Preparing for AI: A Large MSP Shares Their Methodology | EP177

(upbeat music) - What's up, man? Hey, how are you? Did you know that I'm a lord? Did you buy one of those little plots of land in Scotland? - Well, my mother-in-law bought it for me years ago and the only reason I'm bringing this up now, 'cause it's been a while, was that in my team Slack earlier today, 'cause I had a call with a client who was in England and so one of my team members are like, are you Lord BinFace? And I was like, I don't know what that is, but I am actually a lord and then I had to go find my paper. I do own a plot of land in North Ireland, plot number, M55, 96, 46, and therefore I have a lordship. I am Lord Justin Asgard. (laughing) - And I will forever be known as that. I'm changing my LinkedIn profile. I should have done that a while ago. - You know, I'm sorry. That sounds like your dungeon crawler carol name. - I have no idea what your reference is. - No, but the rest of the audience will, so. I feel offended in a little bit getting there, right? 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It's great security with great support, designed to help MSPs grow their business. Learn more at Blumera.com. That's B-L-U-M-I-R-A.com. - What's up, everybody? Welcome to the All Things MSP Podcast. I'm your host, Justin Asgard with me. Always with my podcast producer who unsubscribe from his beard to now he's running beard light. Mr. Eric Anthony. - Hi. - Is that like, blood light? - No, no, no, no, no, no. Like instead of playing for beard plus, you know how beard light. - Okay, that's fine 'cause I just can't do blood light. - Okay. - Yeah, you learn something new every day here at the show folks. - I know, and always interesting stuff, right? - I would love for anyone to just send Eric like a 30 rack of blood light after this episode but like, haha, if you laugh. - And I know exactly who I'd give it to. - Yeah, look, it's been one of those weeks, right? And we talked about maturity last week, so we don't have to be as mature this week. Is that the way this goes? - I'm down with it, I don't have that idea. You know what that means for you guys to bottle episode. - No, no. - Yeah, it's been a week. - I think this one is pretty neat. Not often do we get to interview large MSPs and I'm sure that if you've been in this long enough, you've heard of logically, there are large MSP, really more of an MSSP, and I got to sit down at Chanukon with MJ Patton, who is not only the CMO of logically, but she also sits on the data council at GTIA, and so had a lot of interesting things to say about how logically has implemented AI, not only for their clients, but also for themselves. - All right, so take a listen to that right now. Hey, there are all things MSP, welcome back to another session here from GTIA ChannelCon in San Diego. I have with me MJ Patton, from logically, they are a large-scale national managed security service provider, and she is the CMO. And we've known each other for a long time. We've done a lot of things here with GTIA back when it was CompTIA, and now she serves on the data council. So this is going to be an interesting conversation, because not only are we going to talk about AI, and kind of what MSPs need to think about as a framework, but because she's on the data council, we're going to kind of cover that data piece as well, because the data leakage problem with AI, I think is significant. - Yeah, thank you for having me. - Yeah, no problem. So how long have you been in logically? - I am coming up on four years. - Okay, I know it's been a while. How is logically doing? - Well, great, great, we're continuing to innovate. It's actually one of the things that I love about logically is that we have a very innovative culture. We have our own R&D department. So we test all solutions. We are always looking at what is going to create value for our customers, and then we implement those solutions and everything. So it's been fun. It's been an exciting four years. And it's just the beginning. Right now, we're on a verge of, you know, this whole new kind of like arrow with AI. - Right, right. And you guys are big enough you have your own event coming up, right? - Yes, so we have logic on that is our end user conference, heavily focused on value creation, education, there's no pitching, no, like, you know, everything is about addressing challenges for SMB, IT, and cyberleaders. So we go into the business impact, but then we also go into the technology impacts as well. - Okay. So AI, obviously the big conversation here at this show at most of the shows that are going on right now, because it is rapidly changing the landscape for MSPs and MSSPs, how has logically internally approached AI? - We are, I don't want to say that we're like AI first, but we are AI first. And it really came from leadership and was pushed down. Josh, our CEO, he jumped on board and said, "Hey, this is how we as an organization need to evolve. "We need to embrace AI." We also took the approach of AI and this is contrary to a lot of other organizations where they thought of it as like efficiency gains and hey, how do we improve, you know, our profitability and then cut people like we did not take that approach. We took it as like how do we leverage AI to amplify what we are doing and grow with it? And a part of that was also helping with our internal culture of that change management, right? Because AI for some people, it's scary. Are they going to essentially possibly build a tool that is going to replace them, right? And what we wanted to do is explain, this is making sure that you can focus on the relationships. On things that humans are really good at, not the task that we are now so overburdened with, right? And that is an interesting concept to me in this situation because it's not really new. We've gone through this with technology with automation and we thought people were going to get replaced by it. And that's not the key play here, the key play is to take the people you've got. And like you said, put them on the things that only humans can do to amplify and grow the business rather than cut because cutting never gets you that much growth. - Yeah. - It can get you some profitability. Typically it's short term. Growth is what's going to get you long term health for a business. And you're seeing a lot of these technology companies where they pivoted to this motion, cut a bunch of people, implement an AI and then they're like, oh crap, I have to hire all these people back. And it's a serious thing. So in my department, for example, it was really working with my team and trying to have them reimagine what their role really means. Like instead of you're the one who's doing the task, you're the orchestrator, right? And how do we make sure that you are focused on the strategy, focused on the systems, focused on enablement across the organization rather than you have to be the thing that pushes the button or you know writes the thing or whatnot, right? But it was a scary transition. We're still going through it. But it's exciting to see how we've been applying it internally and by applying it internally. Then when we brought it to market and we're selling AI to our customers, like we breathe it, like we know the challenges. We've run into the hiccups, right? And because of that, then we're very proactive on, well, you now need this type of solution. You need an AI policy, you need training and enablement. We ended up partnering with TechSkills Academy last year in order to provide AI training to customers because we knew this was an issue. Like just to have AI in your workplace, that's not enough. You have to help enable. the adoption of it. >> That's an interesting concept because I think that a lot of MSPs are not set up for training. >> Right. >> Maybe some enablement, some light enablement but not really training. So partnering with a training organization I think could really help the average MSP as well as a large MSSP like logically to do the groundwork for preparing their customers for AI. >> Yeah, I want to say this, I think we have a really great opportunity but everyone has to understand it is okay that you can't do all of the things. >> Correct. >> Right? And instead, think of like, okay, if the customer needs X, could we deliver that internally? Or could we find a partner that does that really well where we still create that value for the customer? Because as long as we're creating that value for the customer, it really doesn't matter who's like delivering it. You want to find a really great partner and make sure that you're solving that like the business challenge for your customer, right? And that's the approach we've taken when it comes to these solutions, instead of thinking like we have to deliver this and then, oh, do we have to hire headgown in order to train and that's not our specialty, right? >> So there's been a theme because I've talked to several MSPs over the course of this week about kind of getting prepared and building a framework and patching, but packaging AI. And there seems to be very much a focus on that AI preparation piece, which is enablement. It is policies in place. So what other kinds of things in that kind of prep phase do you think make a difference for your clients? >> Yeah, so everyone is starting to use AI, right? It's on our phones, it's personal laptops, all of it, right? And so I think the first thing is working with clients showcasing, hey, you're actually really exposed. And do you know what your employees are putting into these tools? Is it supposed to be there? And so we usually start with a shadow AI assessment. We try to, we scan the environment and we're like, hey, look, we're already seeing this. And it's probably even worse because if it's on their cell phones, you can't track that. >> Right, you can't track that, so you need to have a plan in place. So then this ends up leading into, okay, we need to have policy documentation. We have to roll that out internally. And also understand, people are going to use it, so then you don't want to be so stringent that people are trying to go around it, right? Because that's, that's behavior, right? And that people will do that. So then it's a conversation of, okay, well, you know people are going to want to use it. Then what is the best way for you to enable your team to use AI in a very secure way, right? And so we started out with doing Microsoft Copilot. That was our first way of entering the AI space. And then from there, now we have what we call Logic AI, which is built on hats. >> Okay. >> So that way we have a secure tenant, right? >> Yep. >> That can be managed. And then the other piece was the training component, right? And making sure that we have an arm that can deliver that like department-specific, function-specific training in order to see adoption increase. The other thing in relation to it is we realize that unless you have like true ownership around AI, things don't move along, and then you don't see the value of that solution. So when we engage with a customer, it is really hand-holding them. Like this is AI transformation, right? >> Right. >> And you have to treat that. You have to do change management. And I think the MSPs that are really going to succeed in this are going to have to learn change management skills. >> Yeah. And some of them do. In fact, you know, if you have an IT guy that comes from a very formal, large IT space, change management is second nature because they've had to do it for their career. So many MSPs that have not come from that experience who have, I don't want to use the word homegrown, but, you know, they haven't worked in a large organization. They come from a smaller organization where change management wasn't as critical as it is in a large organization. And so you're right, they may not have those skills. And I see that as a definite hindrance because it is a transformation, a disruption. And so you're taking something that exists and making something new. You need to know what it took to get from A to B so that if you need to fix something you can go back. >> Yeah. Change management, it's not just like, hey, we're putting in a tech and then that's it. Like, that's it, right? It is constant communication. >> Yeah. It's an ongoing thing. >> It's ongoing. It's a level of accountability that you have to be driving, right? And checking in, like, where are we? Well, like, you know, resetting expectations and showing the value and it's just constant, like repeatable communications in order to make sure that this actually happens. And I know that that is going to be stretching some individuals, but, you know. >> Well, because so many MSPs, even though I would say over the last five years we've really talked to them about focusing on business outcomes. And it takes the same kind of skills a little bit to go after business outcomes and track that progress with the constant communication and things, like you mentioned, to move people forward on business outcomes rather than just technology. >> Yeah, that's 100%. And we're seeing, like, everyone, I mean, we've been talking about business outcomes for quite a while, you know. But I think this is really causing, like, you have to adopt this. Like, there's no question. >> Right. >> Yeah, exactly. I've got to mention, like, the data piece is a huge component of that, right? So sitting on the Data Advisory Council, this is year three for me. I always love data. I always geek out about data. Like, you know, I don't know what it is, but it's just a thing about myself. Well, I don't think there was urgency behind data. I think it was kind of a nice to have, like, oh, I'll do it when I have time. You know, but no one really thought about it significantly. >> Right. >> And now that we're in this, like, era of AI, it's coming up, the AI's only as good as your data. >> Right. >> Right. And you've seen all those memes where it's like, why is the AI now functioning? Oh, it's this guy's file from 2008, like, without data information, right? So I'm seeing a lot more demand for data services, making sure you're configuring it properly, that you're securing it properly, archiving anything that is going to ingest, like, bad data into these systems. So I think there's going to be a very large demand there. And then the AI piece. But MSPs need to think about how are they addressing that internally for themselves, you know, so that way they know what their customer is going to be going through. Yeah, and I think that's a really good point, just like you guys did it logically, you adopted it first. You did all the learning before you started talking to clients about it. >> Yeah, it's, you have to be eating your own dog food. >> Yeah. >> Right? >> Yeah, you have, in this space where things change so much, if you're not using it, it could, you may learn a new technology, but if you're not using it in-house, then it will change by the next time you need to support it. And there's, again, change management, kind of, if you have the right change management rules in place, so that, in this case, it would be, you know, if it's not something you use in-house, you would make sure that your technicians are going to training on it on a consistent basis to stay up to date. >> I think of it this way, when you do it yourself, what a great opportunity for you to just identify, hey, like, all of the challenges that come out of it, and then you take that, you package it up because probably your customers will have exactly the same issues. >> Yeah, exactly. >> So, like, during that process, just notating, oh, well, this failed, we should probably, and like, that happened to us, when we rolled it out internally with Copilot, we didn't have training, and so, what happened, you know, adoption, right? And so, we had to completely, but that is the reason why we have now, like, a training partner, right? So what a great opportunity to test this on yourself before you do anything for a customer. I also imagine that you almost probably have a gap in adoption, because you have some people who are going to gravitate it passionately, and then some that are going to drag their feet, especially without the training that you talked about. So, yeah, I definitely see that happening, and obviously, in order to be as efficient as possible an organization. needs to be kind of consistent in their AI usage. >> Yeah. Yeah, for sure. >> Now, we said we were going to talk about the data side of it too. And we've touched on it a little bit. But in terms of the Data Advisory Council, what are you guys, what are the main topics that you guys are talking about when it comes to AI and data? >> Sure. So, you know, it's interesting because data really is the foundation of many things. And there's a lot of crossover with many of the other councils. And so we happen to be the, I would say a very collaborative council. So we're working on several initiatives. One with the Cybersecurity and AI council, we're trying to put together resourcing and then provide our guidance of, here's how you should be prepping data and configuring it, et cetera, like all of the data implications that you should be aware of from a resource standpoint. We're also working with AI council in order to kind of put together overall playbooks. Like this is how you should be configuring your data in order to prep it for AI implementation to be successful. We are also working on how do you essentially productize data as well, and deliver those services to your clients. So there's multiple ways that we're trying to create value for ITSPs, around data, because there's an educational component, but we also want to provide actionable toolkits that they could use as they're leveraging internally and then with their customers. >> So I imagine part of the problem is that AI has sped everything up to the point where there's less eyes on the data before AI has a chance to actually grab it and try and use it. And it's probably really relevant in two places. Number one, it's old legacy data that has never been cleaned or is outdated. It's also the processes of getting new data into your data sets. How are you recommending that MSPs address both the cleanup of old data as well as the refining or processing of the ingestion of data to make sure it's clean as soon as it comes into the system? >> Well, it really starts with understanding where do you have data. That's what we recommend, that's number one. Find out all of your different data sources because it's not just data that you might have in your SharePoint, right? It's all of the tools that you have. It's how do you then reconcile that data so it speaks the same thing. This reminds me of a debate that we had, let's see, like three years ago, in relation of how do you make sure that the data correlates to each other from all of these different databases, right? And we had some people who are like, you can't do it, there's no way to do it. And it's like, there has to be a way. You can assign a unique identifier that goes across every single customer information that you have in order to connect it all together. But then you have to start thinking about, okay, where do you house that data and then how do you protect that, all of those components? Number one step, though, is figuring out where is the data. And then it is labeling and configuring it properly. >> Okay, I imagine it also might help, especially in a smaller organization, a larger organization, this would be hard. But in a smaller organization, to make sure that you have one source of truth data set. >> Yes, yeah. And so for example, when it comes to our customer data, Salesforce is our source of truth. And then it is connected to every other system and integrated in there. So that way we're pulling off of the same data sets. So everything ends up mirroring. That was a really large project for us. It took a very long time to fully set it up, integrate all of the different systems. We had to build some specific type of integrations, because not every system spoke really well with Salesforce. But it empowered us to then pull much more impactful reporting, right? It made sure that we all could see the same type of information about what's happening with the customer. What are we planning for the customer? It enabled us to connect all of the teammates that all touched that customer as well, right? But I think a lot of organizations, they don't have that, right? It's everything is in pockets. And it's like, well, your data here says this. Well, I went into this system and it says that over there. Well, how do you pull that? Are you looking at the same, you know? >> Yeah. >> And you have to have that source of truth to reconcile the other data. >> Yes. >> And otherwise, with siloed data, you're going to get a malfunction in the AI, because it's not going to know what to do with two conflicting pieces of data, or it's going to guess and be confidently wrong. >> Exactly. >> Yeah. Well, MJ, this has been a great conversation. I really do appreciate it. It's a view that we haven't seen yet from some of the MSPs that we've interviewed here at GTIA ChannelCon. And it's been really helpful to see it from almost an enterprise level. >> I appreciate you having me, Eric. >> Thanks so much. >> Thanks. >> And we're back. It's weird how we do these. >> Oh, no, it is. >> So weird. But I was going to understand how television is based. >> No, let's not bore them with that. We bore them with way more important things. >> Yeah, there's a couple of things, like MJ said, you got to eat your own dog food. And that is so true in this industry. Like so many MSPs I know have no problem selling services or tools, AI, like whatever, and they're not using it themselves. And they're not implementing it on their own equipment or anything like that. And so it makes your life so much harder when you don't do that. >> I have lived by the eat your own dog food, which is why, by the way, for the record, I don't make dog food. >> You know, I think it's interesting that that theme of eating your own dog food has kind of run through all of the interviews that I did at ChannelCon on this subject, right? So the MSPs are actually recognizing that this is something new that they need to get their head around before they can start talking to clients about it. >> Yeah, and I think the bigger problem is that because we're still in that bubble in AI where, you know, every day it's something new. Like I got an email from Claude every day with like, or anthropic, with like new features. And I'm like, I haven't even figured out the features of yesterday yet. Like they update Claude more often than Google Chrome updates. It's hard to stay on top of it. But like if you can get 75, 80% of that grass done so that way you can then talk to your customers about it and understand the differences between AI's and how to use them properly and how do you, you know, what's it built into their tenant if you're going to use Copilot or Gemini versus Claude or ChatGbT. You have to be in it. I actually just recently gave everyone on my team, we moved everybody to Claude, and we've like tapped Claude into our systems. Like now everybody's got Claude. Like I want you to learn Claude because I think that Claude is going to be the one that we want to sell to our customers and it makes sense for the customer base that we have currently, right? So like, be in there, understand how these tools are talking to one another. It's one thing to understand the alphabet soup, but it's another thing to understand what does it mean from a compliance standpoint? What does it mean from an integration standpoint? What does it mean from a data standpoint when you're integrating or when you're selling AI integrations to customers? So I think it was a great episode. Good job. Good job, man. I'm sorry, I wasn't there. Next time. Next time. Well, you can listen next time by checking out facebook.hunt.com/groups-allthingsmsp. Check us out on our YouTube highdeaf-glory-youtube.com/atallthingsmsp. If you comment on this post, what is strangely similar to another post, Eric, I'll send you a sticker. Like, subscribe, ring the bell. You know what to do, which is send Eric a case of Bud Light. That's Eric. I'm Justin. Bye! Thank you for listening or watching the All Things MSP podcast. If you liked this episode, go ahead and give us a thumbs up. Hit that like button and consider subscribing to catch all our weekly episodes. And from your host to extraordinaire, Justin Escar and myself, Eric Anthony, your humble producer and All Things MSP founder, thank you very much for spending your time with us. 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