Hey Channel Insiders, welcome back for another episode of Channel Insider Partner POV. Today I am joined by Philip Sellers. He's the Chief Technology Officer at Value Added Reseller and Managed Service Provider Zentelegra. We dive into a wide-ranging conversation largely about AI as most things are these days, but also about what AI brings in terms of both opportunities and challenges for partners and their customers. Along the way we talk specifically about security, guardrails, governance, and also how at the end of the day the AI wave, like most tech waves before it, is really about people and how change management and comfort with new technology and hype cycles all impact how the channel approaches and responds to emerging technologies.
If you're a service provider or reseller interested in knowing how your peers are addressing all of these topics and more, you'll want to stay tuned for my episode. Thanks so much for joining and remember you can find this episode and more at channelinsider.com. Let's get to it. And I am joined now by Philip Sellers, the CTO at Zentelegra. Philip, thank you so much for joining me. >> Oh, thanks for the invitation, Victoria. >> Absolutely. I guess before we kind of dive into the conversation that we'll have today, introduce yourself a little to our audience if you could and then maybe also introduce them a bit to Zentelegra if they're not familiar. >> I'm Philip Sellers.
I'm the CTO here at Zentelegra and I've been with the firm for about 4 years. I've known this firm since, well, really since inception. I worked for one of our first clients who is still a client today over 15 years later and I've known our founder for about the same length of time. I worked most of my career in client-facing roles as a customer buying, running teams, doing operations. And our founder here at Zenegra, Andy Whiteside, enticed me over about 4 years ago.
And it's been a fun ride. For those who don't know Zenegra, our heritage started in the Citrix world, and we've grown into an international reseller and managed service provider combining both under one company to help our clients solve their biggest business challenges. And we focus in the middle market with some of our enterprise customers also following. But we've also got some sister organizations that cater directly to different verticals and small business and other countries.
So, we like to say that we're a global company with a next door feel. >> Well, Philip, with that in mind, we have, I know, many things we can dive into, but maybe we'll start with what customers are expecting from a partner like Zenegra in the market right now. I know we talk a lot about things like AI demand and everything that AI is introducing into companies in terms of what they need support on. But when you think about your customer base and what you're hearing from customers of Zenegra's, where are some of those key focus areas that you're finding conversations returning to? >> In our client set, we're really focused on digital transformation.
And that means something different to every client. Because every client's somewhere different on that continuum. For some of our clients like healthcare companies, it's around accessing their electronic medical records securely and being able to boost productivity in the clinical aspects. For other organizations, it may be around boosting their security posture, you know, implementing zero trust. For other companies, they're looking to boost productivity by adding and augmenting their people staff with AI.
So, we run kind of the full gamut and all of those are relevant [clears throat] to most companies, but then it also depends on your readiness. And so, I think that that's one of the things that we try to do is look at the whole customer, solve the whole problem with a solution, not just throw product at a company, but actually try to make sure that the products work together. And that's where we come in to add value. We're the experts that can make these products work together.
And you know, we take that value add part of value added reseller very seriously. So, while we're doing that from an expertise standpoint, we're also trying to layer in, you know, a lot of other value to our customers world. >> I know we kind of dove right into the the AI of it all, so to speak, as I always say, but this seems like a process and an approach that Zentech has taken with customers since even the the time before AI, which feels a bit foreign now maybe to most people.
But, how has the advent of first generative AI and chatbots and now kind of into the agentic experience that I know a lot of businesses are targeting? How has that evolution impacted how you've approached customers, if it's changed anything at all? >> Well, it definitely has. I think that it brings more customers to the conversation for us. Like a lot of buzzwords in the industry, I remember back when cloud was this amorphous thing and you know, it meant different things different companies and everybody had a cloud strategy, everybody had a cloud play.
That's kind of where we're at today with AI. Everyone's got their version of AI, everyone's got some different take on it and it really comes down to advising our customers around the utility. What can you actually do with it? And so, AI sitting in some of the products that we we resell, like a monitoring product or say a service delivery product, you know, they're going to be able to tap into the data set there in that one product. But what we're also seeing is the real value is correlating that data, making sure that all of the different systems that you do business in can talk to your AI.
And you start to get real value when you can ask it simple questions like, um, "Tell me about the interactions with this particular client." You know, if you're in a customer service or retail role, it's great for recapping, you know, what you've won, what you've lost. Uh, and those are use cases that we use internally. But for clients, you know, there's all sorts of boosting sort of features that we try to show them the art of the possible. And And so, that's not different than what I think what we've done typically.
We try to be advisors, and so we do try to paint that art of the possible. And with AI, I think it's a little vague and different for everyone. So, part of that is just ideation. Let's talk with people. Let's say, "Hey, did you know you could do this?" Or "Hey, we could do that." So, um, we start there and make it more approachable. And And I think that's one of the things that we find success with is now they can grab a hold of something, and then the next idea starts, and the next idea.
And that's how you start to flourish. >> You mentioned in there too the way that Centegra's utilizing AI internally and the lessons you've learned from some of those processes. How important is it for you as a provider to kind of walk the walk as long as, you know, alongside talking the talk to use the the maybe overused metaphor there, but uh, what have you learned in your own adoption of it that you've then started to take to customers? >> It gives me more time in the day, and I think that's the productivity gain that I was looking for.
We all have resource constraints, and for me time is personally one of the most difficult things. I do not have enough time in the day. There's never enough hours to return every email and return every phone call. And there's a lot of things vying for my attention. I'm using it to help me kind of break through the noise and get to the things that need my opinion, my action. And so working with, you know, co-working things in my applications to help me get things done.
It's funny. I've been able to take simple things like, "When can I fit a 30-minute meeting in with this potential person?" And and it goes and it scrapes my calendar and it looks for those time slots and it's kind of simple [snorts] things, I hate to say today, um but they're really effective time savers for me. I'll also note that um it's really good uh for taking content and recreating content. We just spent a week with our sales team and we did a level set where we had created some basic sort of things, almost resemble a 101.
So, we took those slides, we threw it into generative AI, it created a online class for us that we can assign to all new hires. And so, it can take an idea and really take it from idea to something really quickly. The caveat is don't trust it the first time. Generally, you got to tweak it, you got to check it, you know, it's it's not going to be perfect out of the gate. And so, I think that's one of the things we've also learned is that you're going to have to tinker a little bit and people who are naturally interested are people who want to figure out things, they're going to be your power users when it comes to AI because they'll get in and do the work.
First drafts are just that, they're a draft. And so, um whether it's code, whether it's a PowerPoint, draft of a contract or a document. All of those things, you definitely have to still be there. So, I see it as a productivity boost, but I still need to be in the chair and control. >> When you talk to customers, right? And I'm going to ask this because I hear a lot from MSPs and resellers and just peers collectively in the workforce, right? Who go, "My boss said we're all using AI." And sometimes those bosses then have use cases and they have ways that the workflows are going to change and other times it still sounds there's a CEO saying, "We're going to do the AI." And then there's maybe not a plan in place around it.
Are you noticing customers more frequently thinking about those kind of use case pilot projects? What are you sensing in terms of the of maturity curve of AI adoption? >> Yeah, I I think that there is a little bit of a training gap. So, similar to painting the art of the possible, I do think organizations need some sort of a a plan to go in and to evangelize this. If they're going to be spending money for monthly subscriptions, you want to get the most out of it.
So, I do think some sort of an adoption plan is a great idea for organizations. And that can take a lot of different forms. There are formalized kind of computer-based training. It could be tips and trick videos that you do internally and really tune it to your organization. But, the key to me is sharing that information. When you find something that helps you, there needs to be a way to evangelize and share that with other people in the company.
What you don't want to do is create one expert who's great at it and everyone around them still struggles. You want that person to also be sharing. And so, adoption of new technology, I don't think AI is any different than any other adoption of new technology. You know, I went through this transition from Skype for Business to Microsoft Teams. That was right at the beginning of COVID. And so we had this whole training and adoption plan. We were going to do lunch and learns and show it off and show people how to get value from it.
Send out gift cards. Like there's this whole intentional sort of plan. And COVID happened and organically Teams was adopted everywhere and we didn't have to train for it. So sometimes you find magic. But I think having that plan is really important. >> I know we've spent a lot of time talking about the ways that you're taking AI to customers, but you also mentioned earlier as we were talking about Centegra's approach to this that vendors are increasingly embedding AI into their products, whether I think frankly some people feel like they've asked for it or not in some cases, right?
But when you think about the way that, you know, you need to be able to discuss with vendors what their road maps look like, what you're bringing to customers, what customers want from them and vice versa. How has that evolved if it has at all, that relationship between you and the vendor? >> You know, in times of intense change like the AI adoption phase we're in, I think there's a tendency with our vendor partners to race to have an AI play. The ones that I appreciate most have a real usefulness.
They're born out of answering a real problem. And you know, it's taken us a lot of time to really normalize ChatGPT. I think that was the first aha moment for most consumers and and even for business folks. And now we're starting to see our vendors take that and try to make it more approachable for answering or doing their business function, you know, application is just an application of software to solve a problem, right? And we use our applications all day long.
So, it's getting to that solve problem faster. Uh and I think that's that's the key to it. I have to be able to answer my problem. That's the key. And so, if it falls short of that in the product, then we definitely have a problem validating and showing the value to a client. And so, adoption's definitely going to be significantly less. But, you know, I will take our monitoring partners, say LogicMonitor or ControlUp. Both of those platforms have really robust AI plays that tap into all of that metrics and statistics and math underneath the covers that go into the dashboards, normalizing what normal looks like, and, you know, figuring out what anomalies look like, but correlating things together.
Monitoring's a great place because there's so much data there. And so, I'm a huge advocate of using AI in your monitoring platform. But, if you stay in one platform, I think you're going to be very limited. Integration to me is where you find the most value, and that's really what I think we feel as a firm is our place is, once again, helping folks integrate all of these different applications together so that you get maximum value. Uh so, you know, in some ways that that really matches who we've always been, but there's nothing to say you can't use two AIs, right?
We use one for note-taking, and then we use a different one for kind of co-work and things like that. And so, you can integrate those two. Even though this one's got AI, too, you've got AI over here. I think that will increasingly be where the industry goes. You're going to want it plugged into your Salesforce, your ServiceNow, your CRM, Dynamics, maybe your accounting system. And then, the next step is, "Oh my gosh, it's got access to everything.
How do I secure that?" And that's the next step. So, I think the integration story becomes a security story, also. >> I'm glad you you went there. That was going to be kind of my next question is I I front-loaded this conversation, I think, with the benefits and the possibilities and the the opportunities ahead, right, for you and customers here, but there are real concerns and and valid challenges and struggles that that any adopter also needs to to keep in mind.
So, to your point, whether it's security, whether it's governance and compliance, whether it's just getting the things to work the way that people want them and expect them to work, what are some of those, if not roadblocks, things that you have to work through alongside your customers to get these systems to deliver the value that maybe leaders are expecting to see out of them? >> That's a really great question. Uh the the roadblocks typically are going to be people-related, honestly.
Um it's going to be less about technology, in my opinion, because the technology's largely developing, you know, open ways to communicate between AI platforms exist, you know, accessing data, but, you know, the AI that I use on a daily basis, it doesn't have unrestricted access to my applications and to my data. There are guardrails built on to that platform, and understanding how to allow access while making it safe for the company is very important.
I use kind of an old sort of example when we first got Microsoft Search, you know, we turned it on in our environments, and then suddenly these file shares that had read-write access for everyone in the company, all of those documents started showing up in search results, and we started freaking out because, "Oh my gosh, people shouldn't have access to that data. It's got this kind of data in it. And you know, AI exposes that same sort of thing. We did a a lot of work with clients around readiness for Microsoft Copilot and making sure that the data and governance of the data in the Microsoft 365 platform was ready to have AI adoption.
And whether you integrate it with their Copilot or a third-party, the access question is still the same. So users and permissions is really important. And so that becomes probably the bigger technical issue that we have to conquer is making sure that the permissions are are correct. Um but that's also kind of a people problem too because people put things in the wrong place. >> On the note of people, I'll ask you something else kind of along the lines of this conversation that I hear more and more I think from MSPs, from other partners in the space is that AI's automating quite a a good deal of work.
It's unlocking new efficiencies, but people are no less important to maybe the the feeling of the channel and the community aspect of the channel than than people have ever been. How do you think the balance is going to continue to shake out between AI and whether that's the the human in the loop phrasing or what you want people to then be spending their time on if AI is automating some of those more uh basic tasks? >> I I think this is the traditional automation story, right?
You know, we were trying to get time back. We were trying to be smart about our resources. And I think AI will be assistive in that way. Um I do think the human is very important because at the end of the day, who's buying from us? Uh the AI is not buying from us. And so it's still very much a people and relationship business that we find ourselves in the channel. And you know, one of the things that I've observed as a client, as a buyer, uh in you know, relationship with a value-added reseller or an MSP is that typically those are the teams that are my continuity.
You know, my reps at a vendor may change. That may happen often, just kind of the way that the vendors structure their incentives, their quotas, things like that. People tend to move around a lot, and so it's very frustrating as a buyer, as a client, to have that continuity. So we leaned on our reseller for that. And we would follow an account team we had trust and we had the relationship with from company to company. And so for me it's extremely important to have that trust lane, to become that trusted advisor, and then to be very respectful of that.
But at the end of the day, all that I just described is a relationship. So that can't be replaced by AI today. There's an adage, people buy from people they like. And we believe that. We believe this is completely a relationship business still. Until I guess the AIs get their own credit card, which can you imagine an AI buying its own tokens just to keep spending tokens? Like, I mean, Anthropic would be rich, right? So we we still have to have those controls.
We have to have the ability as a human to still sit in the middle. Agent take changes that to some degree. And so you get a lot more autonomy and it starts talking between systems and and solving. So I think placing those smart gates is important so that the human is still there, too, because we've heard examples of entire data sets being lost. And you know, as I talk about security, I always talk about the fact that code is imperfect. This is still very much the same thing.
AI is imperfect. A lot of what we do with rag models is try to get consistency. And so, uh get predictability for systems. And so, across that, as we look at the authentic story, having that repeatability, having consistency becomes imperative if you're going to just turn automatic remediation on in an environment or automatic actions. So, you want to make sure that there's some amount of time of monitoring and trust built up uh before you kind of go into those models.
So, long-winded answer, but hopefully I got to the essence there. >> No, absolutely. I've spent the last 20 minutes picking your brain about AI, but I don't want this to to just feel like an AI conversation. Philip, when you think about either the way that you continue to support customers, new things that you're finding at Integris internally, what beyond just the AI adoption, right, excites you about opportunities ahead as a provider? And what, if anything, do you think maybe we should be talking a bit more about than we currently are? >> For me, it's also really important that that security stay at the forefront.
And the security defense-in-depth is the strategy that we've used for security. And so, that has served us well. And I think that we must have the foresight to look at where the security industry is going. There really does need to be adoption in correlation of the data that you're assessing. If you don't have something that's stitching all of this data together, then you're at a huge disadvantage for spotting some sort of malicious activity in your network.
And, you know, that's been the path we've been on with our security partners. It used to be a point purchase for a SIM, a point purchase for an EDR. Now what you need is a platform. And so I think the security platform is probably the most significant thing a company could invest in in the security space. Each of our vendor partners has kind of that full portfolio. And the more of those components that you adopt and the more that they correlate and work together, the better you're going to be able to defend against the inevitable.
Every company's going to have someone that clicks on a link. Everyone's going to have an engineered attack against our help desk for a password reset. We're we're going to get into those situations and you know, for probably the last decade security professionals have been saying it's not if, it's when. And I think we're at a place today where we see when becoming much much more often. And I think that's a scary thing for all companies. At the end of the day, data is is the crown jewels.
And so that's the other piece of of the puzzle I think that we're still working towards. Data powers AI, data powers decision making, data powers strategy. And so the data story is still incredibly relevant. And then being able to access data across all systems, that becomes a huge enabler for analytical type professionals and executives alike to be able to really manage a business well. >> Well, and within that that vast data conversation too, I know I hear a lot from partners and from their customers who say that organizations in the mid-market and the enterprise all the way down to SMB need a partner to help them with many of these conversations, whether they have internal IT teams or they're fully outsourced.
So, how do you then kind of think through the ways that Zentegra is supporting those various data use cases, and then also the to your point, the security of it all? >> Yeah, I mean, I think it's a universal way that we kind of approach a lot of our conversations, and that is a co-management, right? Coming out of the Citrix space, we probably had some of the Well, I'm going to say we have the best. Let's Let's be honest. I'm going to think that we've got the best, right?
So, we've got the best people in the industry when it comes to Citrix, and so for a company that may have a Citrix administrator, or maybe half of their time is devoted to Citrix, what we want to do is come alongside them and give them an escalation point, and give them the ability to a phone a friend. Um so, in the data space, we're trying to do the same sort of thing. We want to be able to help transform and connect data sources. We want to be able to help our customers to obtain the most value out of that uh data because if you can monetize your data, that's a built-in revenue-generating source.
There may be insights, there may be data that's locked in unstructured formats. If you can access that, standardize it, and then be able to report or make decisions on it, it can guide you towards brand new opportunities. I've seen previous firms and customers alike use data to open up new avenues, uh new product, uh new revenue-generating sources from previously unthought-of sort of places. And so, that's what we want to enable. The path to get there are going to be things like semantic layers, data normalization, uh data lakes.
And so, the data science part of this also comes into play. So, we we work in some of that with some of our partners to try and help people draw insights out of it. Um I think that is a place where we're going to see a huge disruption over the next probably 5 years because of the AI innovation that will come into that space. But, it's sort of a chicken and egg situation, right? We're going to do a lot of work to prepare that so the AI can tap into it and then the AI can help to also transform and draw insights from that data in the future.
So, that's kind of the approach that we're taking today is is just enabling. There's a lot of captive useful data we see for our clients if if they can just get access to it. >> I want to ask to Philip as we begin to kind of wind down our our time together today. I hear a lot and I think we all hear a lot and maybe we're those of us in media partially responsible for this constant everything is changing MSPs need to change, nothing will ever be the same, everybody has to evolve kind of mindset because of of some of the things that we've discussed in this conversation in terms of what AI is changing.
From your perspective, it it sounds like Zintego is doing some things new and different and some things have always been true and probably always will be true. How much of an evolution plan do you think this market moment is for channel partners versus how much do you think kind of fundamental basic best practices still apply? >> So, I'll answer that in two parts. I was at an industry event with an OEM partner a couple months ago and they were talking about resellers who had created AI practices and the trajectory of revenue generated from investments into those versus the trajectory of revenue based on the distributors who had invested in AI programs.
And the distributors are monetizing it really well. While resellers typically are not getting the benefit of those investments. And so I think you know, watching and understanding those trends is important for us as we map our future from a managed services perspective. You know, we we really want to help that customer succeed at the end of the day. And so like you said, everything is changing and nothing is changing all at the same time. You know, the everything is changing I I think is somewhat hype.
It's a hype cycle. But there is a fundamental shift here. And you know, we've we've seen a couple tectonic shifts in the industry. I think AI will normalize and we will just expect it to be a part of our day-to-day just like our smartphone. We see things that come as trends that will be big disruptors. And I do think that there are a number of jobs that may be disrupted. And we may see certain professions either diminish or maybe disappear. And so there should be some concern around that.
But uh you know, if you're also the person who's able to create and learn to administer those same platforms, it becomes an opportunity for some. And so I think the cycle continues that as we change and as things evolve, new opportunities will present. You know, we we talk about things with high schoolers and you're going to be working in job that doesn't exist today. And for a certain percentage of the population, that's going to be true. I hate [clears throat] to go into the fear factor.
You know, some of the larger tech minds kind of talk about how AI is going to take away jobs and things like that. And and I think it will be partially true, but I do think at least for the next few decades it's a little overstated. And that could be a bad assumption, but I believe in people at the end of the day. And so I do think that the human factor is an important part of doing business in a whole. So, you know, things may shift, but we've seen those shifts all throughout history.
And so I don't think this is necessarily as big of a shift as some might play it up to be today. I just think that sort of like the invention of the cotton gin changed the way fabrics and manufacturing happened. I think this is our cotton gin. And so it's going to enable us to do a whole host of new things and augment our lives and maybe ramp up productivity in the same way that we saw during the Industrial Revolution. So, that's my take on this.
And I'm just hopeful at this point. That that's kind of where I stand. >> Sure. Well, I think that's a great place to stand and maybe also a great place to end today. So, Philip, thank you so much again for joining me for this episode. If this has piqued somebody's interest in learning a bit more about Zintegra, where would you point them? >> Well, our website's www.zintegra.com and that's xentegra. Go there. And if you want to get in touch with anyone, you can reach out to info@zintegra.com and it'll get routed to the appropriate people. >> Perfect.
And as always, if you want to hear more about the industry, you can also head to channelinsider.com. But thank you, Philip, again for this episode. >> Thank you, Victoria. I enjoyed it. >> >> Woo!
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