This HITT brings together technology industry experts to discuss the evolving landscape for tech advisers in 2026. The panel examines how customer conversations are shifting from platform-focused questions to outcome-driven inquiries, with the market growing to six trillion dollars at nearly ten percent growth. Key themes include the uneven but expanding impact of AI across business operations, particularly in customer experience and productivity enhancement through micro agents. The discussion covers the convergence of technologies like SASE, SD-WAN, and zero trust into unified modern enterprise architecture solutions. The speakers highlight the rise of managed services across all business areas, from traditional IT infrastructure to AI model management, as customers seek to reduce complexity and vendor relationships. They also address infrastructure challenges, including data center power constraints being solved through innovative solutions like supersonic turbines. Throughout the conversation, the panel emphasizes that successful tech advisers differentiate themselves not through competitive pricing but through strategic insights and understanding of client business outcomes, marking a fundamental shift in how technology advisory services operate.
Transcript is auto-generated.
IoT, edge, AI, security, connectivity, they’re all blending into these very high value opportunities. And the advisers who can see those intersections and guide customers through them are the ones who are gonna be winning big this year. So to help us break this down, I’m excited to welcome today’s speakers. We have Dan Foster, chief financial officer Josh Lupresto, SVP of sales engineering Jason Kaufman, principal solution architect and Sam Nelson, VP of CX and AI. Everyone, welcome. Thank you for joining us today, and I’m going to turn it right over to you.
Alright. Thanks, Cass. Well, first off, I’d like to think I’m the CFO, but I’m and I’m really good with numbers as my team would tell you, but I’m the chief revenue officer. So welcome, everybody.
First off, we wanted to talk about the market. I wanna set the context. Our market continues to grow, and it’s accelerating. Omnia, the analyst firm, said that it will reach six trillion dollars this year, growing at nearly ten percent.
So the growth is moving up too. What’s more important though than the size of the market is how customers are buying. For the past decade, and we see it all the time, customers asked a familiar question. What platform should I buy?
What technology should I buy? Today, that question’s shifting. It’s now moving to outcomes. How do I achieve this business outcome?
I have these KPIs. What can I do to achieve them? Whether that outcome is improving customer experience, maybe reducing cyber risk, enabling that flexible workforce, we’re seeing the modern role of the tech adviser change dramatically. The modern tech adviser isn’t defined by those platforms they sell anymore, but rather by the problems they solve.
So that evolution is what we’re here to talk about today.
What I wanna bring, before I bring in the panel, I wanna do one quick thing. In the chat, drop one word or a short phrase that best describes what your customers are asking for right now.
So think of it. Security, AI, cost optimization, user experience, whatever you’re hearing the most.
Let’s see it.
Let’s see here. What do we got?
We got some helps in there. Just asking for help.
Help? Yeah. This is good. This is good.
I like the ones that say growth and efficiency, like, something that’s, a goal oriented request.
Yeah.
Alright. So let’s alright. I think that’s a good context. So I brought in a lot of brainpower here to help me with this.
So I you know, I’m known for building great teams, but, I gotta have this, the folks that are super smart in the, in the chat with me here. And I got them right on the screen here. So let’s jump into this. Chandler, show, show just that first slide.
Oh, you got it up here. The, let let me just real quickly, we talked about this, the industry inflection point, products to outcomes. We’re seeing that. Our data shows those conversations have shifted quickly, and we see a lot of data.
Last year, we did five thousand interactions with both you and your end user as a tech adviser. Number two, AI is everywhere, but it’s really got uneven impact. It’s moving fast in automation, analytics, CX, but our adoption remains lumpy. I would call it lumpy.
We’re seeing it drive huge value in contact centers, security operations. But a lot of the mid market CIOs, they’re still they’re still identifying where it actually fits. So we’re gonna come to the AI. Now the next point, convergence.
What do I mean by convergence? Look. We all know this. SASE, SD WAN, zero trust.
They aren’t separate conversations anymore. They’re the architecture behind the modern enterprise.
Advisors who understand these intersections are shaping this long term strategy of the modern enterprise architecture.
And then finally, this idea of the rise of managed everything. Think of the MSPs.
Team, I don’t know how many MSPs we have in the portfolio. It’s a lot. But think about what’s happening. End users are are are end users are CIOs, are VP of infrastructures.
They are fatigued by complexity. They want fewer vendors, more accountability, and predictable outcomes. So we’re seeing managed services uptake in areas we never thought before. Sure.
Network observability, endpoint management, CX, but even AI model management. So advisers who translate that complexity is where we’re seeing winning. So let me, let’s let’s back up a bit here. So I kinda gave you the what I think is a pretty interesting landscape in which to be a tech adviser.
Let’s Sam, let’s start out with you, AI AI everywhere. What’s your sense? What are you seeing?
Yeah. So you hit it on the head there, Dan. See, AI is is most prominent in CX right now, and it has been actually for some time.
And so when you say that AI is uneven across the business, you’re totally right there. In fact, right now, kind of global AI in the CX market sits at about fifteen or so billion, but the forecast that as you can imagine is going to skyrocket to about seventy six point seven billion by twenty thirty three. So the growth is there, but I mentioned it on the Tuesday call prior, which was CX is the front door. And you have to realize that AI is completely horizontal, meaning it spans across all of the components of the business.
While CX is the front door, well, what’s behind the door? Right? What’s actually keeping the house up? It’s the foundation.
You’ve got your network. How are you securing the house? Right? And then more importantly, what kind of data do you have living inside?
Because AI is only as good as the data you feed it, and we all know that garbage in is essentially garbage out. So, the conversation is very heavily pivoting outside of CX and more into, I saw it here, a lot of keywords popping up in the chat around improving efficiencies. Right? AI is a great play to improve efficiency across the business and not just within the CX world.
So there’s a lot of opportunity here, and you also mentioned, you know, pivoting to outcomes over SKUs. Folks, that’s the best way to start navigating a lot of these different use cases, another term I saw in the chat here, to determine where exactly you could fit AI in. We’ve kind of pivoted from, hey. Here’s a shiny object to, hey.
What are you looking to achieve? Okay. Now let’s bring in the shiny objects.
You you know, Sam, one one of the elements I’m seeing a lot is cost optimization in the chat. And we saw in the tech trends report last year, they were effectively funding innovation, funding AI through cost cutting, through cost optimization. So about robbing from Peter to pay Paul. And, Jason, you know this. In the colo space, the data center space, what we’re seeing is, hey. Let’s go actually let’s go optimize our workload, and then I can go fund that AI. Any any thoughts on that in terms of cross funding of initiatives?
Yeah. A lot of times, companies are running an overcapacity. So, like, they built a lot of infrastructure, and they’re trying to figure out what applications they need to run, who needs to access it. And what they’ve done is they’ve overbuilt.
So when we come in to do a FinOps consulting engagement, you know, the first thing we wanna look at is you know, obviously, we wanna look at the different connectivity options. See where we could save them there. That’s easy money. But when you’re looking at the infrastructure, a lot of it is saying, hey.
You have these servers that are doing this work, but you’re not leveraging half of the stuff and hardware that you already have. Let’s look at rightsizing that and seeing how much we can actually take that money and leverage it in something to transform another avenue. So as Sam was exactly saying in the AI space, there’s a lot of pressure coming from, you know, down from the c level to the board members all the way down to say, hey. We need to optimize in order to have competitive advantage or we need to, you know, optimize for x.
How are we gonna find that money? And then going into things like colocation and cybersecurity, a a lot of those things, there’s a ton of bloat that a lot of customers have because they went out and they have, hey. We have this one use case. We need to go solve it.
Let’s go get this application. Or, hey. We need to have this these amount of servers in order to hit these applications that now they’ve moved that to the cloud. They don’t need it anymore.
If it’s just sitting there, then they’re paying for it, and they didn’t even know it. Somebody’s just writing the check, and nobody’s actually holding accountable all the things that are going on in the back end. So a lot of that stuff is low hanging fruit that we get in and deep dive and figure out, hey. You could save x amount of money here.
Now let’s leverage that and take you to the next level.
Josh, you you’ve seen AI work internally with a lot of the development we’ve had. There’s there’s, what I would say is some revolutionary stuff happening, but there’s also AI sprawl. So talk to us about both sides of those because I think a lot of it our advisers are sitting there saying, and Sam does a great course on this. How can I use AI to benefit my operation? Sure. I wanna sell it, but how can I use it internally?
Yeah. Definitely. By the way, this is a this is a plug for all of Sam’s events and trainings. If you haven’t been to these, I think they’re fantastic, because it helps with two things.
So I’m gonna I’m gonna get to the AIP. So this kind of at the end. I think we’ve been trained over time to to listen for certain trigger words. Right?
My Internet is slow. We need to move to the cloud. It’s very single threaded, but that’s just that’s how we’ve been. We’ve been very reactive to opportunities.
I think the advisers, what I’m seeing today and all these you know, we talk about all these interactions that we see, they’ve kinda shifted that mindset.
It’s not they they understand that the customer doesn’t have just a connectivity problem or just a security problem or just a data problem in isolation. They have a business problem. So now the problem that we have to get to is is finding what that new problem is. And so now maybe now it’s, hey.
We need to manufacture this widget faster, or we need to reduce customer churn. And so I think the solution, what I’m seeing right now, is that it’s not just one product. It’s a bundled approach. So maybe it’s CX layered with some robust secure connectivity, and then we’ve gotta figure out how we handle that data.
And then it’s then then we get to what they want, which is AI to provide the insights on top of it. So to me, I think the the problem has been converging right before our eyes. Now we’ve just gotta make sure those those solutions match. And so you you you had these first couple years of the run ups with the LLMs where everybody just went out and tried to figure out some tooling.
Right? Everybody’s, you know, entrepreneur by nature. They went to figure it out, and and then we went, uh-oh. That’s a lot of data that could be go leaking out there.
And I think the reality was everybody struggled to kind of productize this early on.
And so we’ve we’ve again, we we talk about this in a lot of the trainings and the events, but, you know, there’s a lot of productization in all these different segments. But you just can’t have one of these conversations about the other. And I think the the best way to get into it, the engineer here loves to reverse engineer it to go, what’s the problem that we’re trying to solve? And then then you just see this wealth of opportunity to go, okay.
We we need to get to this. This solves the problem for seventy, eighty, ninety percent of our users. We’ve gotta back into it by getting the the data’s not in a good place. We have no processes around how we’re gonna continually commit to being able to get the data in a good place and then feed it into the tooling and then train it.
So it’s a very iterative development cycle.
And the spoiler alert here is most customers have no idea how to get through this journey, so we’re helping everybody through this for the first time.
Yeah. And then but but touch on the more pedestrian view of AI sprawl. You know, like, you got people over here using things like Gamma, but then you’ve also got do I go Claude or do I do hot swapping between Gemini and, you know, whatever we’re at five dot two with OpenAI?
So, I mean, you you’re you’re suffering from we all suffer from this. Right? Because you’ve got those innovators out on the edge that are out there with, Cloudbot, and then you’ve got people that are still stuck on three dot o ChatGPT. Right? So how do you think about that just from an administrator’s perspective?
I, you know, I think about we we wanna empower the people, and you wanna empower the people at the businesses to make the decisions closest to knowing you know, the ones that are closest to knowing what they need and and what the what the consumers of that product need. So you you have to step back and go, is there universal tooling that solves this? But but I think foremost, it starts with the way that it makes it to us is we need AI. And then we all laugh and go, for what?
What are you expecting it to do? It is gonna drive your car. Sure. You can buy that.
Great. You you can go buy AI that way. But it’s a step back and go, what are you expecting it to do? And let’s try and flush out the majority of the use cases.
We’re gonna miss some corner cases along the way, but can we can we solve seventy five percent of your use cases for the foreseeable future? And does this platform do that for right now, but also leave you an innovative path to integrate and add in other things and not constrain those people that are trying to run and move fast? And then, of course, get rid of those corner cases of people that are unintentionally leaking data out to an LLM that, you know, feeds into deep secret, something some untrusted model or whatever it may be. That’s the that’s the solve.
Yeah. Yeah. So when we think about when we think about the future of this, Sam, you know, you got this idea of micro agents. I I was listening to a podcast last night, agent swarms.
Josh, you know the one I’m talking about, where they’re talking about the agent swarms. But, I mean, this idea of a micro agent, it goes in and does a very specific task to create productivity, and that’s what we’re seeing some real value near term. We’ve got providers who are out there, LLM Gateway. I mean, so we’re starting to see moving just from CX to your earlier point into real productivity enhancement within the business operation itself.
Right. Yeah. And I was just having a conversation with someone earlier about this, but a great segue from which has predominantly been CX as it pertains to AI is, hey. What else can AI do in the business?
And the quick win is around these micro agents where it’s as simple as, hey. Process this document for me. Or even a little more complex, which is, oh, received this document. Item is missing.
Reach out to this customer to gather information. Let this other person know internally that I’ve gathered the information and that it’s ready to go for an outreach. Right? So it’s as simple as a little workflow like that that could save a lot of time for the business.
And then that way, you know, they can use, you know, the actual humans for more complex tasks, more valuable tasks within the business. So very quickly expanding into that world. But then there’s the next thing, right, Dan, which is, okay. How do I make sure that all of that data is secure in all of those doings, especially when there are no human eyeballs on it?
And someone in the chat pointed it out that quality control is absolutely mandatory. So you have to do that. Right? And then you have another problem, which is, hey.
How come this isn’t going as fast as I want it to? Well, do I have the network, like, up to speed on all this stuff? So you could quickly see how it, like, snowballs, right, into this much bigger project if you approach it right.
So there so there’s data governance issues. Imagine that. Right? Like, I I can’t tell you how many times I get pitched last week at our sales kickoff.
I got pitched multiple times by people saying, hey. If I just get that API if I just get that API into your dataset, then I can do wonderful things. Think about the future of APIs, like a personal API where somebody can effectively take your entire you because you’ve actually architected yourself within that AI infrastructure. They’ve got all your data.
But you said something importantly.
The infrastructure, the the ability to get out on the highway and move fast. I wanna talk about pivoting to one of the areas where we see advisers driving significant revenue is building the highways, building that modern enterprise architecture. So, Jason, I talked about it earlier. You know, you can’t just it’s no longer separate conversations, SD WAN, SASE, ZTNA types of things, and then the requirements all the way through to Cola. What what are you seeing out there from a modern enterprise architecture conversation?
Everything’s getting way more distributed. So a lot of things now is meeting the users where they’re at, a lot of them are using their mobile devices. I usually have it to my right here, so that’s why that’s why I went to reach over there, but it’s actually on this side. But a lot of times, I’m working just from my cell phone, to where I need to access our CRM and to be able to, you know, get the customer data.
I need to access my OneNote where I have all the notes. I need to access email, but that’s wherever I go. So designing something to where I have access to everything that’s gonna make me impactful by the day, same with all the users that are within a business, and then making sure that you’re getting those applications production ready to where they’re always, you know, available, you know, that’s something you have to keep in mind. And then building the roadways in order for make that happen and make it robust, that’s where the modern network is.
It is not just saying, hey. I have these branch offices, and I need to connect this to Azure because that’s where all of our infrastructure is. No. Now you have Azure.
You have SaaS based applications. You have the users that work in the office. You have users that don’t. A lot of companies now are moving to a hundred percent remote workforce.
Now that adds a ton of complexity when designing a network because now you need to put the security up in the cloud area because you don’t have an on premise firewall to worry about. So SASE now is kind of out of the equation. Now you’re looking at things like SSE, the way you you don’t have that on premise firewall. So a lot of times, these conversations start out with, okay.
Where are users accessing from, and what are they accessing? And then how are we gonna make that the most efficient, robust, and secure way? And then that starts that conversation, getting it to goal oriented on, okay. We need to have this great user experience.
We need to make sure that everything’s up when they need it, and you need to make sure that it’s where they need it. And that starts all those conversations on the AI tool sets, all the cybersecurity, and then all the infrastructure.
Oh, you’re muted, Dan.
Victim of the double mute?
The double mute. It happens. It happens a lot.
We don’t talk about it.
It happens. It’s it’s just like that football game this weekend.
It gets all the Bats fans.
So let’s not go there.
By the way, I was asked to comment on the football game this weekend, and the best part of that game was the flyover. It was a wonderful flyover. So if you weren’t paying attention, then, go back and watch the video. One of the best flyovers they have. So as we think about what Jason was talking about with that modern enterprise architecture and the ability to connect to data centers, the ability to connect to data centers has never been more constrained.
The energy. You know, we’re talking about you had dinner last week with an adviser, and they’re selling turbines. I mean, where, Josh, do you see this part of the business and the constrained resource around the data center looking as we build out that modern enterprise architecture.
You know, I when when some of these things originally you know, when when AI and these things came in, you know, I think about twenty twenty three when it really started to get productized, everything sounded so far away. I was like, oh, this is great. This is fun. How can I really put this into practice?
How does it really affect me? Can’t possibly be that fast. You know? And then you get in a car, and it drives itself.
And you go, that works pretty good.
Okay. So these things tend to move a a lot faster than we expect. And I you know, look. I think this country is great at figuring out a way to solve a problem, and there was constraints to your point, obviously, of of all this run up of AI.
Everybody gobbled up all the power, so then we have to figure out what do we do next. Okay? So we’re we’re dramatically underserved from a power generation perspective, so let’s leave it to the entrepreneurs to figure out a way, and and that’s exactly what they did. So I I was reading this.
Do you guys remember the the Concorde? Right? Ultra awesome speeds across the across the water, supersonic flights. You’ve you’ve you’ve been on one of these.
I have. It’s it’s overrated. Hold go like this. Fly that’s that’s a flyover.
Don’t die. Don’t die. Don’t die. Okay. We made it. Great. Those the you know, if you’ve heard of Boom Supersonic, just as an example, this is a company that is just out there producing the next order of, you know, the Concorde replacement.
So they’re making turbines for supersonic jets. Okay. Cool. Cool business model. Very capital intensive. Turns out you gotta make money after a while.
And so then what what do they see? They see a problem in the data center world. So now Boom Supersonic is picking out up orders from data center providers to bring these forty two megawatt modularized supersonic turbines. That’s so many futuristic words.
Supersonic turbines plopped into a data center parking lot, feed it from, you know, gas fed. Right? You know, just natural gas. And look at that.
You get forty two megawatts out of some of these. And so I was reading a there’s a data center provider that’s got forty of these on order. They’re gonna get them in for testing late this year, probably ramp up production starting that’s next year. Right?
So so we’re able to figure out a lot of these capacity constraints. And then past that, of course, the conversation around the touchy subject around SMRs and nuclear.
How do we gonna go there.
You you love your small modulars.
Look. I love safe, clean power that allows us to build the tools and technology that we need to. And I think America will figure out a way. Seems like the turbines are the first way to alleviate some of those power constraints. Pretty cool stuff.
Yeah. And so I see in the chat, you know, one of the questions is, can we sell this? No. What we’re doing constantly is focusing on how do we monetize technology infrastructure.
So if you can’t sell it today, I can assure you that our engineering team, our supplier management team are out there trying to cut new terrain around what we can do in that space. We see that as a limiter. We wanna bring that to you. So that’s a continued focus of ours.
Alright, Josh. I talked about the rise of manage everything. And so maybe this is, you know, jet engines as a service, but let’s actually get a little more specific with stuff you can sell in twenty twenty six, you know, endpoint protection. Obviously, some of the, even AI as a service, you know, the ability to do models as a service.
What what do you see in that m a MSP space? We’ve got so many of them. How do if I’m a tech adviser, how do I approach this managed everything?
I I think you know, it’s interesting. I was on with a a CEO this week, you know, a big manufacturing company. And so you hear manufacturing, and you think, oh, man. There’s gotta be a lot of legacy tech there.
And so it is a it’s an MSP opportunity dream where you go, they’re just gonna need a lot of things. And so we we thought the conversation was gonna be a little bit about, hey. I need to do some I need to figure out how to do AI. What’s the right path for me?
And the more we uncovered, I think what we found is that it opens up an opportunity to step back, step back, step back. Because what did he add? Legacy ERP, ancient ancient Microsoft platform, a s four hundred running the core of the infrastructure, not updated on his Microsoft MDR for his endpoints. And the list kinda goes on and on.
So he had he had this vision of, I want to do I just wanna do a little bit of AI on the front end for some better data, better visualizations, more real time, make better decisions, give my people a little better tooling, and he can’t. He absolutely can’t. He’s he’s one to two years away from modernization to be able to do that in the way that he wants to do it. And so I think the this this idea is I I love it when the end customer really gets to understand all of the things that our advisers can help with.
And so this MSP story just seems to be a a very prescriptive, thing that we’re we’re pulling out of the first aid box time and time and time again because customers, what they’ve gone through, it seems like over and this and this guy talked about this, he’s gone through some trimming on his IT staff. And so he’s gotta do more with less. He’s leaning on outsourcing, and we just hear that message over and over and over again, and this guy was no different. And so I think that’s what a point to recognize what a lot of your customers are going through.
Call that out. What’s the CIO struggling with? How are you dealing with capacity constraints on the team, and how are you leaning into outsourcing? And what’s the problem that you need to solve?
And it might those those two paths tend to converge.
Jason, anything on the m s anything jump out to you in the MSP kind of managed everything space as you look out over twenty twenty six, some new hot topics?
Yeah. One of the problems I’m seeing a lot of customers have is they they went out and bought all these systems. And just like Josh was saying, they have trouble with employee retention or they they opened up because they’re starting to scale, and they’re realizing we need more capacity internally. We need more resources to support this, and they’re having trouble supporting the existing platforms.
So they’re finding it’s it’s harder to find an MSP that could focus on all the platforms that they already have without being invasive and replacing stuff. So they’re open to the conversation on, hey. Let’s look at somebody that you have a great relationship with, an MSP, and then they have their own platforms and something that they can manage effectively and co manage with you guys. So you don’t have to, you know, you don’t have to fire everybody in the IT staff.
We wanna work with them. Like I just had a conversation with somebody. She she actually was a chief data scientist at a large pharmacy company. And what she had was five open recs for data scientists.
And what she was having trouble was with the interview process. She was like, hey. How do you find good good people to come in? Do you guys do staff aug?
Like, yes. We can. But what we what we do have is we have teams that can come in and augment the internal staff that you already have. So looking at outsourcing a lot of the more complex component, the teams that are already readily available and they’re already staffed up, and you don’t have to worry about the whole hiring and firing and HR processes with all that.
You know, let’s augment that team with with a team of resources, and then you could leverage that money that you could use that elsewhere for more strategic task.
And that’s where the conversation is starting is, hey. You know, we’re trying to scale, but we don’t wanna go hire more people. It’s not, hey. We replace the existing people we already have. So the MSP conversation is more of a co management conversation and augmentation rather than, hey. Let’s just completely give our keys to the kingdom elsewhere. So they’re they’re understanding that there’s more flexibility in the MSP conversation than they originally thought.
No. I love that. I love that. So just to wrap here, as we look out, you know, I saw the chat lighting up, Josh, with, you know, turbines and SMR.
We always will be looking out there. So think about it. Quantum computing and the impact on security. Think about robotics as a service.
Chad Muckenfoss is super excited about that. So we are constantly looking out beyond the headlights, but we’ve also gotta say, look. What’s going on today in our enterprise, in our mid market customers? And I would I would say one other angle.
It’s a very different angle to bring in, which is I I sat down with Jay McBain, two weeks ago. And Jay talked about and Josh, you and I talked about this. He talked about be aware that there’s seven different partners at the table sometimes. So if I go back to that challenger so challenger sale, then challenger customer talked about five different constituents from the business.
It turns out, and Jay Jay actually, corrected me. I said, well, we’re kind of a GSI killer. You know, we’re an assassin. We’re category expertise in there taking these very large deals from the likes of Accenture, WWT, Deloitte, you name it.
And he said, but be aware, they’re always at the table. So you gotta figure out how to play nicely. So there’s oftentimes in these large deals, seven different partners in seven different ways that this end user is buying. So that’s that’s number one. But I I wanna leave with this insight, and then we can deal with some of the q and a, which is this idea of the adviser insight. You know, we we’ve analyzed thousands of partner and the differentiation is not who gives the best quote.
It’s those who bring the best insight into the client’s perspective. So this transition from tech platform to outcomes is gonna be critical for you as a tech adviser.
As you go forward in this space, it’s going to be enabled through AI, enabled through that converged network, but it’s really coming down to that adviser edge. Any final comments on that, the adviser edge team?
I look. I I I double down on it’s just a change in how we’ve been trained to have these conversations, right, to to the point of what’s the what’s the weird what’s the weird thing that you’re trying to solve? It’s a very it’s just a very open conversation. Right?
What what what like, I’ve never done improv, but I understand the training in improv is what do you say that’s the next thing that can keep that conversation going? And people wanna talk about the problems that they have. And so now people are just faced with weird and crazy unique problems that they don’t think anybody can solve, and we’re seeing them get solved over and over sometimes with with this front end shiny AI thing. Sometimes it’s you’ve gotta go back and do some of these basics, these database modernizations, secure more endpoints, like, some of these real true basic things.
The the technology is flashy. It’s cool. It’s amazing. It’s it’s it’s Moore’s law, you know, to this crazy curve, but it still comes back to the basics.
There’s a process. They’ve gotta have key components done and modernized, and a lot of people are behind the curve. So just don’t forget that ask those weird questions to understand that exact outcome and see good success.
I always love when we get a an an email from a customer before the before the call, and they’re like, hey. Can you just give me a list of all the different OEMs and the and the people you have access to? Because that’s what they’re used to. They’re just used to somebody giving them the catalog and saying, hey.
Pick what you want. You know? We’ll we’ll set it up or, know, you can buy whatever you want. Because when they get on the call and you start asking that question, hey.
What are your goals? You know? What are what are you guys looking to do? Where are your main problems at?
They don’t expect that, and then you catch them off guard, and they take take a step back, and they’re starting, oh, he wants to have a real conversation about this stuff. And that’s the value of an adviser is because nobody’s really asking them that. Those SIs, they’re just coming in saying, hey. What do you wanna buy?
Here’s what’s on the shelf. But somebody to come in and add those insights and get the strategy and saying, hey. Let me solve your problem, make you look good to everybody else at the company, derisk you, now that is something that’s gonna provide that person value.
Love it. Derisk you. Love that.
Anything else? Thing, guys. Yeah. No. The last thing here, I’m gonna dovetail off what said, but the the great email that I love, emphasis on the love, right, is when someone says, hey.
What suppliers do AI? Like, who are your AI suppliers? I’m like, folks, come on. Back up.
Back up here. Right? I’m not gonna just give you a list of all those. So kind of looping everything together here, folks.
Engage the team. Right? Get to know who does what well, and really get to understand the use cases because if you identify the use cases, then that’s something you can actually work with.
Awesome. Cass, we’re gonna hand it over to you.
Well, thank you all again for a really great conversation, but a very strategic look at kind of where the market is heading for twenty twenty six and how our advisers can talk to their customers and position them in a much better, position for the year. I did see this come up a lot in chat today, so I just kinda wanna also bring this to the everyone’s attention as well. You know, next week, Sumair Riaz is going to join us for a fast, musty section on AI risk. A lot of you were talking about the risk of AI, the security that goes behind having that AI. So if your customers are adopting AI faster than they can control it, make sure that you also tune in next Tuesday for that conversation so you know how to position those conversations with your customers.