Bringing Clarity to AI: What to Know and Where to Start

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Thank you for joining us. I'm Travis Cook, director of Industry Solutions at Connection, and part of our connection Helix Center for Applied AI and Robotics, where I lead partnerships and sales enablement for artificial intelligence. I'm joined today by my friend Jeff Mushkin, VP of Core Engineering at Helix.

Together we're gonna share some insights from our Helix AI practice and how we're working with customers of all shapes and sizes to help them apply AI to solve their business challenges. We'll provide a, a view on some of the lessons learned through our engagement with hundreds of customers over the past couple of years. Jeff, I've been looking forward to this conversation.

Likewise. So, as we begin our, our talk today, what does the Helix team look like at connection? What expertise do we have on staff that our customers can tap into? Great question. So we think of our customers as a lifecycle within the ai, uh, ecosystem, right?

We have mature customers and we have, uh, customers that are really just getting started. So our expertise, uh, really requires a full spectrum of capabilities. And, uh, our ethos within Helix is really a security first approach to ai. So we, we tend to begin with, uh, our team

that handles governance and risk and compliance and safety. Uh, we have a whole team, uh, many of us have spent 20 plus years in cybersecurity. So we have a, a rich depth of capability. Uh, and that's typically where we would, uh, uh, start with our, our internal team.

And then we look at the next phase of a rollout, and that would be the data readiness side of our customers. Uh, that the data hygiene, are they, do they have the right data? Uh, how do we handle the pipelining and the data orchestration? So we have an entire data orchestration capability, uh,

within, uh, the Helix team. And then when we get past, uh, data, we start looking at the infrastructure. Uh, we're thinking on-prem, cloud, uh, private cloud, hybrid cloud, and on-prem. And even for our military customers, we're dealing

with air gapped, uh, for highly sensitive capabilities. So we have an infrastructure team, uh, pull, uh, pull together that really focus heavily on how do we optimize the infrastructure for our customers in the most cost effective way for their needs. Then we look at the software side of this.

Uh, so we have full stack capability, uh, front end, back end, uh, from embedded AI through bespoke solutions that we might be creating internally, all the way through some of our SAS providers, um, that we will probably talk about in this, uh, get together

and holistically. On top of all of that, we, we have a team of advisors and, uh, from consulting all the way through to solution delivery. So we have an entire team, uh, to cover the data, the infrastructure, the software, the hardware, um,

and the bespoke, uh, programming of AI to make it actually do something. And then wrapped around all of that, we have a team of center of excellence, uh, expertise. So in vision, in digital, twinning, co-pilots, rag inferencing, a lot of technologies

that we focus on within, uh, ai, we have teams that are just dedicated to delivering those capabilities to our customers. So I think from a technical expertise, we really have full coverage, uh, from beginning to end of the AI ecosystem.

And, um, I would probably throw back to you the technical talent is required, but we also need a sales capability to have these discussions with our customers. Maybe you can touch on that a little bit. Absolutely. So, you know, we've got hundreds of salespeople here at connection, working closely

with customers all the way from small medium business to to large enterprise, uh, customers in the federal space, as you mentioned. And a couple of years ago, we really started to undertake that effort around upskilling our team. And it's really much the same in some respects, I think any of our customers have to do in educating their teams and,

and upskilling their teams to take advantage of the capabilities that that AI can offer. Um, our sales team needs to be well positioned to help our customers on their journeys, right? To understand what can we do, what capabilities do we have,

what solutions can we offer, what partnerships can we bring to bear? So we've undertaken a pretty close to what's a two year effort and taking a, uh, a a significant number of our sales team members through a, through a really robust program.

So that starts with some foundational training on, um, starting to help the team and become conversant around AI and some of the language of AI and some of those topics that they need to understand. Um, on top of that, we begin to layer, um, a couple of meetings a month, uh, with that team

to bring those partnerships and, and solutions and continue that education process. Uh, and additionally we've got a couple of, of dedicated real immersion days each year. Um, we do this twice, one in the spring and one in the fall where we bring the team, uh, out

in person live for a couple of days of really focused training. So through that process, I think we've learned a lot about the amount of effort involved in the education and the continuous nature of what we have to deliver for our teams to make sure that they're well positioned

to help our customers and, and help them along their journeys. And we, so we continue those, uh, those efforts today. It's interesting because not only do you focus on direct education from a sales standpoint, but do you actually focus on the expertise within very

specific industry segments? Maybe you want to talk about how you break that up and how you look at those segments. That's right. I think that's a critical point, Jeff, because foundational to Helix and the work that we do is the subject matter expertise around the specific vertical markets that we serve.

So we have a robust practice around healthcare, retail, manufacturing. Uh, we're working with financial services customers, higher education, K to 12, federal. Um, as we've mentioned, having the subject matter experts who come from those industries have really been immersed

in those industries. That's a critical, uh, component of our ability to serve our customers because we speak the language, right? We've got the subject matter experts that can speak the language, they understand what those customer challenges are. For example, in manufacturing, our subject matter expert can walk a factory floor

with the customer and really take a look at their operation and offer some best practices, opportunities for improvement. What are some of the, um, low, what's some of the low hanging fruit when it comes to, um, some projects that the customer could undertake to really improve their operation?

Thinking of, uh, our sales people and our industry experts, walking a factory floor is really critical, uh, within artificial intelligence to really understand our customers at a very deep level, uh, which is really the most prominent way to achieve success, because there's a lot of background noise, uh,

with solutioning of artificial intelligence. And how do you begin? Uh, and again, we have beginner customers that are just getting started and really looking for that expertise to avoid a lot of pitfalls. Um, and then we have customers that are really far along in their journey, right?

Absolutely. And that expertise that your team brings to the table really is essential, uh, for the, the collaboration, uh, with, uh, helix. Well, it starts with a common language, right? And having a common language allows you to really have a productive conversation with the customer

and then develop, um, solutions that address the business challenges. With that in mind, um, I know you've been working with a lot of customers. Can you give some examples of some customer engagements and what that process looks like with Helix? Yeah, sure. Um, I think to your point, uh,

bringing expertise to the table, um, matters with regard to rolling out, uh, very particular needs at the individual customer level. And so a good example would be, uh, uh, military, uh, we'll start there and we'll do commercial as well, right? To show the, uh, the capability set, uh, that helix, uh,

brings to our customer base. But, um, we were asked to come down originally, uh, in this particular example, uh, for a three day set of workshops to really get them up to speed on, uh, the latest and greatest in training capabilities and so forth. And, uh, this customer, uh, the goal

of this project was to walk out with maybe five use cases and, uh, and then figure out, uh, following our methodology how to put that into practice infrastructure data, uh, and then solutioning. And we spent three days,

we had 80 people in the room from leadership to very technical t people. We walked out with over 37 use cases in this example. And that led to solutioning of both cloud, uh, capabilities for some of the use cases.

Uh, we had on-prem use cases for some classified activity, and, uh, and then a hybrid on-prem. And then our infrastructure teams came in and, uh, talked to them about the hardware requirements and speced that out to the, uh, uh, the needs of that set

of customer, uh, use cases and turned into a, uh, a very long lasting relationship. And, uh, and so this shows the prowess of going from workshopping and ideation with our customers that are at different skill sets and different capabilities, uh,

straight into our data orchestration team that we talked about earlier, our infrastructure team, and then of course, our solutioning all the way through to delivery, uh, in the retail environment. It one of your verticals that you were just referring to, uh, we were asked to come in, NA nationwide, uh, retailer, uh, asked us to come in and they had a couple of problems.

Um, they had a set of management that was highly nervous, uh, uh, concerned that AI was going to interject in their, their jobs and livelihoods. Um, so were very resistant. Um, and they had a lot of potential use cases, but they weren't really sure.

So we sat in the room, uh, again, uh, started with discovery session, a workshop, and, uh, we had 30 people in the room. Uh, every C level person was in the room, every president of every line of business and the vice presidents below. Um, we walked out of that meeting with, uh,

which turned into a full on strategy session. We walked out with, uh, 40 something use cases, and the CEO had pulled us aside afterwards and said, the managers that we were most concerned and nervous about were the most elated and excited to start participating in getting their use

cases actioned first. And so that's the power of the education and walking through and, and culture shifts that, uh, that actually matter. And so that's a really good use case. And then I think from a research and development standpoint, uh, kind of a third use case, uh, customer, uh, we were, uh, part

of a Navy challenge US Navy, and they were seeking a highly secured framework, uh, for AI usage among the, uh, the naval officers and, uh, and to be used infield, which would require non,

um, cloud capabilities, so on-prem or even air gap for, uh, highly secured applications. And our team went through a competition of sorts, uh, with every major, uh, AI competitor, if you will, to a helix. Uh, we came in first place, uh, we won that.

And the, the interesting part about it is that it resonates with the customers, that the deep levels of capability and expertise combined with a really good understanding of what the customer's pain points are that you were alluding to earlier, having those experts that really understand the

industry segments, um, it, it all coalesces into conclusions. So there, there are really three simple examples, and obviously, uh, as you said, we've been at this for a while and we have hundreds of customers in that pipeline. So we, we have, uh, really good, uh, stories to tell.

And, and the interesting part, Travis, is that really everyone's on a different journey. It's not a set a a fixed journey. And I think that's very important. And, and you alluded to it with our sales folks. They need to understand how the individual customers are

interacting with their particular journey. And, and then we come in and fit nicely and have all those learned experiences so we can work with them as our partner. And so it's really helix working with the customer as one, and that's, that's how we do it from a technical standpoint. And I, and from a sales

standpoint, I know you do that as well. Absolutely. It's a, it's a true partnership. And I know one of the things that we've talked about in the past is this need to balance short term objectives, you know, the need to get some quick wins to demonstrate the effectiveness of some of these solutions versus the longer term,

kinda longer arc of time. Um, how are customers thinking about that? How do we help customers in making some of those determinations? Yeah, interesting question because of it, it's really about a balance, right? And, and different customers have different interest. So we do a lot of listening, of course, uh,

but early customers need wins, that that's really what it comes down to. You have to prove value. Uh, there's a lot of noise in the marketplace and, and people are uncertain, what do I do? How do I do it? So short term, we're looking for, uh, the quick understanding, the quick wins so that we can build buy-in, uh, and,

and create alignment, uh, within the customer itself. That's, that's really, really important. Also, it allows the companies to figure out what actually matters to them. So short term is get in there, get ready to start doing testing and development work. Um, easy examples of short term wins are repetitive tasks,

replacing repetitive tasks, optimizing pro simple processes within the companies, uh, co-pilots with capital C, Microsoft, and lower KC in general, agentic ai. Those are easy short term, uh, ways to engage with a customer and have them start building a sense

of trust in the systems and capabilities within, uh, their teams. Uh, long term, it gets really interesting, uh, long term, we're talking about transformation at a strategic level, uh, where it's includes innovation, right? So most of our customers, like the retail customer I was,

uh, using as one example. We walked out and we started to, uh, we were hired essentially to create the three to five year AI plan and journey for this retailer, uh, and then implement it with them. So, uh, that's, that is a long-term process.

So we're talking about strategic transformation, uh, deep integration of ai, uh, to reshape the culture as it exists within, uh, the corporation today. So how do they leverage AI to create broad success? And, uh, and then what metrics do you tie against that, right? Customer loyalty, perhaps, uh, market share.

Some are looking for cost savings, others are looking for top line growth, right? So we, we learned this along the way, but long term, those are the type of programs you're looking for, where you're touching very specific core company metrics. And then the multi-year strategy

has to be done in the long term. I would not focus on that, uh, short term. Uh, there's a good statistic that, uh, 70 plus percent of AI projects fail, right? And that's, um, primarily when they'll then call Helix, uh, you know, we had a project fail, uh,

you know, can you help us out? And, and typically what you find is they try to grab the long term before they did the first step. And, and so we want to guide them along and, and, and basically help them not, uh, stumble on and fall into those type of pitfalls. So I think with all the work, um,

and from a technical standpoint, you look at it from the strategy of how do we engage our partners? How do you explain the approach of working with those partners, uh, from a hardware side and, and a software side? Yeah, that's a, that's a great question, right?

And it's a complicated one because, um, I think our, what I hear from our customers is that they've been inundated, right? With the marketing from, uh, all of the various partners out there that everything is AI power today, right?

And there's a whole myriad of different solutions that a customer could choose from. What we want to try to do is calm that confusion for customers. Um, and we've done that through, um, a couple of primary ways. One, we work with our foundation partners, some of those top OEM partners.

Uh, we work closely with the likes of Nvidia, Intel, a MD, um, major hardware manufacturers, uh, that we partner very closely with to understand what are they seeing in the market, what solutions, uh, they have on offer that can address some of those customer business challenges. So we try to take a fairly agnostic approach

for our customers, and then apply, apply that to, uh, customer situation where they have certain considerations. Um, there's cost considerations, there's brand affinity, right? There's, uh, AI workloads. And so, um, we help the customer make those determinations about what's appropriate there on top of that.

And there's been really, I mean, you've, I think we've seen this explosion and the, um, ISV or independent software vendor realm, um, with just thousands of, of different, um, software companies that have emerged over the past several years. So we're working very closely, um, with, uh, quite a number

of ISVs, and we're carefully vetting, um, those partnerships on a whole number of different, uh, criteria. Um, but the primary aim that we have there in developing those partnerships is how do we solve the customer business challenge? And, um, you know, can the company that we're partnering

with provides scale, provide support? Um, can they be a good asset to the, to the customer, regardless of the, of the vertical market? In some cases, these are industry specific. Maybe it's a healthcare solution, but, you know, healthcare, retail, manufacturing

and financial services, federal high head, K 12 and beyond, because we have 35,000 customers spanning those markets and, and many more. But we've worked in short, we've worked very carefully, um, to curate a portfolio of partners

that we think can really move the needle for our customers. I think what's exceptional about what you do, Travis, and and your team, is that not only do you work with the partners, but, and I see this when I'm working with, uh, customers, uh, because of that relationship, what we're, what you're doing is allowing Helix to extend

to our customers all that breadth of knowledge coming out of like NVIDIA's engineering teams directly. We have access to all of that capability set, whereas our customers probably wouldn't, uh, they most certainly wouldn't have, uh, the Mindshare. Uh, and that allows us to help our customers solution faster

with best practices, engaging the partners when they are picked and, and having all of the best of breed at every step of the way. And your team does a phenomenal job at con uh, building those relationships, uh, integrating their capabilities with, uh, helix capabilities,

uh, and extending that out to our customers. Yeah, well, it really does, to your point, it, it really does take a team. And, and here at, uh, connection, we've got a very passionate team of folks that work very, very hard to stay abreast of what's going on in the market, to be, you know, talking with our customers, to be talking with our partners. Um, but, you know, our team here,

connection extends to those partners. Um, and our, we have our mutual success, our customer success for a customer that might be just getting started. And we talked about this idea, we kind of covered the whole spectrum from customers that are fairly early in their journeys to customers that are very mature and maybe they've had a practice

around AI for a decade or more. Um, what are a couple of things that our customers should keep in mind if they're earlier on their journey? A couple of nuggets you could offer? Yeah, good question. I I think this actually would apply to both sides of the spectrum, but do not go it alone.

Uh, there's so much failure without the wisdom of having seen projects, uh, stood up and succeed, projects that did not have alignment and failed. So don't go it alone. And, and clearly for all of our customers, uh, coming to Helix is obviously a, a good place, a good grounding

to get started, to go through those discoveries and understand the complexity of the landscape, and then how to, uh, use a company like, uh, helix, uh, to simplify that process, right? So don't go alone, uh, is, is complex. Um, take advantage, uh, of a company like, uh, ours.

And then data readiness, it is underestimated how difficult it is to get AI moving without the right set of data. So you have to have data readiness, and that's why we have teams, uh, just focused on, uh, that particular part. So if you're early stage, uh, you don't want to go alone,

you definitely want to get a, a handle on your data. Your structured and unstructured data planning would probably be the third item that I would bring up. Uh, do you have governance boards in place? Do you have alignment with the business units? Um, do you have alignment from the C level all the way

through to the lines of business to the workers? Do we, do we really understand what the target is that we're going for? Without that alignment, you'll see a lot of failure. It's usually not a technical problem that causes AI to fail. It's almost always an alignment and a miscommunication problem.

And so we like to handle that, uh, head on. So those are probably the, uh, top three. Excellent. Yeah. So To accomplish those three, we need to provide to our customers really a full range and breadth of capabilities. Um, you control the catalog in essence

and how that gets, uh, disseminated to our customer base. You wanna talk about that catalog? Yeah. It's, it's, um, absolutely a, a, a joint effort in putting that catalog together. And you hit upon some of the, some of the, um, solution areas that we can begin to address.

So we've talked about areas like workshops, and that's an, a natural area that we often get started with customers that are maybe a little earlier on. And that could look like use case refinement. It could be our, the possible, right? Helping understand sort of best practices. It could be an infrastructure workshop, right?

There's a whole variety of different workshops that we have available and we are, are, are ready to, um, bring to customers right across kind of a diverse audience. You talked about that line of business coming together with IT leadership and what the value of that for a customer. And, um, and the partnership.

We've also got a, a variety of different assessments. These are largely related to infrastructure, right? Do you have the right infrastructure in place? Do you have the right facility in place? We know that, um, you know, to do, uh, AI well, um, and, and to be able to

support the infrastructure that's needed to run AI workloads. There are some, there are facility considerations, right? There's power cooling, space constraints, the weight of the, of these devices, right? And a whole host of other things that, that, uh, we have the expertise to help you understand your

preparedness, um, to start to, um, uh, to run AI workloads within your facility or within a co-location, uh, facility. We've also got capabilities around, uh, digital twinning. I think, you know, many of our customers will understand that that's, um, uh, of, uh, simulated environment

of virtual, um, twin as it were of a, of a physical environment. Um, so we've got those capabilities and that expertise. We're doing an awful lot of work with customers around computer vision or, or vision ai, right? That's a, um, set of solutions that spans across,

in a very horizontal way, across a lot of different vertical markets. There are literally dozens of use cases as we know, um, uh, that, um, customers can employ us, whether it's, you know, worker safety or defect detection or security. And the list goes on there. You talked to him when we first started our conversation

here around, uh, security and compliance. So we've got a whole practice and, uh, set of experts around security, uh, and compliance, and then gen ai, this idea of AI agents that can take, take action. So there's a couple of sides to primary sides to that.

There's customer experience and then employee experience, and a whole array of use cases across both of those. So that's kind of, those are big buckets, I know, and there's other things that we can do and address for customers, but those are some of the primary ones. What's in interesting about that is from a customer standpoint, we see so much of this

interweaving between them. So a good example, uh, we had a bank customer that originally we were focused on security, compliance, all the typical things you would expect from a regulatory regulated industry. And by the time we were done with that conversation,

it actually turned into a vision use case, uh, for safety and, uh, security of, uh, the facilities, high net worth area, um, for this global, uh, entity. And, uh, so you don't, you never know, right? And so our centers of excellence that you are referring to

and how you've mapped out the product catalog, there's a method to the madness essentially of how this applies to a, a set of customers where it's not so obvious when you get in. Uh, but as you start through this workshop process, which is where you just started, uh, the conversation, uh,

is brilliant because it's a discovery for our customers about what the process could be, should be, and how to follow the methodology that we've created within Helix. Um, but it's also a discovery for us to really understand at a deep level what they're looking for. So it's ideation, of course,

it's worth chopping if they require knowledge, but it's also strategy sessions in general, we find, right? Because that's what leads into how does the company move forward? Um, how do they apply, uh, AI in the most effective way, short term and long term, as you were referring to earlier.

If we can spend maybe just a little bit more time on use cases, because, you know, we've talked about a, a handful of use cases, but maybe a couple of others that, that, you know, you're doing a lot of work with customers. What are some of the primary use cases that you're seeing come up over and over again? Sure. And that is a many hour conversation,

but I think if we, if we were to, um, bubble it to really probably four or five core areas, uh, inferencing in general, the idea of, uh, utilizing knowledge and, uh, creating chatbot capabilities, uh, we see a lot of that. And, and that's a really good starter, uh, position

for companies getting into it. It's also highly matured at this point, if you can say that over, you know, a handful of, uh, you know, four or five, six years. Um, but inferencing, uh, requires literally everything that we've been, uh, talking about from data to, uh, infrastructure, software orchestration, and so and so forth.

It's, it's all of the above. So inferencing, uh, rag, uh, retrieval, augmented, uh, generation is probably next in line. And that's taking the knowledge that our customers have, uh, their specific ip, their data, and building models around that, uh, training models around that.

And, uh, communicating with the large language models and, and small language models, which are now, um, uh, growing in capability and, uh, necessity given compute and power that you're referring, referring to earlier. So we see a lot of rag opportunities and capabilities to solve significant sets

of problems for our customers. Chatbots, we talked about vision, you were just, uh, alluding to it. Vision is probably the most mature, uh, of all, uh, AI related, uh, implementations. And, and there, it's an expanding market. Uh, what vision AI used to be is not where it's headed now,

now it's much more sophisticated and blending, uh, the ability to basically talk to your videos to get intelligence and reconnaissance and analytics out of it. So that, that's an expanding market. And then we have the agent side that you were referring to, we would think in terms of customer experience

and employee experience. Um, so call centers, collection centers, um, interactions with your customer that can be done in an automated way, yet have the same feel as if they're talking to a human. Uh, in some respects, it's a faster set of capabilities,

and the customers are happier, right? They get the job done, uh, at lowers costs. So, uh, lots of benefits, uh, from A-C-X-E-X, uh, standpoint. And then finally, uh, we, we were discussing it just a bit earlier, uh, the agent side as it relates to copilots, uh, there's a lot of activity in

that space led by all the major, uh, brands, uh, out there. So that's, that's what we, uh, I I think if we were looking at how to start attracting, um, activity on the, uh, the early starters, these are the areas where you'll hone in No doubt.

Uh, if I can ask you another question, this companies think about, uh, return on investment, right? Um, so ROI for ai, how do we help customers think about ROI? Yeah. So ROII think you have to take a step back, uh,

because it's maturing in different ways, right? And so it's, uh, what's the, the value, what's the time to value? Uh, and then how do we actually define ROI in general? So maybe we break that out into buckets. We have the traditional ROI, um, dollar spent, dollar saved

or dollar created and so on. And, uh, and, and that has its place, and there are metrics that we would help our customers where through. But probably the more interesting are the, these two subcategories. There's the rocks, ROX return on experience, or return on employee, some would call it.

And this is where really companies should be starting their AI journey. And so what is return on experience? Um, email cell phones, if you didn't offer your customer, your employees, uh, these basic necessities, these basic tools, they

probably wouldn't work for you, right? These are just, they're required. They, you have to have them. They create a tangible set of productivity, but also an intangible, like how much time would you lose if you didn't have tool X ai? And the categories I was talking to earlier about like, uh, programming and training models for chatbots and rag

and so forth, they bring so much productivity, but some of it will live in the intangibles. And so you, you need to think in terms of a return on the experience of your employees. And, uh, the, the main metric would obviously be output, uh, work, product, uh, productivity in general.

And then of course, uh, from a financial aspect, you would get into the ROI side. But then there's this third category that we would wrap up into this return on, and that would be return on the investment into the innovation that they have to take place. That long term model we were talking about earlier, uh,

the return on the future capability set by investing now. And so in almost every industry, you have leaders in AI where they're investing a lot of money and a lot of time to build up the muscle memory, the knowledge, the wisdom. If you're not doing that, you're already

falling behind, right? So there's this category. There has to be a bucket of capital that is allocated for this return on the future. And it's not an if, it's kind of a when at this point, because the market is maturing at such a rapid pace that if you don't start, you're really gonna fall behind.

And it's not a fear or uncertainty doubt kind. It's not a FUD problem. Uh, it's a reality of you have to get that process started. Um, otherwise you, one, you won't know what you're actually not getting a return on because you haven't started. And two, you're then at that point not allowing the company from a culture standpoint

to start maturing into this new economy, uh, this new tool set, um, that provides all of this other return. So that kind of actually is interesting because that culture shift is pretty significant, right? And we've, uh, talked about it with the one retailer as just one example of many.

Um, and now we've just kind of touched on it, uh, with the return on future strategic innovation to create a culture shift. Um, but that leads right into change management, and I know you deal a Lot with that. Yeah, yeah. No doubt. I, if we hear a connection, we are undergoing our own change continually, right?

Just as our industry is changing, um, change management is a, is a, a, a challenge that everyone is, is wrestling with. And, um, to your point earlier about don't go it alone, you know, draw on an experienced partner

who can help you along that journey, help kind of map out how to do that properly. A couple of things. I think that when you look at it, organizations that are getting it right, um, they have a diverse, uh, AI committee. Um, they're having transparent conversations, including

with their employees, um, and they're investing in employees with upskilling, right? Um, and so that consistency of communication, bringing together, um, various stakeholders, um, ensuring that you're communicating what the vision is.

And even if you don't have all the answers, because, you know, I don't, I don't, there aren't many customers who have all the answers today, right? But, um, that cadence of communication, that transparency, again, having that team come together and work together, and then finally, investing in your most valuable resource, your employees, right?

Um, and upskilling them and making sure that they're getting access to the tools that they need to continue to be successful. So those are just a, a, a few nuggets there that I think I would, I would share, but the most important one is the point you made earlier. Um, pick a good partner, you know, someone with the expertise.

We'd like that to be the, you know, connection in our Helix Center for Applied AI and robotics. Um, and we think that, uh, we can help customers, um, along that journey. I agree that connection Helix, uh, our team will work with you to provide the expertise and services that are essential to success

as you tackle your AI projects. If you have questions about AI in areas such as use cases or governance, security, data infrastructure, and you want further information, please contact your connection representative or reach out to us at the Connection Helix Center

for Applied AI and robotics connections AI practice at our website, www.connectionhelix.com. Uh, I'm confident that our full range of capability will help you to achieve success. Thank you, Jeff. Really enjoyed the conversation today.

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