout your organization, it doesn't take you as
(12:43):
far as you need to be in order to like
get to where we were just saying with the driving
of the productivity element. So how do we look at usage?
How do we say that there are you know, x
amount of people in your organization that are really AI champions,
They're utilizing AI a lot, they're finding value from it.
And how do we drive almost like the ball down
(13:04):
the hill or some forward momentum right and ensure that
you're you're you're utilizing the champions in the organization to
push forward the AI adoption and and highlight the value
that they're getting from AI through to all the you know,
other people in the organizations that may be you know,
just gabbling in AI at this point in time. And similarly,
(13:28):
on the usage side of the house, how do we
look at the actual kind of prompts and things like
that that are being pushed into place so that we
can say, okay, you know what, here are the most
common ways that people are generating value from AI, whether
it's something as basic as you know, crafting an email
to something more in depth like creating code. So I
(13:51):
think the usage element is kind of that second core
key pillar that we look at. Following that at a
guidance is number three. How do we ensure that we're
creating action points to drive additional pieces of adoption throughout
looking at not only just hard metrics, but also getting
(14:13):
insight into employee sentiment.
Speaker 4 (14:15):
Right.
Speaker 2 (14:15):
That's and sentiment has always been a core part of
the next Thing platform. It's something that is key in
terms of pushing everybody forward in terms of driving adoption.
So what happens if you know people are struggling with
you know, certain rules or policies or not having access
and you may not have ever seen that before, but
all of a sudden, if you have contextual sentiment pieces
(14:37):
that are coming into play, now, all of a sudden,
you're able to put in place the programs, the trainings,
the communications that are necessary in order to drive adoption
through of AI throughout the organization and with the right
tools that maybe people are asking for because you have
their actual sentiment that they feel around it. And then finally,
(14:58):
is the measurement kind of piece, right, what are the
key metrics that organizations can leverage to be able to
do Provide a roll up to the executive leadership team
and make sure that they're saying, hey, here's you know,
the amount of active users and the trend of active
usage for AI and the different tools across our organization.
(15:19):
We're making great progress here. We're seeing, you know, an
uptick in the actual number amount of engage time with
artificial intelligence across each user. And now all of a sudden,
we can find out, you know, what is the value
or the time saved by utilizing AI, and gain context
by really benchmarking that against other organizations which I think
(15:39):
is a key piece because without that kind of benchmarking
and context, you're just measuring against yourself, and with something
so new in the industry, there's really no kind of
internal comparison that you can have, So those are kind
of key pieces.
Speaker 4 (15:56):
There's a lot there. I think that it high lights,
and we talked about it a little bit. The vision
that next think has our ability to execute being being
developed on a foundation of an AI platform. It allows
us to move quickly in doing these things. What's being used,
who's using it, how is it being used, where is
(16:19):
it successful versus where is it struggling. How do we
share those best practices with the rest of our enterprise
and help people come up to speed. I think are
all things that in our vision and our ability to
execute that others aren't able to do. Using AI inside
the platform to help manage AI outside the platform is
(16:41):
something that no one else has, and I think lots
of people share our excitement on this AI drive coming
out to help really manage this transformational change in it
to a different level. Do you see it as a
natural extension of what we've been doing all along in
our core dex principles that are now just reaching into
(17:03):
some new apps and new technologies, or is it the
flip of that where it's fun fundamentally new approach tailored
to the wave of AI.
Speaker 2 (17:13):
I think it's actually closer to the former. I think
what we want to make sure that we're doing is
keeping structure and process the same. Right, we've had customers
with us for so long they've been able to see
value out of and great value out of the next
in infinity platform. We don't need to reinvent the wheel
(17:33):
on that front, but we do need to ensure that
we're continuing to move forward to innovate to be to
provide the right resources to be the most beneficial kind
of DEX platform for every single customer you know out there.
And really, I think that's an extension of the core
kind of DEX principles that you know you've been seeing.
(17:53):
I think you've probably if you're listening, you've probably heard
us talk about ce diagnosed and fix so many times.
And I think there's a natural kind of extension of
how that comes into play even here, right we talked
about visibility, see diagnose, usage and guidance and making sure
and fix kind of all coming into play there where
(18:15):
it's now you know what's going on in the environment.
You're able to understand what are the great things that
are happening, and how can I kind of extrabulate that
but also fix some of the kind of issues that
people may be having from an adoption standpoint or from
a measurability standpoint. So and ultimately it all stems back
to our greater goal of creating a better digital employee experience.
(18:38):
If you're able to utilize the latest technology because organizations
feel like they have the visibility and foresight and control
over it, then now you're providing not only a better
digital employee experience, but a more productive workforce as well.
So certainly extension and I think there's kind of continued
(18:59):
ways that decks and AI will continue to come together
and we'll push push the industry forward. Here, Hi'm Matt Dina.
Speaker 5 (19:07):
Here. Have you had early feedback from customers or prospects
on AI drive and what would be the thing that
resonates the most with them?
Speaker 2 (19:18):
Yeah, so we have And hello Dina, how are you
the thing that we hear most as of right now
from a lot of the customers that have been leveraging
AI drive for I guess a couple of months now
in preview mode has been really all about adoption, adoption, adoption, right.
(19:39):
I think I started off the top of the call
by saying, everybody's investing in artificial intelligence. That's the case,
the numbers don't lie, and we've heard that from all
the different customers that have been utilizing AI drive to date.
But they're really kind of stuck at a point of
how do I ensure that I'm driving adoption of artificial
intelligence in the right way? I think Tim you might
(19:59):
have alluded to it that you know, AI is only
as good as the proficiency of the workforce utilizing it.
So how do we ensure that we're training people up
the right way? How do we ensure people aren't going
around in circles, which is pretty easy to do with
AI if you're continuing prompting and prompting and prompting, waiting
to get to the answer that you are hoping for.
So what are the best practices for kind of changing
(20:22):
things together and moving that forward? So adoption is probably
number one, and then measurement is number two, right, especially
with some of the customers that we work with that
may have been a little that may be a little
bit more mature in nature in terms of their AI strategy.
You know, maybe they've been able to see to a
certain extent what tools have been out there. Maybe they've
seen some success with driving the adoption of some of
(20:45):
the corporate owned tools or corporate mandated tools that they're
they're uh, put a bit put in place inside their organization,
but they don't know how to continue to make sure
that they're unlocking the insight into how much did that
actually save me? How much? Why has this been so important?
(21:06):
And why should I articulate this as a great outcome
that I can then push to the other people throughout
the organization that may not have adopted that now have
a real sense of Look at my colleagues who are
seeing all this value and time saved and productivity and
things along those lines.
Speaker 5 (21:26):
Fantastic. It feels like a cornerstone product with a big,
big future. What can you share about the roadmap in
general for AI drive over the next couple of years.
Speaker 2 (21:36):
Well, the one thing that I will say is there
will be continued investment here. I'm on the product marketing side,
so roadmaps a little bit out of my full jurisdiction.
But what I will say, is that we know that
we want to continue to invest in this product, that
there's going to be continued evolution of it that as
(21:58):
we hear more and more from customers about you know,
the AI value gap that you know Gardner has coined,
and how we can best represent the data to be
able to showcase how that can be unlocked the better.
And we're going to continue to leverage you know, a
lot of the different dex capabilities that we have and
infuse them in there to make sure that you know,
(22:20):
we're taking full advantage of the Infinity platform, you know
that's already out there because there are so many kind
of tie ins, right I alluded to some of the
engagement pieces before, but there's so much more than that,
especially as it relates to some of the digital adoption
pieces as well. So continued investment, continued breadth of scope
(22:41):
across the platform, and ultimately continued learnings for for our
customers as well.
Speaker 5 (22:49):
Great does AI drive itself? Leverage AI today and how
do you see that evolving in the future more less?
Speaker 2 (22:57):
Yeah, multiple different facets actually, So as of right now,
there's functionality in there that makes it extremely easy to
be able to As I mentioned, kind of ladder up
success in the status. Right, we're leveraging our own artificial
intelligence to scan across the next in coffinity platform and
(23:18):
gain learnings from what the data is saying. Right, how
do I quickly, if I'm managing the next Thing platform,
get a read from our official intelligence on you know,
here's the progress that was made week over week. Here
are some of the action items that we should take
to continue to drive more productivity and drive more kind
(23:40):
of active usage, and then summarize that and be able
to provide it up the ladder without even really having
to spend too much time kind of analyzing everything that's
going on inside the AI drive dashboard, because it's already
been there and correlated against, like I was mentioning before,
the benchmarks of other organizations out there, so that they
can gain some context. The other one that I think
(24:02):
is extremely important on the AI front is we had recently,
I guess it was a few months ago now launch
AI sentiment analysis as part of our kind of employee
engagement campaigns. And so now all of a sudden, this
becomes this key way of leveraging AI for you know,
AI purposes. If I send a survey out that is
(24:25):
tailored to each individual AI application and get you know,
thousands upon thousands of responses back. How do we leverage
AI to culminate all of those things, find trends, find categories,
and then make recommendations on ways to actually improve some
of the processes that are out there. If everybody's saying, hey,
(24:45):
you know what, I have been utilizing chat GPT, but
I'm willing to make the move over to Microsoft Copilot
if you know, we can do X, y and Z
with it, and that becomes something that has been said,
you know, ten times, one hundred times, two hundred times.
Now in your your large organization. Now you've got some
backing and some guidance as to how you can kind
(25:08):
of better make an approach to providing that shift in
the organization and driving additional AI adoption. So yeah, multipleffer,
multiple different levels of AI within AI drive today.
Speaker 5 (25:22):
Definitely that the insight that you would get back to
your point of thus you diagnose fix with the power
of AI drive gives you a lot of actionable information
that would really help with the decision making based off
of data. Not just that, but also the analysis that
you do from the engage campaigns alluding to that how
(25:45):
might the roadmap intersect with other nexting solutions like assist
or adult in the future.
Speaker 2 (25:50):
Yeah, so I think assist is already live and well
today right in terms of how these two kind of
pieces come together. If I'm utilized in the next Thing
platform and i have a question about the artificial intelligence
tools that are deployed throughout my organization, I'm going to
be able to ask Assist and it's going to be
(26:11):
able to provide answers for me based on the data
that we're already collecting. It's part of the big benefit
of AI drive being embedded inside of the Infinity platform
and coming standard kind of out of the box. Is
now all of a sudden, all of the different additional
pieces of data that are nicely collected, that are nicely
displayed and easy to read, are already kind of being surfaced,
(26:34):
and Assist is reading into all those things, and you're
going to be able to effectively ask additional questions on
top of what's already displayed on screen to get additional insights.
So Assist is out there, and the assist also has
engagement campaign creation capabilities as well, which is nice. So
while we're coming with pre configured AI engage campaigns for
(27:00):
or specific tools you know you could there's nothing stopping
for you from asking assists to create an additional one
and continue to get you know, quick value and be
able to see things progress forward. On the adopt side
of the house, this is another one that I'll just
lightly touch on now, but I think the correlation is
(27:22):
certainly there. Right, we talked about guidance as that third pillar,
and there are many many different things that you can
do with AI drive out of the box from a
guidance perspective, but the layering addition of adopt on there
takes that one step further. Right, think about custom guides
that you could put in top of AI tools through next,
(27:43):
think adopt and be able to effectively have you know,
these in real time, contextually relevant guided ways to not
only you know, push people to the right tools, but
also have them utilize those tools most effectively because we
have you know, the guys set up for every single
(28:04):
employee to be able to do so so and customize
for that particular tool to make sure that the user
experience is the most intuitive possible. So I think we
touched upon you know, breath. The next thing platform and
continued intersection of AI Drive, and that's no different for
what we're doing with Assistant Adopt and AI Drive as well.
Speaker 4 (28:28):
So, Matt, I think many others are like me with
the art of the possible spinning through their head, the
breadth of our platform and where this might apply itself.
Let's let's hone in on for our listeners, who in
an organization should be paying the closest attention to AI
(28:49):
drive right now? So a role or some specific priorities.
Where does it serve itself best? And what are the
risks if this kind of arena is ignored, and what's
the best way to learn more? Especially how much does
it cost?
Speaker 2 (29:08):
All right, well, you know what, let's start and reverse
because it's the question that everybody always asks, how much
does it move? And we shouldn't have kept everybody waiting
till the end. But AI drive is available for free
for everybody as part of the next Think Infinity platform.
So if you are utilizing next Think Infinity today, in
a few weeks time, you'll see AI drive roll out
(29:31):
to your particular instance, which is great because I think
it's a key, as I think we said, cornerstone of
you know, driving digital employee experience forward is the you know, visibility,
adoption and value that's garnered from artificial intelligence. So having
AI drive available to everybody will go a long way,
(29:52):
and there's no need to even have to further justify
additional expense in terms of you know, who should be
paying closest attention to this. I think it's it's threefold,
if you will. So one is it's no secret that
end user computing teams are the teams that are utilizing
(30:14):
Next Think Infinity the most as of right now, right
and I don't anticipate that on changing, but I think
there is a major tie in between what AI drive
can do and the value that end user computing teams
can see. And it can be as simple as, hey,
(30:36):
you know, you've just been responsible for deploying a whole
bunch of AI tools across the organization. Aren't you curious
about how they're being adopted, what the actual kind of
number of people are in terms of utilizing them, how
what are they utilizing them? And then ultimately are there
things that we may need to roll back? Right like
are there particular tools, I think tools that can be
(30:59):
you know, positioned as Hey, this was a pilot. But
the pilot, you know, didn't didn't surface the value that
we were looking for, So let's try something else. That's
the thing with AI. There's so many tools out there
that it's going to be a trial error run for
a lot of organizations in terms of what are the
most effective ones for their organizations. So how do you
(31:19):
reallocate and repurpose a lot of the different kind of
budgetary components that may be invested in one place and
repurpose them in another in order to ensure you're finding
overall efficiency. And I think a lot of that kind
of falls back into the hands of end user computing
teams having full kind of knowledge and scale over what
their environment entails. The other two I think in some
(31:40):
organizations AI centers of excellence, right, those are people who
are putting in place, here's what the rules of the
laws of the land are in terms of the AI
tools that we'd like to use. So having them have
the visibility and understanding of you know, what are our
people actually utilizing the tools that we're recommending, are they
(32:03):
utilizing them effectively? And how can we drive continued adoption
of them? Because they're the ones that are kind of
wanting to put them in place is key for them
to continue to provide learnings back to the organization. And
then finally it's all the way up the ladder, right.
It's no secret that every single organization has AI top
(32:23):
of mind on their kind of strategy planning sessions each
and every single quarter in year. So how do we
ensure that C suite has visibility over these kind of
key components as well and really be able to provide
that information all the way up to be able to say, Yep,
here's the impact that it's making and here's how we're
driving our organization forward, because we don't want to be
(32:45):
left behind by not utilizing AI to its fullest potential phenomenal.
Speaker 1 (32:51):
And I have to say that before we leave AI
drive behind and take our leave. I really loved what
you said Tim about using AI inside the platform to
help manage AI outside the platform. It's such a cool
way to put it, really succinctly articulate. It's not just
AI drive, but I think that the total next thing
strategy around AI adoption and transformation very very cool breakdown
(33:16):
as well, and Matt really really appreciate it. And look,
before you go, sometimes we have our guests on reality bites,
and I dust off this question usually because I'm genuinely
curious about it in the individual case, and there's somebody
who works with you, I'm genuinely curious to know your answer, Matt,
What do what do? What do you most like about
(33:37):
being a next thing or what's top of your list?
Speaker 2 (33:40):
Yeah? Two four. One, of course, is working with both
perspective and current clients on a regular basis. Understanding, you know,
what they've got going on, their environment, the challenges they're facing,
and how can we continue to help and propel them
forward is one, and then two is really long lines
(34:00):
of uh, making impact right and understanding of hey, here's
the things that you know we're hearing from our customers
and how do we ensure that we're taking that back
to you know, product and engineering teams and say, you know,
these are the things that we need to develop. And
I feel, I guess in the role that I currently have,
that I have an opportunity to be you know, voice
(34:22):
of the customer in terms of being able to relay
that back and ensure that we're building the things that
are going to be the most impactful for every single
one of our customers, like I said, to propel their
organization forward and get the most out of digital employee
experience platform like next Think.
Speaker 1 (34:39):
Well said Matt, and thank you so much about breakdown.
Of course, interested listeners can learn more about AI drive
by looking at the show notes. We'll have links to
all kinds of resources and places you can get a
bit more information inside and even perhaps make contact with
somebody to discuss it in your account. Thank you Matt
for joining us, for telling us about this amazing, amazing
(35:00):
new product.
Speaker 2 (35:00):
Man really appreciate it.
Speaker 3 (35:03):
To make sure that you never miss an episode, subscribe
to the show in Apple Podcasts, Spotify, or your favorite
podcast player, And if you're listening on Apple podcasts, make
sure to leave a rating of the show. Just tap
the number of stars you think the podcast deserves. If
you'd like to learn more about how next Think can
help me improve your digital employee experience, head over to
next think dot com. Thank you so much for listening.
(35:26):
Until next time,
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