The AI and CX Landscape
Join us for an enlightening session with Ben Edwards, Director of Sales Engineering at Sandler Partners. With a wealth of experience in implementing contact center solutions for thousands of agents at industry giants like Dell and Hewlett-Packard, Ben brings invaluable insights into the world of CX technology. In this session, he'll guide you through the process of evaluating your AI and CX technology needs. Discover the essential questions to ask your team and organization as you embark on this significant challenge. Learn how to identify the right starting point for evaluating your technology stack and address the most critical challenges and channels first.
(upbeat music)
- And welcome to our next session
with Ben Edwards of Sandler Partners.
Ben, how are you doing today?
- Hey, it's a great day.
What an awesome couple topics that we've got here
to talk about today, Brian.
Really excited.
- Yeah, and thanks for the time that you've given us today.
I know you're busy talking to a whole bunch
of trusted advisors here, which we'll get into.
So we have slides here, which is great that it can kind
of guide us through this presentation a little bit,
but just for the audience's sake,
I've asked Ben to share a lot of his expertise
and understanding around like,
how do you evaluate the CX landscape?
So that's what we'll kind of talk about here.
Maybe you've mentioned a few other things,
but maybe first and foremost, Ben,
can you give us an introduction of yourself
and your experience at Sandler Partners?
- Yeah, definitely.
Let's jump into the next slide.
So yeah, Ben Edwards,
I'm Director of Sales Engineering here at Sandler Partners.
And I've got about 20 plus years of experience
in contact center.
And what I do most of the time is I'm talking to customers
or buyers, people who are probably on the session
listening in today, as well as what we call trusted advisors,
people who come alongside buyers and customers
to help them out.
My role is to bring all of that experience, Brian,
to help uncover opportunities
to really just help the projects get started.
I can also bring in trusted advisors and make introductions.
And in the end, what I think I do is help the buyers
to identify the requirements that they're looking for
and the likely solution providers
that they're going to be working with
and set them on their path or their journey,
as we're calling it here today, you know.
- Yeah, and so just for the audience and myself,
to clarify, it's like, and we'll talk about this,
it's like there's so much time that you can take
into the evaluation phase.
Like it's bringing in yourself and Sandler partners
to help with the better understanding of, you know,
how to evaluate and how to get connected to partners.
Is that kind of like how to clarify the main goal
of what you guys do?
- Yeah, definitely.
I think you got it just right.
- Okay.
- Okay, so let's go to this next slide here that you have,
which is again, more or less like the thesis here
of what you're trying to share with us today.
So YAI as well, even for customers
and trusted advisors, tell us why, Ben.
- You know, I think journeys are always exciting.
I had one too Orlando recently, it was exciting,
but it's also very nerve-wracking.
I traveled out of the country and before that,
journeys are so important.
There are growth opportunities for us, Brian,
and doing something here, like we're gonna talk about today,
like where we want to embrace artificial intelligence
or AI or CX customer experience.
It's okay to be a bit nervous at the beginning of the journey.
You know, I think that there is just such a high interest
in AI right now.
I talk about it all day in pretty much every meeting
that I make sure that I bring it up.
And can I, can I, let me stop you on that
just because I know you're talking
to a lot of different customers.
Are they bringing, has it like shifted?
We're now there bringing it to you of like,
hey, like there's this all AI stuff,
like what do I do here?
Or are you still kind of being more proactive
than talking to your customers about it?
- Yeah, definitely.
I'll bring it up if they don't.
I love the conversations where they bring it up.
I think like a year ago, every CIO said
that they needed to have any AI strategy.
I think that that's not just trickle down,
like that's avalanche down.
Everybody needs to have an AI strategy,
regardless of like what your level is in the company.
I've got a stat for you.
Tell me what you think about this.
IBM tells us that like 78% of organizations
are investing in AI just in this year alone.
So yeah.
- That's crazy.
That is great.
So that definitely means that they're coming to you.
Yeah.
Well, I mean, in that regard,
and I've had this conversation with a few other like
technology partners and agencies,
but it puts the pressure on you bad to like
have that understanding of everything that's out there today,
because I can just assume, and correct me if I'm wrong,
but a lot of customers and brands will come to you,
just trying to ask questions to better understand it.
Is that accurate?
- They do, they do.
And I always feel like being a trusted technical advisor,
the role that I wear and play,
I don't have to know every answer though, Brian.
I'm gonna actually jump into that in a little bit
with you.
- Yeah.
- Okay, cool.
So let's go to the next thing here,
which is the solution, the cycle.
And I love this, and this is why I want to hear from you
in the audience, just because this is not just,
hey, one or two times that you've kind of gone
through this cycle with a,
I'm just gonna call them brands for right now.
But you know the ins and outs at all this.
So go ahead and tell us a little bit about
how this cycle kind of works.
- Yeah, I think in the solution cycle that a business goes
through in adopting a technology,
there's a lot of stages that are important.
And I'm just showing probably four of the key ones here,
evaluation and selection.
Like that's early, that's, hey, we're talking about this,
Brian, we haven't done anything yet.
Like the real hard work hasn't yet started.
Hey, have you ever built a house though,
or jumped into a big project where you didn't have a plan?
- It's better to have a plan.
- It is, it is.
A lot of times customers, they just want to jump
in implementation.
And the business really just wants to get into that,
hey, get me the technology, I want to start using it part.
But you and me today, let's just start at the beginning
of this journey, let's focus in on evaluation.
And here's why I wanted us to do this, Brian.
I think there's a lot of uncertainty,
a lot of people don't know what AI is all about,
can help them, I don't think there's been people
who have really done projects like this before.
So it's gonna be new for a lot of people for a while.
- Yeah, and I mean, let's be honest though,
like technology, evaluation and even implementation
has been difficult even leading up to this point.
So I can imagine that it's kind of getting
into this direction of like, all right,
we might have an issue here.
- Yeah, I think that's so true.
It really is.
We always want to have a good foundation
to start any project, whether it's a big complicated one,
like we're talking about here or not, we're not at all.
So all right, thank you for showing us this one.
Let me turn the tables on you.
Take a look at these numbers here on the left.
This is from Gartner talking about how we spend our time
on projects.
I mean, look at that.
Buyers don't have time.
Is my assertion to you.
- So just so I understand this correctly,
and I hope the audience does too,
like we're looking at this pie chart more or less
like in the entire evaluation phase, right?
It's saying during this entire evaluation phase,
27% are researching independently, 22% are meeting
with my group, 18% researching independently offline,
others meeting with potential supply or 70%.
That's like, to me, that's so diverse.
Like there's so many things that you can do people
to talk to, like, right?
Like that's also a takeaway that I see.
- It is.
Like that's valuable time that we see over there
in the pie chart in blue.
And then I think it's great.
It's like 83% of their time is spent internally,
you know, talking with stakeholders.
And this is really critical.
I'm gonna, we're gonna jump into stakeholders in a minute
because I think again, it's a part of like having a plan
that's happening on the right team.
But I wanted to talk about this because this is where
that trusted advisor can come alongside a customer
and really help them because the trusted advisors spend
almost all of their time in that 17% right there.
I, as a buyer, get to go through a project like this,
maybe once a year, once every couple of years,
our trusted advisors are out there and available
for the customers.
And that's all they do.
That's what they specialize in.
- Ben, has there been any change in this graph?
If you look, like if we were to look at this
five, six years ago, do you think that we would be seeing
the same exact thing?
Or has there been any sort of shift in the last year?
- I think the shift is that the trusted advisors remit
or ability has really expanded.
Here's one for, I've got one trusted advisor that we work with.
They authored a report and a buyer's guide
on 70 providers of conversational AI.
And so of course they couldn't have done that a few years ago,
there weren't even that many, but there's a real meeting
of the minds in this space right now.
And I'm grateful for it and happy to be a part of that.
- I'm just gonna have to dive a little deeper into that.
I know that's not you, that's someone else,
but is there a point where you just have to,
well I don't wanna say give up, but like,
is there a point where it's like, okay, well,
if you go past the 20th vendor, the 21st vendor,
at a point it's like you're gonna,
you're not gonna find any brand new features
or you know, brand new, I don't know,
strategies of implementation.
Or do you or is it worth the time
to really understand everything that's out there?
- Good point here, 'cause there are hundreds
of providers out there.
And I know that in that list of 70
are a good representation.
And I think that's really one of the themes here
in evaluation is that we don't wanna just jump in
to a project with the first provider that comes
into our inbox or with the provider
that we already have a contract with.
We wanna have, you know, intent, we wanna be meticulous,
but we can't spend our whole time evaluating.
We can't live in this phase forever.
We have to make a decision.
We have to for the business,
for the health of the project move forward.
70 was a pretty good number, it's a great report.
- And maybe I'll just call out that.
I think for me looking at this,
like one thing to take away is that
it does take up so much time.
And I think there is a line that you have to draw of like,
you can either educate yourself,
but know that it's going to take a long, long time
in order to really understand the space
of where it's at right now,
or you need to partner with someone
that you can really rely on to get that trusted feedback.
Do I have that right, though?
- Yeah, you really do, you do.
If you're gonna have a project,
you should have a project manager.
Somebody who knows the methodology
of running a project, if you're gonna jump into
artificial intelligence,
get something you know it's about AI,
or it's going to help you level yourself up,
whatever the case may be.
Half in the right tool is always one of the things
that unlocks making a specific task,
or a job, or in this case, a project, so much easier.
- Yeah, I'm gonna skip to this next slide
that you put together here,
which is around the stakeholders to engage
a lot of different stakeholders,
first impression, that walk us through the slide for us.
- Yeah, I don't think, this isn't a list
that tells us who we have to have.
My thought here is for those of you watching today,
just the breadth and scope of people
who can participate in these sorts of projects.
Brian, you tell me, how many stakeholders on average
are involved in a team to make like a CX
sort of purchasing decision?
- I mean, I would tell you that there's one
that really makes the call, like yes,
we're gonna sign the contract or not.
I think that person is incredibly important to get
from the first get go.
And then usually there's probably two other stakeholders
that are more unlike the nuts and bolts of implementation
and solving that outcome is kind of like
the answer I'd give to you.
- So it's actually closer to nine to 13,
so a little bigger than even that pool.
Yeah, it's big.
And that's what I'm just wanting to show
and suggest to all of us, hey, let's recognize
that these are big business impacting decisions.
Here's some great people in your organization
and or similar in each of our organizations, go out there.
Go find them.
Recognize this though, Brian, I say this pretty regularly.
This is not just an IT decision,
but we want to find the business,
work with the business.
We want to build that cross-disciplinary team here.
Because in the end, and we'll keep talking about this,
successful projects are aligned to business goals.
And like I said, we'll get into that in a little bit more.
So yeah, check out these titles
and I really like the outcomes here as well.
If you haven't worked with these folks before, Brian,
take a look at the rightmost column
under the business outcomes and you'll see
what motivates that.
People have different motivations
because of what they're responsible for in their work jobs.
- And clarify for us, like, because I think
we're pretty vague earlier on, but would this be
any sort of tech implementation across the business
or this is pretty specific to customer support,
customer experience?
- This is more customer experience
and artificial intelligence.
But I think the principal in general applies.
- Yeah.
- So I'm just like looking through this.
I will say the, gosh, IT has to have such an impact now
more than ever before.
It's not just about implementation at this point,
but it's almost about the philosophy
and principles behind implementing AI
and not in a business.
Do you come across that now?
- I do, I do definitely.
I was at an event recently with a bunch of CIOs.
And they were continuing to echo the message
that they keep getting asked to do more,
maybe not with less, but their portfolio of solutions
that they have to provide for their business is expanding.
And this AI one in particular has people nervous.
They don't have the staff.
There's not a deep bench.
And they are barreling forward into this future
without the experience and the staff that they're accustomed to.
- Yeah.
Well, I just find this so interesting
because it's like, it seems to me,
if I were to categorize it,
it's a bottoms up approach right now, right?
Because something like chat, JBT comes out, excuse me,
and users all across the world have access to this.
And let's be honest, most people in a business
are probably utilizing chat GBT,
whether the CIO knows about it or not.
And now it's like, hey, we start using this,
start using this.
And again, my assumption is that the word is going
from the bottom up to the top.
And you have the CIO that is in the CTO
that is kind of like maybe pushing back more risk-averse.
And it's such an interesting time when you think
about it that way, or maybe I have it wrong.
Like, is that what you've heard as well too?
- No, I think you have it just right.
Rare is the project actually right now,
where it's at the CEO level coming down.
I do have one CEO I can think of recently,
rather a large billion dollar company,
and said, we have to adopt AI.
That was the, from on high.
And that can be effective, it really can.
And like you said, from the ground floor up,
each of us, let me try it this way, Brian.
Yeah.
Are you using AI?
Am I using AI?
Are we use, have we found ways to embrace it
in our work lives every day?
I think we have.
And that infusion that you and I are doing
at our individual contributor levels,
magnify that across everybody at Customer
and at my company.
Heck yeah, it's like a groundswell.
It's just really building.
And now we are here today to talk about how,
you know, we wanna evaluate these use cases,
and we'll get into those in just a minute,
to really find business value.
It's really happening.
- Yeah.
Last question on that is,
have you seen the need for like a chief AI officer,
and has that been coming up just because of the amount
of work this entails and it's changed in the shift,
can you give all of that responsibility,
added responsibility to everything else
that was on the CTO's plate,
or is that something being talked about?
- I have met two chief AI officers this calendar year.
I think that number's gonna be a lot bigger next year, Brian.
That was a great question right there.
We haven't answered the question at our company just yet.
And so we have a couple of senior leaders
who are sorting out the responsibility.
And I think that that's okay too,
but yeah, some companies.
- Wow.
- Tech forward right there being chief AI officer.
- Yeah, that's pretty cool.
- Yeah, that's super interesting.
All right, so I'm gonna go to the next slide here
and talk about the essential questions to ask.
- Yeah, right.
We're sitting here in this evaluation phase, the stage.
And let's say that we, from that previous conversation,
we've gotten like a group of people together.
And we mentioned earlier that we're gonna spend 83%
of our time talking internally.
I wanted us to spend a little bit here.
Like what are some things that we should ask ourselves?
And the first one for me is pretty straightforward,
but I think it's important to say out loud is,
you know, what is it that we're doing today
that needs improving?
You just said, I'll say it back to you,
but slightly different.
Nobody wakes up in the morning and is like,
"Oh, hey, you know what I need?"
"Is some chat GPT at work?"
"Let's go put in chat GPT."
No, instead they say, you know, they have a use case.
They have a reason, something that needs to be solved.
And I think that that's really the right way to do it.
I think these sorts of questions up here for me,
I hope they're gonna make those of you watching
and listening in today look hard at your operations internally.
- Any, and sorry again to put you on the spot then,
but any patterns that you see, like that are coming out of this?
What are we doing today that needs improving?
Like, are you seeing consistent answers?
- I categorize them like this,
strategic opportunity or areas of great improvement.
Those are nice positive spins on things,
but like opportunity, strategic opportunity,
like what can we do that's really gonna revolutionize
our business or our customer service, our sales team?
You know, and maybe with question, you know, number four,
like how does your business justify investment?
You know, if we can adopt some great AI or CX solutions,
we're gonna have massive improvement.
Maybe that will be less churn in our customer base
or increased sales.
And that right there, either of those,
either the cost of retaining a customer
or increasing revenue are going to justify this.
Brian, I wanna spend a minute though on number two.
- Yeah.
- Right here.
What are some of the great AI use cases
that people can actually buy today?
It's not just this nebulous thing AI.
I think the number one that we've all experienced
are more AI features.
Features that are like attached to your meetings
or your soft phone, you know, recording, transcription,
things like that.
How about generative summaries?
Have you had those yet, you know, you go to a meeting,
hour long, and then in your email,
you've got like this 45-word summary, you're like,
"Darn, that was spotable."
I wish that all the 45-minute meetings
could just be 45-word summaries.
So let me kind of pin you on that then.
It sounds to me that, and again, I'm generalizing,
but the use cases are more internal to start with
than external serving customers,
and then maybe the response is back to customers.
Is that also what you've seen,
or would you recommend that as well too?
Like, well, if you're gonna start with anything,
maybe start internally with internal processes,
business efficiencies, then experimenting with,
all right, how are we gonna utilize AI
in actual customer engagement right now?
- Yeah, you're right.
When it's internal, we have this more popular term
this last year, so-called employee experience,
and those are really like productivity enhancing
capabilities, less meetings, maybe those action items
that we agreed to in our last meeting
get automatically saved into the CRM,
or something like that, employee experience.
But let's give 'em some customer
or sales use cases as well.
I'm gonna bring these out of the contact center.
Think about a standalone chatbot.
Those have gotten so much better in the last couple of years,
and I called my bank the other day,
and I talked to a virtual agent.
I didn't talk to a real human,
I talked to a virtual agent.
Same thing when I had to change my flight home
for more land though.
So those are great examples of AI.
You know, they kinda fall under that self-service terminology,
that idea that I wanna self-serve.
Let me give you another couple ones, so agents.
Number one cost in a contact center, Brian,
is not the AI that you're paying for,
or the brick and mortar that you're unfortunately
maybe still leasing even if you work from home.
It's the humans that are on the phones
and handling the interactions.
So in that contact center world,
this is where we really wanna bring AI in
and think about real-time use cases like this.
Brian's on the phone, talking to Ben.
Ben is a high-maintenance customer,
and maybe I'm being really demanding, Brian.
AI's gonna coach you through how to talk me off the ledge
and how to make me happy in real-time.
Now I think that's pretty cool.
- Now, I think you're spot on,
because you see the AI, like,
co-pilot's coming out for engineering, right?
Like, it could be identical to the agent side,
like a co-pilot.
- One other use case that was from my background,
I had 5,000 agents, I had 75 employees who did nothing,
but listen to those 5,000 recorded calls.
We got to 4% a month of calls that got evaluated.
Instead, with AI, we're gonna record every call,
we're gonna transcribe every call, and we're gonna score
every call, and chat, and email,
and all of the digital interactions.
So 100% QA, I like that.
And then those same 75, I think about what we could've done
with those 75.
We once have done with less of them,
we would've had those 75 people on the right interactions,
rather than like needle in a haystack,
maybe finding a really great call or a bad call.
I think that, dang, we could've been such a higher
performing organization.
- Yeah.
- If we had had that.
- I mean, it's crazy just to think about that for a second.
Like, we have the ability, you have the ability
to analyze 100% of phone calls now.
Like, come on.
- Every interaction.
So let's go to this next slide here.
So evaluating your tech stack, buying or building,
oh gosh, what knowledge you're sponsoring,
who will support and manage these,
these give me,
this just makes me stress a little bit,
just thinking about, gosh, there's so much to do
in the evaluation stage.
And again, that's why you're here Ben,
but walk us through this slide for us.
- I think this first point is really key,
and it's kind of got a similar thought
from the last couple of topics.
Like, let's look at ourselves,
let's know ourselves, Brian, pretty thoroughly.
Let's look at our operations.
Are we a buy shop or are we a build shop?
I mean, large enterprises, they like to build,
they got big budgets, so we like to think SMB,
they prefer to buy.
But really with AI, like, I mean,
I'm getting emails and offers for AI this and AI that,
what do we wanna do here?
So, I wanna go back, let's keep building this evaluation,
you know, effort that we have here.
We're coming up with a business goal,
we've found our stakeholders, we've agreed,
and now we're asking ourselves, like,
do we really have the chops and the budget to go out
and like get some platform capabilities
and hire some developers and,
or, and that's not a bad thing,
I don't mean to say it that way,
but, or are we looking for a solution that's a build?
Let's look at the second point here.
You know, is the AI that we're looking for going to be,
like, a feature, like we just talked about,
like you and I wouldn't go out and like,
write custom AI to record calls and score them?
People have already done that,
like we'll just consume that as a service from somebody else.
So, AI can be standalone or it can come as part of your CRM,
like, customer.
You guys are a CRM, in fact, you're a CRM
in the contact center and you have AI capabilities.
So, people who are customers of customer today,
they can go out and get AI from you guys natively,
or they can go out and they can get AI standalone.
And there's benefits to both, right?
Don't you think?
- Yeah, oh yeah, who's benefits the both?
But it's, again, what is this problem?
Is it solving and what are your, you know,
your variables that you have to deal with at the end of the day?
I've got some really big complicated ERP
and supply chain and my CRM's a mess.
Like, I don't have time to build.
Like, I'm barely, you know,
I've got so much tech debt right now
that what I really wanna do is take advantage
of some services.
You know, here's another one.
I think the third one is important
'cause I want people to realize that you gotta have knowledge.
And that means a knowledge base,
that means a repository.
Because the AI in any of these use cases
that we talked about just a couple minutes ago
doesn't just, well, actually, right,
we don't want it to just generate random answers.
And we don't want the GPT that everybody's afraid of
where it's like, you know, creating answers
from other people's repositories
or just hallucinate as they say.
So where is knowledge?
And make sure that that is available for the AI as well.
It's a tech advantage of.
- Yeah, I think that's honestly, from my point of view,
like that is probably the most important part of it, right?
It's really understanding the knowledge data,
that you have that even others don't, right?
That can like actually make use stand out
at the end of the day by using these AI tools.
My company has a lot of intellectual property.
And that's a big part of our value as an organization.
And before we adopt AI,
we want to make sure that we're going to be secure there,
that we're not going to lose control
of that intellectual property,
that it's properly represented
to the people who are going to consume our chatbots,
our virtual agent experiences that connect to this.
And this kind of leads into this next part.
And we've kind of been talking about this.
I think maybe, is this what gave you heartache,
or heartburn this last one?
Who the heck is going to support that?
- Yeah, I mean, this closes the loop, right?
So a lot of conversation earlier about like,
hey, there's some companies that are installing
a chief AI officer,
because they don't know the answer to this question sometimes.
- Yeah, it's part of that uncertainty of the journey.
It's fun to imagine the destination
and all of the fun that we're going to have there.
The bold, bright future.
But what are we going to do when we get there,
when we arrive?
And how are we going to make sure that
the investment continues to deliver value for us?
If you've never had a solution like this before,
do you really know what the care and feeding requirements are?
Is it an hour a day?
Is it an hour a week?
AI, Brian, it's not magic.
Nothing is, this is technology.
And someone needs to, maybe for these turns,
tune your AI, train the AI.
And that is really the case.
And you can do it internally.
- Right.
- Your provider maybe does part of it,
but somebody has to do it.
Somebody's always needing to tend to the shop.
- Right.
100%-- - That's important there.
- Yeah.
- So last but not least, I think,
and this is, I mean, come on,
like this is kind of the aha moment here,
where it's about business outcomes at the end of the day.
I love that you put the highest priorities in here.
'Cause I mean, again, this is what I hear all the time too.
So for me, it's almost really sure.
And like, okay, we're not missing anything.
I'm not missing anything.
But go ahead. - These are priorities
that I typically use when I'm talking with like
people buying AI in contact center solutions.
And they can be whatever they are,
but the key takeaway, you already said it,
is it's these sorts of outcomes
that are really going to cause an organization
to adopt this.
You know, we said that earlier in this conversation
that there really is an imperative right now
that people are interested in AI and CX,
that people are making that investment right now.
And I just encourage all of us to find what it is
or we're trying to achieve.
You know, what's not up here, implement chat GBT.
Or, you know, some cool hip technology.
But boy, if I could reduce churn by a couple of percentage points,
that does a lot for me, a ton.
I mean, if I can improve brand loyalty,
in heck yeah, man, if my AI can not just answer questions,
but if it can answer it in the style,
the tone that it matches like my marketing
and my culture, right on.
That's going to make my customers more sticky,
more interested in buying and consuming whatever it is
that I'm selling.
- Yeah. - So.
- I have one question for you Ben,
then we'll finish here.
But when I see reduced costs, pretty easy to measure that,
increased revenue, easier to measure that.
Improved customer service, how would you tell someone like,
"All right, that's what we want to do,
improve customer service."
And then it's, well, okay, how are we going to measure,
you know, we were actually doing this or not,
what would your response be to those individuals
that are asking that?
- Now, like 10 years ago, we would have been talking
about surveys.
You know, did Brian complete a survey?
I mean, that first and foremost was like,
did the surveys get sent out?
Did they get completed?
You know, we want to evaluate and score.
And I think that AI is so helpful here.
- Think of that point that you and I both geeked out on,
like every interaction can be evaluated and scored now.
So I think that's probably like the number one way
that an organization should look at AI
and improve in their contact center team,
especially like that use case is exceptionally strong
right there.
Get 100% of your interactions evaluated.
Because then you're going to find the right ones,
the ones that you want to teach people to avoid
or teach the people to replicate.
Here's something else I want you to think about on this one.
You asked me earlier about how do we get into this?
Just have the conversation, okay?
Just open yourselves up, take a bit of a risk
when you're in this group of stakeholders that you've built
and just open, have a business conversation.
You don't have to lead with the technology
or tell them that you found the coolest chat bot
or the best widget that does this, that or the other.
You don't need to be an expert.
Don't be afraid to just ask questions.
Use the trusted advisor.
That person, that role can also help people
through these conversations.
Heck, user sales engineers, customer has just a bunch
of great sales engineers as well.
So use your solution providers to help navigate
your organization through these conversations.
- Yeah.
Well, Ben, thanks again for your time.
I think this has been fantastic.
Again, just to clarify here for the audience, right?
Like evaluation now more than ever is incredibly important.
And just to take the steps and correct me up on wrong, Ben,
but what I've learned from yourself right now is like,
you gotta look in words, you gotta understand business outcomes.
Stakeholders, we're not talking about one or two stakeholders
from your research, you're telling us that.
Like, no, this is a whole company initiative now.
And so it's important to reach out there.
And you gotta trust the people around you
if you don't have the time
and most of us don't have the time, right, Ben?
- They really don't, Brian.
I'm glad we made time today.
Thank you.
Thank you, customer, for having me today
and putting on this event for everybody.
I guess the journey that we're on here around AI especially
is maybe uncomfortable and nerve-wracking, it's new,
but it's also exciting.
It's a great opportunity.
I suggest that you guys get talking about it every day.
I'm thinking about it in my professional life,
my personal life, I think about it with my kids.
I think about the privacy and of course the opportunity.
And I think that all of that fits in this evaluation phase
that so many of us are right now.
It's a good place to be.
- That's true.
Well again, thanks for your time, Ben,
and thanks for the session.
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