In this episode, you’ll learn:
How AI and automation can boost efficiency and profitability in your MSP.
Practical examples of AI applications, from sentiment analysis to multilingual support.
The benefits of leveraging your PSA data to improve ticket resolution and onboarding processes.
Listen on Spotify or Apple Podcasts
Connect with Mark Pennington on LinkedIn by clicking here – https://www.linkedin.com/in/mrpennington/
Connect with Daniel Welling on LinkedIn by clicking here – https://www.linkedin.com/in/daniel-welling-54659715/
Connect with Adam Morris on LinkedIn by clicking here – linkedin.com/in/adamcmorris
Visit The MSP Finance Team website, simply click here – https://www.mspfinanceteam.com/
We look forward to catching up with you on the next one. Stay tuned!
We created It’s a Numbers Game Podcast to help MSP owners learn and understand how to build and maintain a financially healthy MSP business. In this podcast series, MSP business owners like you will learn the fundamental steps, the tips and tricks, the dos and don’ts to achieve MSP financial growth.
Transcript;
Adam: So Mark, Dan and I have just been talking about how kind of neither of us really know anything about automation in the MSP industry. so we’re really looking for you here to, to enlighten us and indeed our audience. So I suppose, perhaps a good start here is to explain what automation means for MSPs. And, perhaps you could just give some examples so that, you know, both of us and the audience can, Really try to, to get to grips with this.
Mark: I think, Yeah, automation is a bit of a catch all term, really, and it’s got, there’s a load, there’s many facets to it, and I think historically within the MSP space, certainly for the last however many years, quite a few years, automation has been, really key to drive, efficiencies, profitability within an MSP and obviously leveraging tools to really achieve that, and, you know, and traditionally the, The automation tends to be a set of tools which you can then configure and get it to carry out repetitive tasks.
Mark: some examples could be within your PSA, you might build some workflows just so you’re handing tickets, you know, just to give a really basic example, you’re contacting a client, and, you need some information from them. You might put a workflow to basically chase that client. Once or twice to save your engineers doing it as a really basic form of automation.
Mark: And then you go as far as, you know, your arm and your monitoring and management tools, configuring that just to help automate that. And that’s historically what the MSP has been using for quite a few years. And which is great and really driven a lot of efficiencies within those spaces.
Mark: with AI and the emergence of that technology and the ability for us to actually start leveraging it,within our space, it’s the accessibility, which has really made it hugely powerful. It’s now, instead of just having those,those tools that you can, streamline repetitive, tasks, you can actually start leveraging AI, to really start doing more complex cognitive.
Mark: Tasks that require multiple steps or processing and understanding, what’s actually happening, build context and provide valuable outputs. And we’re still at the, we’re still at the very early stages of this. but yeah,the power of hyper automation is the terms being coined is huge.
Mark: And that’s something that we’ve been playing about with.
Adam: so this kind of makes sense. And in my MSP, I guess we started to grapple with some of those workflow components.but now we’re in the area era where we’ve got AI, which can take that up another level and start, if I understand it correctly, to, replace some of the activities that. so perhaps you could just bring that to life a bit more again, with some examples, some real kind of life examples,of how this works.
Mark: Yeah. so again, some of the things that you possibly can do, some of the things that we’ve been playing about, as an example, some of the hyper automation is, you know, that ability to really drill into the data that you have within your data repositories, your PSA could be a documentation, it could be lots of different, places where you store data and actually the ability to Yeah.
Mark: Leverage that data is really limited. It has been limited because a lot of the time the data is just unstructured. It’s unfiltered. So you put data into it. We’re all as MSP owners plowing tens, hundreds of thousands of pounds of engineering time, putting data into systems. That we never really pull out.
Mark: and that’s where the, that’s where AI is able to really help in, in, in one example is where we’re starting to really start pulling on that data. We can structure that data, understand it, and then present the information back, in various forms, just so that the. You’re not losing that knowledge. You know, we’ve all had those instances.
Mark: We’ve had those engineers that have had too much knowledge in their heads to be able to actually leave the organization. And you’re in that really tricky situation where someone leaves and then do you pay them more? Yeah, what’s happening there? Whereas what, where actually their knowledge, their information is actually within your system.
Mark: So you can start using AI to really drill into your data, understand it and present it back in a way that is really simple and valuable to the. To new engineers that are coming on board just so they can get up to speed quickly. So there’s a huge amount of, there’s huge amounts more things that you can do with it.
Mark: So again, sentiment scores, you can translate things automatically if you’re working in multilingual locations. You know, there is, there’s a huge amount of potential, and we’re literally just scratching the surface at the moment.
Adam: So I think you’ve mentioned three things there. Let’s just pick them off, actually, and just dig a little bit deeper. So I made a note of, new engineers on boardings, expanding skill sets, sentiment scores, I grabbed. What was the third one?
Mark: The third one, what did I say? Oh, language, you know, being able to translate, translation and things like that.
Adam: Okay. So talk me through the sentiment score example.
Mark: So with the sentiment score, it’s all about, or how we see it. It’s all about managing to do exceptions. you know, the, With the AI, it’s able to take a gauge of how it can understand how the user might be feeling or even the engineer, I suppose, from that perspective and really gauge how a ticket progresses and whether actually the user that’s interacting with you is happy or unhappy about certain things.
Mark: So if you’re seeing a ticket that’s, maybe Going off piste, take it a bit longer than, you’d want it to do. It can really start highlighting the sentiment, the feeling behind that ticket and really highlight it to people ahead of time. so you can actually, before the user, really becomes upset, you can catch it.
Mark: and escalate it to the right people and maybe do something differently to make sure that you actually solve that and really start driving that really good customer service. So that’s just one example of how you could leverage
Adam: Is that something that you’d expect the engineer to be able to do anyway? And
Mark: you would hope so. I mean, engineers are, you know, you know, if you could get, engineers, equal customer service and equal tech, and that’s. To me, a good blend, all engineers are the same plus emails are tricky. Yo email, text communication is a tricky, medium to really pick up, sentiments and tone in.
Mark: so again, it’s only best guessing and a guide.
Adam: and I guess to some extent it’s,it’s a tool, not a replacement.
Mark: no, it’s all about what are we trying to achieve as MSP owners and ultimately what do the customers want? They want. They want their tickets sold quickly. They want to fix first time. It doesn’t come back and they want empathy. Yeah. They pay us to do a service because they can’t do it themselves and they can’t do it themselves is they’ve got varying degrees of IT knowledge, or maybe that’s scale that they can’t do it.
Mark: Yeah. It’s that sort of thing. So it’s just making sure that we understand we’re in a customer service industry. And we have to provide really good customer service. So we can leverage AI to really highlight those bits where customer service might be falling down for various reasons and catch it earlier and try and correct the correct that path.
Adam: Yeah. No, it makes sense. so talk me through how this helps with new engineers.
Mark: so yeah, so just to give you, yeah, to probably lean more on the, the pulling the data out of your current PSAs, example. so some of the things that we’re. Working on is, as I mentioned, there’s a significant amount of investment of time and money put into data, putting data into PSAs.
Mark: And if you know, if a ticket comes up for fixing a problem, I can probably guarantee you fixed it a hundred thousand times already. And it’s in the system, but guess what? We. Google it again to figure out how to fix that thing again. so what we’ve, started doing is, is presenting, relevant ticket information to the engineers at the point where they’re opening the ticket.
Mark: And the idea being with that assumption that you’ve already fixed something, probably a hundred times, as I said before, why not actually just leverage the data that’s already there, and present that to the engineer at the point of needing it. So it can pull in all the information about what the ticket is at the moment.
Mark: It can guess, it can take a guess, guess. best guess at, the, what you’re trying to do, what the user wants, and it can then search your PSA to pull out all the relevant tickets that it thinks scores it, you know, ranks it based upon how relevant it thinks it is. And it can also automatically summarize a solution. And present that solution to the engineer at the first point of just simply opening up the ticket. And that’s the solution presented from your previous fixes. So that’s what we are trying to achieve with the solution that we’ve put in. And again, the idea being that. Knowledge, you know, experience, an experienced engineer who knows the customer and knows the infrastructure is obviously it’s difficult to replace.
Mark: and, you know, what we’re doing isn’t necessarily there to replace engineer. But we understand the information is in there. And when new engineers come on board, they don’t really know sometimes where to go. And what we’re doing is trying to signpost them and say, look, There’s tickets here that might be relevant.
Mark: Have a look at it, summarize it, figure out what’s going on there. And it means that you can avoid escalations and really start hitting that first time fix. Not only that, you can really start, filling out your team or first line as with effectively relatively inexperienced, and low cost, engineering because all the investment you’ve put into your PSA, all that knowledge can be pulled out and presented straight to them.
Mark: They just need to follow the instructions.
Adam: Sure. you know, my mind is racing thinking, Oh, hang on a second. Can I now replace first line engineers? With admin staff, you know, can I go a level lower, from a triage kind of perspective and it just gets escalated to an engineer, you know, if the AI doesn’t kind of kick in enough.
Mark: Yes, I mean, I mean, there’s a huge amount being played about with obviously like chatbots and being AI backed with that. So it’s self serve because again, a lot of, a lot of the user base, they don’t like calling in. They much prefer sitting behind emails or chat programs, that sort of stuff.
Mark: Can you replace that? Yep, definitely. That’s probably coming on. I’m seeing in the industry, there’s a lot about, you know, you can effectively hire AI engineers and then actually they are the people that you’re interacting with. And I’m sure the industry is going to go that way, a lot more. Like I said, the pace is, it’s a little bit scary.and I think it’s just getting quicker. so who could predict what it’s going to be in five years time? I really don’t know, but yeah, it could be admin could very well
Adam: No, if I have fascinating and, yeah, self serve, where does that go? Hiring AI engineers, where does that go? where does that, how does that position MSPs?in terms of our value and the service that the clients are paying for. just before we explore some of those aspects in a bit more detail, just talk us through that third example that you came up with earlier.
Mark: Yeah. And again, it’s one of those things. it’s one, the feedback that we’re getting from working with some of the MSPs, with the solution that we’ve been developing is again, can you,that, that language, that language barrier for in the UK,it’s probably not as prevalent as maybe other areas in the world, but can you communicate with different people?
Mark: with the same tools and just have that natural ability to communicate between an engineer and a user from different locations without the barrier of language. And I think that having that built in, having that ability just to flow information back and forth between them without having to go to third party apps or translation tools to do that is, is relatively actually quite a simple thing.
Mark: To do again with AI is it’s really not difficult to do, but again, it’s how you integrate and make it work well for the engineer, just so it makes it all natural, saves time, saves effort. You’re not having to, you know, get particular engineers to look after particular customers because there’s barriers on language or things like that.
Mark: and vice versa, it’s not even just a language thing. We’re finding a lot of our users. Maybe, you know, they can’t write to you because English isn’t really, their strong point, you know, and, you know, and you’re having these tools that can help them craft communications, align the communications to the persona of that MSP, you know, I, you know, I, I don’t know about you, but, you know, I’ve certainly seen some communication in APX’s past where I’m like, yeah, I wouldn’t have written that.
Mark: I wouldn’t have written it in that way. So again, can you try and standardize the way that, not make it impersonal, we certainly, you know, cause again, we’re customer service, we don’t want to, we don’t want to lose that personal touch, but again, can you make sure you’re crafting messages in a consistent way that, that makes it, aligned to the business.
Adam: Persona. an immediate example that comes to my mind is. Helping engineers who struggle with dyslexia and similar type of challenges. again,there’s a lot of, lots of those kinds of challenges out there. And, you know, this is a huge step, right? Just to kind of help, help those guys, you know, be better at what they do.
Adam: the persona side is interesting, isn’t it? how does that work? how do you tune your AI to be more EPX?
Mark: so we, we have a fairly casual, approach. We like to be fairly friendly with how we do it. So we’ve crafted. So again, well, the feedback that we got from the engineers is, yeah, they’ve got to do job notes. Yeah. You have to do job notes cause you’ve got to, you’ve got to document what you’ve done, et cetera, like that, but it’s not.
Mark: It’s not what they didn’t go into I. T. to write job notes, if that makes sense. You know, it’s, they do not enjoy it. So we just made it as, as easy as possible. So we made it so automatically produces their job notes for them, structures it in a way to make it consistent. So again, you can, the AI can understand things in a really easy format as well, but then it is, It’s then flowing that into the communication of the customer.
Mark: So from your job notes, we can craft, and a corresponding, a correspondence to that customer, which is appropriate. Because, you know, the users don’t want to see all the tech. They just want to see a really quick summary or some like to see detailed. You can craft that. And the personas came in because the way that EPX speaks to its customers is probably different to the way another MSP speaks to customers.
Mark: Their customers, some want to be hugely professional. Some might be regulated where it has to be factual. Some may want to put details about what was carried out from a technical perspective. Some just want it really basic in terms of fix your problem. Let us know if it’s, you know, it’s that sort of thing.
Mark: So we’ve put in some ability to add some tweaks to those personas, those metrics. So actually when it’s producing outputs, it’s producing one, which is aligned to what the
Adam: And could you tune it per customer or even per person, end user?
Mark: yes. Yeah. No, we definitely could. We’re certainly not there yet, but there is absolutely nothing stopping us from doing it. So we could have, you know, we could have an IT manager as a contact who wants all the technical details. You could have the MD or CEO that doesn’t want any technical details.
Adam: You just have those personas against those, and it produces those notes and communications in line with that. that is not a bad idea. I will take that. Thank you very much. we’ve all had the stuffy solicitors and then we’ve had the way more informal builders, for example, right. And they’d like to be communicated to in different ways and,and, or you may have individuals that are just quirky and they like a certain type of communication.
Adam: is this limited purely to written communication or can this extend into other forms as well? Okay.
Mark: it can. I mean, we are, we have noodled with the idea of tying it into phone systems. you can actually listen to call, you know, as calls are coming in from the engineer. it will actually listen and start taking job notes and start helping assist the engineer and actually producing the set, you know, starting the ticket off.
Mark: We haven’t really, gone too much further than just written communication. Again, we’ve been very conscious that obviously AI coming and, you know, understanding that customer service is the key focus of what we’re trying to achieve as an organization and not really take away too much of that ability from the engineer.
Mark: Again, we mentioned earlier that, There is things obviously the prevalence of chat self serve is going to rise massively over the coming years without a shadow of a doubt. And again, the industry, or the types of people wanting that are growing. You know, again, people don’t like, you know, pick up the phone.
Mark: They just want to be able to go on a chat window. and that’s something that we’re looking into at the moment. And there’s tools out there that do that as well.
Daniel: that leads nicely into what I’m thinking about here. Well, I’ve, I’ve been,scribbling notes, listening to the two of you, two of you talk through these topics. and I’ve of course got lots of opinions and thoughts on this, but,one of the areas I wanted to get into was,the tools.
Daniel: I’m assuming that,there’s a room in your office where, there’s a, like a big cake team with a brain in it and a load of wires coming out, and no one goes in there or if they do,they’re sealed. And, it’s a dust free environment. You know, when we talk about the tools, AI, what exactly is it?
Daniel: Is there a. Bit of software at the heart of this. does it sit on a server somewhere? how do I buy it? what does it look like? can I get different colors and,
Mark: yeah, it’s a, it’s, yeah, so AI is, is interesting. AI comes in many forms. So an AI is effectively an LLM, so a large language model. So it’s, and they come in, you know, various different forms. The most common one, used, at the moment, is OpenAI. and that’s the tool that we’re, that we’ve been leveraging.
Mark: Now, it’s not on a box. It’s not in our server room. It is a cloud service that we interact with. and It’s brilliant. it’s brilliant and it’s groundbreaking and it’s transformational for what we’re doing. it’s interesting, when speaking to MSPs about obviously things like compliance and GDR and things like that, and although open ai, it’s compliance,and complies with GDPR and things like that, the perception is. What’s happening? where is this data going and what’s happening with it? And although,you know, we use the secured, APIs in the backend, which never form part of its learning models and everything’s siloed and everything’s secured and all that sort of stuff. Yeah, there’s always that feeling that people have in the back of their mind, they’re saying, well, what if it isn’t?
Mark: is my client data going to start popping up in search results and things like that? So that’s a natural feeling. That’s a natural consequence to what’s happening. because we don’t know, you know, you pop a question into AI, they don’t know how the answer comes out.
Mark: You know, they just don’t know. it’s just, Magic, magic pops out the other end. however, there are things that you can do. you can download and have your own,LLM, on your own server,and have it, in a box in your server room, and interact with it that way.
Mark: and that’s something that we’ve looked at and played about with it. With just again from reassurance and compliance perspective as well. So you got various different options, and I think again, that’s just it’s exploding. Just all the options that you’ve you got available to you definitely.
Daniel: I guess like, in the olden days,we’ll all remember, a customer’s, desire to have their own exchange server in their office cause they’ve got control over it. And that was one of the big fears with Office 365. Well, it’s not here. I can’t touch it and prod it. And,and, and, and I guess there’s, there’s pros and cons.
Daniel: we are making the assumption that,we’ve got confidence in the technology. There’s a thing we can go and buy. it sounds like,you’re not buying finished products here, though. You are buying a tool that you are having to then develop and implement.
Daniel: pre, presumably there’s a cost. Resource overhead to that. and,the first thing that springs to my mind is, you know, if you’re building something from scratch, you’re not a software development house. You’re an MSP. and perhaps you built something that, that works for you, but then.
Daniel: Where do we go from there? Is it something that another MSP could have? How much like customization? What’s that? What’s the resilience of what’s been built? and yeah, what are your plans there?
Mark: Yeah, so yeah, the way on MSP, and, and we do have experience and history and software development. That’s actually partly way. what’s found it actually is a as a software house. And then we migrated into more, an MSP and we don’t do any software commercially for our customers anymore, but we still got those skills.
Mark: We’ve still got other skills and. We’ve used it a lot to implement changes within IMSP just to, again, just try and bring some optimization and streamlining what we’re doing. And again, when, and when AI came up, I’m going to be honest, it was shiny. It was interesting. It was fun. We played a battle of it and obviously the power of it, it’s just, it’s still.
Mark: It still, you know, impresses me today, even though, I mean, you know, I don’t know how long it’s been with us a year or so, and you’re still just typing into it. It’s like, how’s it do this? it’s just, it’s amazing. Really. and so when we’re developing this, obviously we’re developing for our MSP just to see if we could do something with the ROI on it is from our perspective, just, it’s a no brainer and actually the industry is moving that way.
Mark: We know it is, it can’t afford not to, you know, you, and if you don’t keep up with it, you’re going to be out priced out, competed out service, all the metric, you’re just not gonna be able to compete on anything. just hope you have really good relationships with your customers. that’s the only thing you could probably do, which is important, but it’s going to be a difficult one from that perspective.
Mark: but in terms of actually scaling it, yeah, I mean, we did go in with this too. Develop something for EPX. but when we started showing other people what we’re doing, they’re quite interested. So we did spin it off into a separate entity,and start presenting it, to others.
Mark: And, the feedback from that has been pretty positive. So it’s fairly small,at this moment in time. but yeah, no, it’s, we’re very conscious about.keeping the essence of what we’re trying to do really clean, like with AI, we could just go off and do hundreds of different things because it’s a really great idea to do all these hundreds of different things, but our focus has really been on the approach, which is we want to fix tickets first time and we want to fix them right and we want to make sure that customers are happy. And that is all the focus that we’ve been doing. And we’ve really narrowed it down. And we’ve had lots of ideas from people saying we could do this, could do that. And it’s like, yes, we could, but not yet because we want to make sure that what we’ve got does that, and it does it really well, because if it does that and it doesn’t really well, people will want it because it’ll make them efficient, make them profitable.
Mark: The ROI would be really clear. and the customers will love them for it. And that’s really the essence of what we’re trying to achieve. And I think people resonate with that because they know that’s what customers want and that’s what they wanna achieve with an MSP. So that’s sort of the approach that we’ve taken so far
Daniel: super. And,well, cer certainly,a Adam and I are,are big fans of,of MSPs,learning something themselves and then sharing it with,with the rest of the community and, and finding new,new opportunities as a result. and it’s really good to see actually in the MSP community,generally there’s a lot of,vendor tools.
Daniel: Technologies that are, founded, curated and developed by MSP or former MSP owners or some in some cases, current MSP owners as well. so yeah, the, I mean, you’ve You’ve probably started to answer my next question, which is,like, ROI,we’re seeing, predominantly time saving and reduction in errors.
Daniel: and in time saving, I’m thinking there’s less interruption if I’m not asking that engineer that knows everything all the time and stopping them doing their work. then there’s another benefit there. but, What sort of, investment are we talking about, and therefore what sort of value of,of return are we talking about here?
Daniel: Like, are we close to replacing engineers or,are we, are we talking about a percentage of, of an engineer,rate that, that we could expect?
Mark: that, okay. yeah. the RRI, yeah, it’s an interesting one. so from the information we have at the moment, we’re, look, we’re looking like with, there’s two main metrics. It’s reduction on time, on tickets, and it’s reduction on escalation. So those are the two metrics that we kind of measure.
Mark: and what it looks like is that we reduce the total ticket time by about 20 percent and reduce escalations by 25%. That’s what we’ve seen from data so far. and the reason we’re able to reduce ticket time predominantly is they say external, external reports. So they’re good. Nothing. Pull up some references for it if needed.
Mark: say about 50 percent of time spent on tickets is looking for information. It’s trying to find, I don’t know, Googling things or passwords or documentation and things like that. but what we’ve been able to do is because we can pull in previous tickets and we can pull in, we can reference documentation repositories and things like that.
Mark: We’re signposting engineers directly to information as at the point of entering that ticket. So we’re really able to reduce down that, ticket time. and again, because we’re feeding that information to the engineer. Potential solves. and again, the example is if say, for instance, we, there’s a brand new ticket, you’ve never fixed it before.
Mark: Maybe it’s a brand new customer. So you haven’t got any history to go on this for this customer. so there’s no related tickets that you can pull out,to reference. It will still go away and understand the ticket and based upon its understanding of that, come back and suggest how to resolve that ticket.
Mark: So it’ll give the engineer five or six options to say, this is what we think you need to do to sell the ticket. And I’ll tell the engineer, this is a how to, step by step guide on executing those, each of those things. So what we found is with our tool, and it’s not just a tool, it’s the processes behind it.
Mark: You have to have a clear way of ticket handling and an escalation process to support it. So for us,we have it. So a ticket comes in, the engineer spends 15 minutes on it. If they can’t do it, look at related tickets, look at suggested fixes, look at documentation. If they can’t do it there, look at, you know, there’s a clear step by step process on how a ticket is handled by that engineer.
Mark: And because of that, and we’re guiding and providing information to the engineer, they’re able to solve it themselves quicker. And we’re finding that we’re, so we bring a lot of apprentices. and we’re finding a way to get apprentices up and running within their first week, solving tickets in their first week, whereas previously to this, before the processes, before the tools coming in, you know, it might be a few weeks before they’re doing a lot of shadowing before they built the confidence up there and they’re not tapping on the, Experience engineers, nearly as much.
Mark: So it frees up a lot of that time. They feel empowered. They’re getting trained. They’re able to feel like they’re productive members of the team a lot sooner as well. So there’s a lot of benefits we’re seeing from that. And a lot of intangibles. So there’s a lot of intangibles, some tangibles and a lot of intangibles from it.
Adam: kind of last air of discussion, to me, this feels like this is, you know, Kind of how, where we were 10, 15 years ago, when cloud was starting to be adopted. And there was a new opportunity for MSPs to start to differentiate themselves from others because they could be experts in cloud, they could articulate what cloud meant.
Adam: They could start to build out their own solutions, and articulate the benefits to clients. And to me, this seems a bit similar to that. There’s an opportunity here for good MSPs to kind of simplify what AI means for their end user clients, and also to start to. Hammer home the benefits of how they’re embracing it to the benefit of the client. And I guess there is also potentially the challenge of how you educate clients around how AI as a tool can augment the overall MSP performance. So it’s not just something you’re going to delegate to, right? Say, Oh, do you know what? We’re just going to chat GPT and type in your query. And it comes up with the answer.
Mark: Cause. Clearly, they’ll go, well, we can just do that. So there’s kind of a whole mixture of things here. And I just, I’m just interested in your opinion around how you see the opportunity from a sales and marketing perspective, and if you’ve got a new device for MSPs today, if they’re not already embracing this, how they might do Yeah. it’s an interesting one about the sales and marketing, how you present it, because if you just slap an AI badge onto something, it doesn’t really mean anything. again, it’s really just understanding.
Adam: was doing that with cloud as well, weren’t
Mark: Oh, yeah, well, yeah, I mean, yeah, what does, yeah, I still don’t quite know what it fully means, but there we go.
Mark: yeah, well, I’ll get there one day, I’ll educate myself. but, yeah, AI is,it, yeah, and when we fell into that trap a little bit when we’re first playing about what we’re developing, it’s like, let’s throw AI all over it, it’s a buzzword, let’s Get going. But actually it was when we’re refining down what we’re doing, it is a tool and it’s how you execute the tool.
Mark: And we, as MSP owners, we’ve all had the lovely new shiny tool that comes along. It looks really interesting and it’s great. let’s pay some money for it and not properly implement it. And then, Oh, guess what? It doesn’t work.so it’s about making sure it’s right for you and you understand what you’re trying to do with that tool and it’s all about the outcomes, what you’re trying to achieve, and then does that tool help you achieve that?
Mark: that’s really the approach that needs to happen. So I’m sort of answering the second question first, so apologies for that. But yeah, so in terms of MSPs embracing AI, yeah, it’s about, I think it’s something that everyone has to be aware of and obviously I think everyone is aware about it. The landscape is going to change. And I said, we’re going to be, we might be talking next year and things have moved on massively. and maybe it’s going to be AI engineers are all the way forward and we’re paying pennies on the pound for those services and IT support is purely commoditized and the MSP has to move more into a consultative, security led practice, and, side of things, which, but I see the industry going into anyway.
Mark: but yeah, so both MSP wants to embrace it. Yeah. It’s just really understanding what they’re trying to achieve. What do they want to do as an organization and making sure that the tools, your business direction is and driving the tools, not your tools, driving a business direction. that’s really the key part to it.
Mark: and then embracing AI. If AI is part of that roadmap saying, actually, we want to be more efficient when I want to leverage it. Okay. Well, What’s the outcomes? And does that solve that? So that’s sort of the advice for the MSP side. in terms of the sales and marketing, you know, I’ve not, I’ve been conscious about not going to the customers, really, talking about AI as a selling point,as a benefit to why we’re a good practice.
Mark: mainly because I think people are still quite scared about it.
Adam: Interesting.
Mark: And it’s not, and I don’t, and I don’t actually feel it’s a significant selling point. The selling point is we’re providing a good service and we’re hitting the things that the customers want. And if we’re happening to happening to leverage AI to do that, then that’s a thumbs up for us.
Mark: And again, that gives us some authority and ability when we’re speaking to them about their business to start saying, Right. Have you thought about this for your organization? Could you do something? But that’s shifting more to a consultative side rather than sort of the I. T. support side, if that makes sense.
Mark: yeah, no, we’ve strayed away from it quite a bit from a marketing
Adam: Okay. I think it’s a fascinating area. I think there’s definitely some opportunity there, anything to differentiate one MSP from another, I think is key. we, Dan, any final thoughts from yourself?
Daniel: s sounds like we’ll be okay until they come up with a consultant ai. and so ho hopefully, hopefully that will see us out, . But, but yeah, I guess the takeaway for me really,and the last point really was about, the, this isn’t gonna. change the direction of our industry.
Daniel: It’s purely going to accelerate it. You know, we’re going more towards consultancy and security. this is an enabler in some ways, as the pandemic was, you know, it was a push towards the remote working and,and,and, yeah, has accelerated things. so I think that’s the takeaway I have from this really.
Daniel: and, and there’s a competitive advantage to be gained. and,and therefore, therefore you’ve got to be, I’ve got to be doing that at some level and at a speed that’s comfortable and, and appropriate for ultimately what you want your business to be, to be delivering you.
Daniel: yeah, really interesting conversation. And,I still think there’s a brain in a cake team with cables coming out of it somewhere. so that’s what I’m going to continue to think about.
Adam: Perfect. Perfect. And for me, I think it always comes back to change where there’s change. There’s opportunity. So I think this is massive. I think it’s change. It’s complex. it’s evolving so quickly. so get involved. Start talking to your customers about it and I think there’s definitely a lot of opportunity Mark, it’s been a pleasure having you on the podcast today really enjoyed our chat and if somebody would like to get hold of you the best way to do so
Mark: yeah,so if they’re interested in, well, if you’re interested on the MSP side, just want a general chat about the MSP is EPS. co. uk, and it’s just mark at EPS. co. uk, if you’re interested in the AI,the assistant on that side, then it’s, if you just go to dark labs. ai,you can have a look there and again, it’ll be mark at dark
Adam: Oh a bit sinister. Do you want to go there? I prefer that one
Adam: the product is called, the solution we developed is called Insight. Yeah, no, DartLabs,yeah, probably we’ll go for it, yeah, go for Insight, yeah, it’s called Insights. But yeah,a pleasure. Thanks very much
Mark: no, thank you very much for inviting me on, it was brilliant chatting to you, so thank you.