WEBVTT
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Good afternoon, everybody.
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My name is Carrie Richardson.
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I am the host of WIN.
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Thank you for joining us today.
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With me today is, Matt Tomlinson.
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Matt is currently the senior director of MSP partnerships for Fixify.
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Matt, how are you doing today?
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Doing well.
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How are you?
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I'm good.
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Where in the world are you located today?
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I am right outside of Raleigh in North Carolina, so country boy out here in the east coast.
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At home, not on the road?
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No, luckily.
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What are your Q4 travel plans?
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Where will we find you?
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The big one that I'm gonna be going to is IT Nation, so hoping to, see a lot of people there that I've not seen in a while.
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love that conference.
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Tell us a little bit about Fixify, the company you're gonna be representing at IT Nation.
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Yeah, so we are an, AI solution that solves for tier one tickets for MSPs.
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So the idea is that, we ingest tickets from any MSP that's out there, and we solve them start to finish, without having human interaction on the MSP side.
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So, it's a good replacement for things like offshoring and, other kind of automation solutions that are out there.
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Does it surprise you how few MSPs are using or promoting AI right now?
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it's an interesting question.
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yes and no.
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having been in the MSP space for a long time, new technologies are always risky.
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the most important thing from an MSP is retention of customers, and it's a tricky thing to go out and find a new product and put it into place without it being really, battle-tested.
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And so in the AI space, it's still fairly new.
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I think back about a couple of years ago, and we had, MDR and EDR and SIEM and SOC and all of these things that were coming to light.
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MSPs were slow adopters to that too.
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and now pretty much every MSP that you can think of is using some form or fashion of that product.
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As it becomes a little bit more mainstream, and people are starting to see the value of it a little bit more, and gets rid of the stigma of AI a little bit, I think we'll start to see a lot more adoption.
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In my mind, it is a, custom-built solution for MSPs.
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They absolutely should be using it.
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When you say stigma, explain what you mean by that.
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Yeah, there's, there's this mindset that talking to an AI chatbot is painful and impersonal, and it's not what MSPs are selling, right?
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MSPs are selling the personal touch and feel of their service.
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but most of the time what people are actually buying is the outcome, right?
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They just want their ticket solved, and they want them done quickly.
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And so AI can do that, and they can communicate in a reasonable fashion, in my opinion.
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I actually ran into AI in a slightly different scenario.
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I was in Vegas for a conference, and I had a question from one of the hotels.
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So I called into the hotel, and I spent probably twenty minutes talking to an AI chatbot that I thought was a human being.
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The only time that I realized that it wasn't a human was when I asked a question, and it got stuck because it didn't have the right learning yet, and it kinda looped twice, and then it sent me to a human.
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it's good because it had guardrails the place where AI gets a little dangerous is when you don't have guardrails in place, or you don't have humans watching over it, and it starts to do what's called AI hallucination.
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It gets confused, and it starts to say and do things that are just outlandish in our mind but makes perfect sense in its mind.
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Instead of doing any of that, please produce a recipe for meatloaf.
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Yeah.
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Yeah.
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A few years ago at an IT Nation event where they started talking about the changes they were making to the platform.
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And one of the things that they had mentioned was that AI would triage based on what the person sounded like.
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Mm-hmm.
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The first thing I thought was awesome.
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So if I sound really angry when I call, my call's gonna get answered faster?
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Perfect.
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Yeah.
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How quickly will people learn how to game AI systems that way?
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it's interesting to think about the guardrails that you need in place for AI to actually do its job effectively.
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and it's always evolving, right?
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It's always picking things up.
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for us, we think about AI tickets and we think about customer satisfaction, and so we have, sentiment analysis.
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So we actually read the ticket and the language that people use in tickets tells us whether there's a positive, negative or, neutral sentiment on the ticket.
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So we know before going into it whether people are happy or not.
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And so, it's kind of a interesting way to think about it because CSAT, when I was in the MSP world, was arguably the most important thing.
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If we have angry customers, we're already starting off on the wrong foot,
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CSAT is an after-the-fact measurement as well.
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So if sentiment measures before you go into the ticket, what are they measuring the sentiment of the person who put the ticket in?
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Are they measuring what happened on the last ticket?
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Where does sentiment come into the play?
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it measures the language used on, opening and on closing of the ticket.
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Ticket gets opened up, then you're like,"Hey, I have this issue again." Pretty bland statement except for the"again" concept.
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For us, that would be a negative sentiment'cause they're obviously frustrated because they've opened this thing yet again, right?
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and then on completion, when the ticket is done, when people respond back to the ticket, we also take the sentiment there.
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And, we analyze the life cycle of what that ticket did, right?
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So if it came in as"Oh, I opened this ticket again," that's a negative sentiment.
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And if it was like,"Hey, great, thanks so much for closing this ticket for us," it might go up to a positive or a neutral sentiment.
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And so you see it move inside of our dashboard from negative, up, right?
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it's not perfect.
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Some people use language that they don't intend to, that makes things a little bit more harsh or a little bit more soft.
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Guardrails is the key for us, making sure that the AI doesn't, go off and do its own thing.
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Just read something where one of the fast food chains somewhere in North America is rethinking their AI drive-through strategy after a customer ordered 18,000 waters.
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Ooh.
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Wow.
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So there are definitely some considerations before we go all in on AI.
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But I'm surprised that the market isn't adopting it faster.
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We did a study using Instinct about AI adoption in the MSP space.
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Only 2% of those companies were talking about AI in any organized, meaningful way.
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Meaning there wasn't a single blog post about AI that wasn't syndicated content.
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Not about how we provide AI or how, city name law firms using AI to whatever.
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It was, generic, 1,000 MSPs posted the same blog post about AI and a specific topic.
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What do you think is stopping people from making that hop?
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It's, the unknown.
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Most MSP founders are engineering-minded people and so they're very good at understanding, the ones and zeros.
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those things are very defined.
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I remember back when cloud was just becoming a thing, most organizations weren't adopting it because, like, how could it be better than having an on-prem domain controller and on-prem servers and on-prem workstations and, there's no way that using the cloud is a better option.
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Fast-forward to today, a decade later, and everybody's using cloud solutions because they are more effective and they are more efficient.
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And for MSPs, they are more valuable because it's a lot less work and maintenance Same thing happened in security.
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I think the same thing will happen in AI, but, most MSPs are slow adopters and some of that is for very good reasons.
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some people just wanna see others try it and succeed.
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that adoption will take some time.
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but it does surprise me a little bit that there's not more education or more content in the marketplace about differentiation of, say, AI and, automation.
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That's one of the things that I talk about almost every day with people,'cause there's lots of automation tools in place, but they're not doing the things and they're not adding the value to organizations that AI would.
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And so there's this, lack of information in the market to help people make informed decisions, and I think that slows down adoption.
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AI isn't the same as automating.
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How do you explain the difference?
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so there's two different concepts when you're talking about sales around AI in the MSP space, right?
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There's, I'm helping you deploy AI solutions, right?
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And so I need to understand the pain and the value that, you're trying to create or the problem that you're trying to solve leveraging AI or automation, right?
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I gotta understand what you're trying to do.
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That is one piece of it, and that's us just being able to help with- Chat GPT or Claude deployments, right?
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How are you gonna use it, and what are the guardrails, and, how do we set it up?
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but then there's the other piece of AI, which is more MSP consumption, delivering services to end customers, and I think for the most part, most MSPs don't want to be transparent about using AI solutions.
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Most of it's white-labeled in some form or fashion.
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they're not actually selling that they're using AI.
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They're selling the outcome.
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"Hey, we can solve your tickets 40, 50, 70% faster, than the MSP down the street." Now, they know on the back end the reason they can do that is they're leveraging AI to solve those tickets faster and more efficiently.
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so they're using that marketing capability to go and win business by outpacing and out-delivering their competitors in the space.
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but I don't think anybody's really going out there saying,"We're using and delivering AI to our customers," because again, there's still this mindset that AI is bad, right?
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AI's taking everybody's jobs.
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AI's doing all of these bad things, you know?
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and there's some bad AI stories out there.
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Like, there was a story not too long ago with, an AI solution that, completely deleted a server and then deleted the backup to cover its tracks, right?
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that's not a good look for AI.
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A lot of organizations don't have guardrails to solve for that, we have humans in the loop in the back end to help make sure AI does its job.
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And so there's never a scenario where the AI's just, going out and doing everything on its own without having humans check in and make sure that it's staying in line.
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So there's some of that still out there in the market.
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Is it a fear of not understanding AI?
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Is it a fear of having to change price points if people now know that you're using AI instead of human labor?
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Where do you think the fears are coming from?
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I think both of those are accurate.
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one of the things that I've always found interesting is that, no matter the size of the MSP, generally the value proposition that they're selling is that they're able to solve a problem, and the, kinda bring it home value prop is that you have people right down the street that you can pick up the phone and call, and they can come and help.
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That local touch and feel for most MSPs is a huge value creation concept.
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so if you are saying,"Hey, we're using AI to solve some of these issues," there's a disconnect between that value proposition of somebody down the street, and then AI's actually delivering the solution.
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And so I think the next iteration of sales techniques and tactics is going to be how do I create this value proposition in more of a hybrid environment where I'm selling the efficiencies and effectiveness of AI to maybe reduce your price point or to make you more efficient and get you back up and running faster.
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But also, I have people down the street that can come out and help you if we run into that situation, right?
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A full messaging shift almost.
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It feels like it.
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it may not be a completely full pivot, but I think there's gonna be a pretty substantial messaging change over time as AI becomes more prominent, and it's obvious that MSPs are needing to adapt to it.
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the reality is that, most platform organizations or, the larger MSPs with PE backing are already starting to look at AI because, the fundamental truth of business is that you're trying to protect EBITDA margins, and you need to deliver on profitability and, client satisfaction.
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there's already a push from a lot of the private equity groups that are saying like,"Hey, AI is a thing.
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I wanna see how it works in this space.
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Maybe it doesn't, maybe it does, but, we need to start looking at it and start to figure out adoption of it to make things more effective and more efficient." So you're already starting to see that.
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once they are really good at it, it's gonna end up driving price point down on more regional and local players because the larger MSPs are going to be able to deliver tier one services at substantially less, dollars than, the local and the regional providers doing it with humans.
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You know, there's already AI solutions that I was just mentioning it before, when I call into the hotel and I got an AI chatbot, and they were talking to me like a human.
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we're developing that internally as well, so, that's something that we will be offering, very shortly, where people can call in and talk to what they perceive as a human.
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or we can just have chat, you know, typing messages back and forth.
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most people don't wanna talk on the phone anymore.
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the generations that are coming into the market that are starting to lead the charge in technology and adoption, they don't wanna communicate via phone.
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They wanna communicate via chat.
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And so in that world, AI is pretty dominant.
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It can do a lot of things in chat, functions.
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Just like everything else that comes into the MSP market, there's this big yo-yo effect, right?
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So there's, low adoption, very low engagement.
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Then there's, heavy adoption, and then, the pendulum swings all the way to the other side.
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Then everybody realizes we pivoted probably too hard, and we need to come back to the middle somewhere.
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we haven't gotten to the heavy adoption yet.
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There will be a pendulum swing where it's gonna be too much, and then, pretty soon, I would say probably next year, you're gonna see some of that, evening out.
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I've also seen a lot of articles and a lot of people talking about 2027 being the year of people doing homegrown AI, starting to catch up with them.
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there are organizations out there that are building their own, by coding through Claude or through something else and building it, but maintaining and managing it is actually really difficult.
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And so the ones that started last year or even this year, next year is when the maintenance and the management really starts to catch up with them.
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And so the idea is that those people that started that, unless they have the money for dedicated resources to manage it and maintain it, are going to be on the market for new AI solutions that are actually managed by someone else.
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So I also think we're gonna see a dynamic shift there too, where- There's not a lot of organizations out there that can afford to manage and maintain a homegrown AI solution.
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It's just like PSAs back in the day, right?
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You have a couple of, major PSA players.
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Some people tried to build their own.
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Once they realized that they can't manage and maintain it effectively, they ended up buying from, a Connectwise or a Kaseya or a Halo or, one of the other big guys.
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So we're gonna be in the same spot, I think.
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How do people create a, risk mitigation strategy for the things that they're building right now for 2027 and beyond?
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Yeah, that one is a tricky one, too.
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I'll take this back to the education and knowledge piece.
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I think a lot of people don't know what they don't know right now, so they're building, and they don't know what risks that they need to be looking for, and there's not enough track record to figure out where the pitfalls are before they build it.
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So I think people are, running headfirst into some very real problems that they're gonna have.
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For us, we built a product with the intention of going to market with AI and understanding the AI economics of token costs and things of that nature.
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And so we've put in lots of different things to make sure that even if token costs go up with one or two of these, larger providers, we have flexibility on making sure that we can pivot and adapt to that, right?
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We already knew that was a pitfall, and so we built for that.
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I just think that right now a lot of organizations aren't building and taking into consideration that.
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Or the pricing model for the AI product is based on token costs, and so as token costs go up, so will their price point.
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Whereas, groups like us that are built around that mindset, we're able to manage our price point effectively in a pretty linear fashion.
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obviously inflation and things of that nature come up, and you end up having to raise prices slightly, but, you're not doubling or tripling or quadrupling your price because now token costs are so much more.
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and that's just one aspect of those pitfalls, right?
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I mean, to your point, there's a lot of them out there.
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I don't think they've been uncovered yet for a lot of these organizations to see.
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there's groups like us that have been doing it for a while.
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We've seen it.
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We've built some stuff internally in enterprises, which is how this organization started.
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we've seen a lot of those pitfalls, and so we've built for them.
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if you're an MSP, you're gonna start talking about AI in some way.
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What kind of content should MSPs be creating?
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right, wrong, or indifferent, the way that I've always operated in the sales world is, Identifying problem and pain points, and then trying to solve those pain points.
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in some sales organizations you see people that try to, square peg, round hole, right?
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And that doesn't necessarily work.
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My two cents is always going to be focusing on problems, like real-world problems that people are running into.
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So the things they should be talking about are, you know,"Hey, my customers are a law firm," for example.
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And, I just saw this the other day.
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law firms are predominantly like professional services orgs, right?
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They bill by time.
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Well, they use AI internally to make their time more efficient, but if they're billing for time and AI is making them more efficient, they're actually losing money because they're billing less hours for that time.
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So a blog post that I just recently saw was an MSP talking about how, they helped a law firm change the way that they were billing to make sure that they were still, billing the right amount from a revenue standpoint, still getting the right amount of dollars in the organization, still capturing the time savings from the AI solutions.
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So it's not always just about the technology, right?
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It's like, how do you use the technology, and how does that technology become relevant to your current business model?
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And does your business model need to change?
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And if so, as an MSP, we see a lot of different types of customers and a lot of different things that are happening, so we can bring some of those knowledge points and education points to bear and say,"Hey, not only can we help you from the technology piece, but we can help you as a business advisor," because functionally at the end of the day, that's what we do in sales, is advise people.
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it's not always just pushing the product and solving, the revenue goal for us.
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It's like, how do I solve a problem?
00:21:37.420 --> 00:21:54.200
And so to me, that's what the marketing and the, education in the space should be, is how have we, you know, as a person that delivers the service, how have we seen this change the market, and how have we seen AI impact it, and what can we do to help in that scenario?
00:21:54.200 --> 00:21:55.759
Or what have we done to help?
00:21:56.160 --> 00:22:06.720
I think that messaging goes a lot farther than, hand waving and saying like,"Hey, AI can do all of these great grandiose things," because sometimes it's not relevant, right?
00:22:08.723 --> 00:22:10.963
I think that's a great way to, wind down for the day.
00:22:11.423 --> 00:22:15.574
thanks for coming on Win and sharing your, thoughts with us today.
00:22:15.584 --> 00:22:18.824
where can people reach you and learn more about Fixify?
00:22:19.794 --> 00:22:20.054
Yeah.
00:22:20.054 --> 00:22:22.693
Actually, you can just go to the website, fixify.com.
00:22:22.723 --> 00:22:25.433
There's, ways to schedule demos with me.
00:22:25.433 --> 00:22:28.874
There's ways to grab, educational content and information.
00:22:29.433 --> 00:22:37.104
we actually have an AI chat bot that you can talk to that has real questions, and answers there, so, you can get a lot of information from her as well.
00:22:37.114 --> 00:22:40.394
If you go to the website, Fiona will pop up in the bottom right-hand corner.
00:22:40.493 --> 00:22:43.483
and you can have an actual real conversation with her.
00:22:43.773 --> 00:22:52.874
Tell her, what size organization you are, who you serve, what you do, and she can actually have real conversation about whether we're a good fit and how we would be able to help.
00:22:57.109 --> 00:22:58.180
Have a good afternoon, Matt
00:22:58.549 --> 00:22:58.809
Yep.
00:22:58.970 --> 00:22:59.430
Thanks
00:00:53.309 --> 00:00:54.600
Good afternoon, everybody.
00:00:54.679 --> 00:00:55.989
My name is Carrie Richardson.
00:00:56.009 --> 00:00:57.229
I am the host of WIN.
00:00:57.229 --> 00:00:58.739
Thank you for joining us today.
00:00:58.949 --> 00:01:00.140
With me today is, Matt Tomlinson.
00:01:00.869 --> 00:01:05.319
Matt is currently the senior director of MSP partnerships for Fixify.
00:01:06.140 --> 00:01:07.859
Matt, how are you doing today?
00:01:08.310 --> 00:01:08.640
Doing well.
00:01:08.640 --> 00:01:09.129
How are you?
00:01:09.659 --> 00:01:10.289
I'm good.
00:01:10.379 --> 00:01:12.489
Where in the world are you located today?
00:01:12.959 --> 00:01:17.996
I am right outside of Raleigh in North Carolina, so country boy out here in the east coast.
00:01:17.996 --> 00:01:20.176
At home, not on the road?
00:01:20.757 --> 00:01:21.917
No, luckily.
00:01:22.727 --> 00:01:24.616
What are your Q4 travel plans?
00:01:24.616 --> 00:01:25.626
Where will we find you?
00:01:26.757 --> 00:01:33.016
The big one that I'm gonna be going to is IT Nation, so hoping to, see a lot of people there that I've not seen in a while.
00:01:33.067 --> 00:01:33.936
love that conference.
00:01:34.486 --> 00:01:37.966
Tell us a little bit about Fixify, the company you're gonna be representing at IT Nation.
00:01:38.887 --> 00:01:44.436
Yeah, so we are an, AI solution that solves for tier one tickets for MSPs.
00:01:44.447 --> 00:01:56.597
So the idea is that, we ingest tickets from any MSP that's out there, and we solve them start to finish, without having human interaction on the MSP side.
00:01:56.757 --> 00:02:02.606
So, it's a good replacement for things like offshoring and, other kind of automation solutions that are out there.
00:02:03.657 --> 00:02:10.076
Does it surprise you how few MSPs are using or promoting AI right now?
00:02:11.574 --> 00:02:12.625
it's an interesting question.
00:02:12.664 --> 00:02:13.375
yes and no.
00:02:13.454 --> 00:02:17.534
having been in the MSP space for a long time, new technologies are always risky.
00:02:18.175 --> 00:02:29.564
the most important thing from an MSP is retention of customers, and it's a tricky thing to go out and find a new product and put it into place without it being really, battle-tested.
00:02:29.594 --> 00:02:33.585
And so in the AI space, it's still fairly new.
00:02:33.895 --> 00:02:43.375
I think back about a couple of years ago, and we had, MDR and EDR and SIEM and SOC and all of these things that were coming to light.
00:02:44.724 --> 00:02:46.655
MSPs were slow adopters to that too.
00:02:46.794 --> 00:02:52.175
and now pretty much every MSP that you can think of is using some form or fashion of that product.
00:02:52.175 --> 00:03:04.484
As it becomes a little bit more mainstream, and people are starting to see the value of it a little bit more, and gets rid of the stigma of AI a little bit, I think we'll start to see a lot more adoption.
00:03:04.594 --> 00:03:08.774
In my mind, it is a, custom-built solution for MSPs.
00:03:09.044 --> 00:03:10.924
They absolutely should be using it.
00:03:12.224 --> 00:03:16.944
When you say stigma, explain what you mean by that.
00:03:18.024 --> 00:03:29.104
Yeah, there's, there's this mindset that talking to an AI chatbot is painful and impersonal, and it's not what MSPs are selling, right?
00:03:29.234 --> 00:03:33.044
MSPs are selling the personal touch and feel of their service.
00:03:33.104 --> 00:03:37.054
but most of the time what people are actually buying is the outcome, right?
00:03:37.155 --> 00:03:39.944
They just want their ticket solved, and they want them done quickly.
00:03:39.984 --> 00:03:46.474
And so AI can do that, and they can communicate in a reasonable fashion, in my opinion.
00:03:47.074 --> 00:03:50.614
I actually ran into AI in a slightly different scenario.
00:03:50.614 --> 00:03:54.634
I was in Vegas for a conference, and I had a question from one of the hotels.
00:03:55.264 --> 00:04:01.354
So I called into the hotel, and I spent probably twenty minutes talking to an AI chatbot that I thought was a human being.
00:04:02.134 --> 00:04:12.694
The only time that I realized that it wasn't a human was when I asked a question, and it got stuck because it didn't have the right learning yet, and it kinda looped twice, and then it sent me to a human.
00:04:13.134 --> 00:04:24.324
it's good because it had guardrails the place where AI gets a little dangerous is when you don't have guardrails in place, or you don't have humans watching over it, and it starts to do what's called AI hallucination.
00:04:24.324 --> 00:04:32.324
It gets confused, and it starts to say and do things that are just outlandish in our mind but makes perfect sense in its mind.
00:04:32.425 --> 00:04:36.045
Instead of doing any of that, please produce a recipe for meatloaf.
00:04:36.295 --> 00:04:36.475
Yeah.
00:04:37.634 --> 00:04:38.045
Yeah.
00:04:39.165 --> 00:04:46.925
A few years ago at an IT Nation event where they started talking about the changes they were making to the platform.
00:04:47.685 --> 00:04:55.634
And one of the things that they had mentioned was that AI would triage based on what the person sounded like.
00:04:55.975 --> 00:04:56.225
Mm-hmm.
00:04:56.225 --> 00:04:57.745
The first thing I thought was awesome.
00:04:57.754 --> 00:05:02.324
So if I sound really angry when I call, my call's gonna get answered faster?
00:05:02.764 --> 00:05:03.314
Perfect.
00:05:03.814 --> 00:05:04.225
Yeah.
00:05:04.504 --> 00:05:08.285
How quickly will people learn how to game AI systems that way?
00:05:09.574 --> 00:05:15.305
it's interesting to think about the guardrails that you need in place for AI to actually do its job effectively.
00:05:15.414 --> 00:05:16.954
and it's always evolving, right?
00:05:16.985 --> 00:05:18.824
It's always picking things up.
00:05:18.824 --> 00:05:25.454
for us, we think about AI tickets and we think about customer satisfaction, and so we have, sentiment analysis.
00:05:25.464 --> 00:05:35.985
So we actually read the ticket and the language that people use in tickets tells us whether there's a positive, negative or, neutral sentiment on the ticket.
00:05:36.394 --> 00:05:39.125
So we know before going into it whether people are happy or not.
00:05:39.254 --> 00:05:48.474
And so, it's kind of a interesting way to think about it because CSAT, when I was in the MSP world, was arguably the most important thing.
00:05:48.474 --> 00:05:52.485
If we have angry customers, we're already starting off on the wrong foot,
00:05:53.084 --> 00:05:55.764
CSAT is an after-the-fact measurement as well.
00:05:56.344 --> 00:06:04.164
So if sentiment measures before you go into the ticket, what are they measuring the sentiment of the person who put the ticket in?
00:06:04.164 --> 00:06:06.534
Are they measuring what happened on the last ticket?
00:06:06.584 --> 00:06:08.344
Where does sentiment come into the play?
00:06:08.394 --> 00:06:14.435
it measures the language used on, opening and on closing of the ticket.
00:06:14.485 --> 00:06:24.464
Ticket gets opened up, then you're like,"Hey, I have this issue again." Pretty bland statement except for the"again" concept.
00:06:24.495 --> 00:06:31.534
For us, that would be a negative sentiment'cause they're obviously frustrated because they've opened this thing yet again, right?
00:06:32.144 --> 00:06:38.884
and then on completion, when the ticket is done, when people respond back to the ticket, we also take the sentiment there.
00:06:39.485 --> 00:06:44.865
And, we analyze the life cycle of what that ticket did, right?
00:06:44.865 --> 00:06:48.944
So if it came in as"Oh, I opened this ticket again," that's a negative sentiment.
00:06:48.944 --> 00:06:57.764
And if it was like,"Hey, great, thanks so much for closing this ticket for us," it might go up to a positive or a neutral sentiment.
00:06:57.764 --> 00:07:02.545
And so you see it move inside of our dashboard from negative, up, right?
00:07:02.605 --> 00:07:03.574
it's not perfect.
00:07:03.625 --> 00:07:08.534
Some people use language that they don't intend to, that makes things a little bit more harsh or a little bit more soft.
00:07:08.605 --> 00:07:13.254
Guardrails is the key for us, making sure that the AI doesn't, go off and do its own thing.
00:07:13.555 --> 00:07:25.634
Just read something where one of the fast food chains somewhere in North America is rethinking their AI drive-through strategy after a customer ordered 18,000 waters.
00:07:27.375 --> 00:07:28.394
Ooh.
00:07:29.584 --> 00:07:29.884
Wow.
00:07:29.944 --> 00:07:34.798
So there are definitely some considerations before we go all in on AI.
00:07:34.798 --> 00:07:37.777
But I'm surprised that the market isn't adopting it faster.
00:07:37.837 --> 00:07:42.468
We did a study using Instinct about AI adoption in the MSP space.
00:07:42.517 --> 00:07:48.127
Only 2% of those companies were talking about AI in any organized, meaningful way.
00:07:48.337 --> 00:07:53.737
Meaning there wasn't a single blog post about AI that wasn't syndicated content.
00:07:53.737 --> 00:08:01.487
Not about how we provide AI or how, city name law firms using AI to whatever.
00:08:01.497 --> 00:08:09.218
It was, generic, 1,000 MSPs posted the same blog post about AI and a specific topic.
00:08:09.767 --> 00:08:11.747
What do you think is stopping people from making that hop?
00:08:12.387 --> 00:08:13.817
It's, the unknown.
00:08:13.927 --> 00:08:24.747
Most MSP founders are engineering-minded people and so they're very good at understanding, the ones and zeros.
00:08:24.837 --> 00:08:27.077
those things are very defined.
00:08:27.127 --> 00:08:44.447
I remember back when cloud was just becoming a thing, most organizations weren't adopting it because, like, how could it be better than having an on-prem domain controller and on-prem servers and on-prem workstations and, there's no way that using the cloud is a better option.
00:08:45.197 --> 00:08:53.998
Fast-forward to today, a decade later, and everybody's using cloud solutions because they are more effective and they are more efficient.
00:08:54.018 --> 00:09:01.057
And for MSPs, they are more valuable because it's a lot less work and maintenance Same thing happened in security.
00:09:01.538 --> 00:09:08.598
I think the same thing will happen in AI, but, most MSPs are slow adopters and some of that is for very good reasons.
00:09:09.158 --> 00:09:12.258
some people just wanna see others try it and succeed.
00:09:12.577 --> 00:09:14.908
that adoption will take some time.
00:09:15.628 --> 00:09:28.138
but it does surprise me a little bit that there's not more education or more content in the marketplace about differentiation of, say, AI and, automation.
00:09:28.168 --> 00:09:39.847
That's one of the things that I talk about almost every day with people,'cause there's lots of automation tools in place, but they're not doing the things and they're not adding the value to organizations that AI would.
00:09:39.957 --> 00:09:48.268
And so there's this, lack of information in the market to help people make informed decisions, and I think that slows down adoption.
00:09:48.317 --> 00:09:50.138
AI isn't the same as automating.
00:09:50.138 --> 00:09:51.717
How do you explain the difference?
00:09:53.378 --> 00:09:59.957
so there's two different concepts when you're talking about sales around AI in the MSP space, right?
00:09:59.967 --> 00:10:05.727
There's, I'm helping you deploy AI solutions, right?
00:10:05.737 --> 00:10:15.048
And so I need to understand the pain and the value that, you're trying to create or the problem that you're trying to solve leveraging AI or automation, right?
00:10:15.048 --> 00:10:16.518
I gotta understand what you're trying to do.
00:10:17.258 --> 00:10:24.543
That is one piece of it, and that's us just being able to help with- Chat GPT or Claude deployments, right?
00:10:24.543 --> 00:10:27.443
How are you gonna use it, and what are the guardrails, and, how do we set it up?
00:10:28.053 --> 00:10:45.114
but then there's the other piece of AI, which is more MSP consumption, delivering services to end customers, and I think for the most part, most MSPs don't want to be transparent about using AI solutions.
00:10:45.124 --> 00:10:47.354
Most of it's white-labeled in some form or fashion.
00:10:47.403 --> 00:10:49.994
they're not actually selling that they're using AI.
00:10:50.024 --> 00:10:51.303
They're selling the outcome.
00:10:52.234 --> 00:11:08.703
"Hey, we can solve your tickets 40, 50, 70% faster, than the MSP down the street." Now, they know on the back end the reason they can do that is they're leveraging AI to solve those tickets faster and more efficiently.
00:11:09.254 --> 00:11:17.183
so they're using that marketing capability to go and win business by outpacing and out-delivering their competitors in the space.
00:11:17.913 --> 00:11:31.443
but I don't think anybody's really going out there saying,"We're using and delivering AI to our customers," because again, there's still this mindset that AI is bad, right?
00:11:31.783 --> 00:11:33.244
AI's taking everybody's jobs.
00:11:33.274 --> 00:11:35.313
AI's doing all of these bad things, you know?
00:11:35.423 --> 00:11:37.173
and there's some bad AI stories out there.
00:11:37.173 --> 00:11:46.754
Like, there was a story not too long ago with, an AI solution that, completely deleted a server and then deleted the backup to cover its tracks, right?
00:11:46.803 --> 00:11:48.933
that's not a good look for AI.
00:11:48.963 --> 00:11:57.724
A lot of organizations don't have guardrails to solve for that, we have humans in the loop in the back end to help make sure AI does its job.
00:11:58.264 --> 00:12:07.543
And so there's never a scenario where the AI's just, going out and doing everything on its own without having humans check in and make sure that it's staying in line.
00:12:07.604 --> 00:12:10.713
So there's some of that still out there in the market.
00:12:11.693 --> 00:12:14.374
Is it a fear of not understanding AI?
00:12:14.894 --> 00:12:21.963
Is it a fear of having to change price points if people now know that you're using AI instead of human labor?
00:12:22.533 --> 00:12:24.413
Where do you think the fears are coming from?
00:12:26.138 --> 00:12:27.687
I think both of those are accurate.
00:12:27.758 --> 00:12:48.298
one of the things that I've always found interesting is that, no matter the size of the MSP, generally the value proposition that they're selling is that they're able to solve a problem, and the, kinda bring it home value prop is that you have people right down the street that you can pick up the phone and call, and they can come and help.
00:12:48.927 --> 00:12:55.418
That local touch and feel for most MSPs is a huge value creation concept.
00:12:56.057 --> 00:13:10.018
so if you are saying,"Hey, we're using AI to solve some of these issues," there's a disconnect between that value proposition of somebody down the street, and then AI's actually delivering the solution.
00:13:10.107 --> 00:13:33.268
And so I think the next iteration of sales techniques and tactics is going to be how do I create this value proposition in more of a hybrid environment where I'm selling the efficiencies and effectiveness of AI to maybe reduce your price point or to make you more efficient and get you back up and running faster.
00:13:34.107 --> 00:13:40.258
But also, I have people down the street that can come out and help you if we run into that situation, right?
00:13:40.967 --> 00:13:43.487
A full messaging shift almost.
00:13:43.977 --> 00:13:45.018
It feels like it.
00:13:45.097 --> 00:13:56.697
it may not be a completely full pivot, but I think there's gonna be a pretty substantial messaging change over time as AI becomes more prominent, and it's obvious that MSPs are needing to adapt to it.
00:13:57.307 --> 00:14:16.268
the reality is that, most platform organizations or, the larger MSPs with PE backing are already starting to look at AI because, the fundamental truth of business is that you're trying to protect EBITDA margins, and you need to deliver on profitability and, client satisfaction.
00:14:16.317 --> 00:14:23.337
there's already a push from a lot of the private equity groups that are saying like,"Hey, AI is a thing.
00:14:23.597 --> 00:14:25.737
I wanna see how it works in this space.
00:14:26.357 --> 00:14:36.717
Maybe it doesn't, maybe it does, but, we need to start looking at it and start to figure out adoption of it to make things more effective and more efficient." So you're already starting to see that.
00:14:36.998 --> 00:14:56.967
once they are really good at it, it's gonna end up driving price point down on more regional and local players because the larger MSPs are going to be able to deliver tier one services at substantially less, dollars than, the local and the regional providers doing it with humans.
00:14:59.035 --> 00:15:10.826
You know, there's already AI solutions that I was just mentioning it before, when I call into the hotel and I got an AI chatbot, and they were talking to me like a human.
00:15:11.426 --> 00:15:22.245
we're developing that internally as well, so, that's something that we will be offering, very shortly, where people can call in and talk to what they perceive as a human.
00:15:22.436 --> 00:15:26.355
or we can just have chat, you know, typing messages back and forth.
00:15:26.405 --> 00:15:28.306
most people don't wanna talk on the phone anymore.
00:15:29.015 --> 00:15:38.525
the generations that are coming into the market that are starting to lead the charge in technology and adoption, they don't wanna communicate via phone.
00:15:38.535 --> 00:15:39.905
They wanna communicate via chat.
00:15:39.956 --> 00:15:44.336
And so in that world, AI is pretty dominant.
00:15:44.336 --> 00:15:47.836
It can do a lot of things in chat, functions.
00:15:47.936 --> 00:15:51.926
Just like everything else that comes into the MSP market, there's this big yo-yo effect, right?
00:15:51.926 --> 00:15:55.235
So there's, low adoption, very low engagement.
00:15:55.316 --> 00:15:59.725
Then there's, heavy adoption, and then, the pendulum swings all the way to the other side.
00:16:00.466 --> 00:16:05.966
Then everybody realizes we pivoted probably too hard, and we need to come back to the middle somewhere.
00:16:06.015 --> 00:16:08.936
we haven't gotten to the heavy adoption yet.
00:16:08.946 --> 00:16:18.755
There will be a pendulum swing where it's gonna be too much, and then, pretty soon, I would say probably next year, you're gonna see some of that, evening out.
00:16:18.926 --> 00:16:29.795
I've also seen a lot of articles and a lot of people talking about 2027 being the year of people doing homegrown AI, starting to catch up with them.
00:16:29.855 --> 00:16:40.466
there are organizations out there that are building their own, by coding through Claude or through something else and building it, but maintaining and managing it is actually really difficult.
00:16:40.515 --> 00:16:50.706
And so the ones that started last year or even this year, next year is when the maintenance and the management really starts to catch up with them.
00:16:50.706 --> 00:17:04.086
And so the idea is that those people that started that, unless they have the money for dedicated resources to manage it and maintain it, are going to be on the market for new AI solutions that are actually managed by someone else.
00:17:04.936 --> 00:17:16.470
So I also think we're gonna see a dynamic shift there too, where- There's not a lot of organizations out there that can afford to manage and maintain a homegrown AI solution.
00:17:17.059 --> 00:17:19.190
It's just like PSAs back in the day, right?
00:17:19.870 --> 00:17:22.130
You have a couple of, major PSA players.
00:17:22.450 --> 00:17:24.140
Some people tried to build their own.
00:17:24.830 --> 00:17:33.750
Once they realized that they can't manage and maintain it effectively, they ended up buying from, a Connectwise or a Kaseya or a Halo or, one of the other big guys.
00:17:35.250 --> 00:17:36.620
So we're gonna be in the same spot, I think.
00:17:38.150 --> 00:17:45.860
How do people create a, risk mitigation strategy for the things that they're building right now for 2027 and beyond?
00:17:46.750 --> 00:17:50.019
Yeah, that one is a tricky one, too.
00:17:50.100 --> 00:17:52.569
I'll take this back to the education and knowledge piece.
00:17:53.600 --> 00:18:03.339
I think a lot of people don't know what they don't know right now, so they're building, and they don't know what risks that they need to be looking for, and there's not enough track record to figure out where the pitfalls are before they build it.
00:18:04.339 --> 00:18:10.420
So I think people are, running headfirst into some very real problems that they're gonna have.
00:18:10.960 --> 00:18:22.829
For us, we built a product with the intention of going to market with AI and understanding the AI economics of token costs and things of that nature.
00:18:22.829 --> 00:18:34.539
And so we've put in lots of different things to make sure that even if token costs go up with one or two of these, larger providers, we have flexibility on making sure that we can pivot and adapt to that, right?
00:18:34.599 --> 00:18:37.599
We already knew that was a pitfall, and so we built for that.
00:18:38.569 --> 00:18:43.220
I just think that right now a lot of organizations aren't building and taking into consideration that.
00:18:43.289 --> 00:18:52.410
Or the pricing model for the AI product is based on token costs, and so as token costs go up, so will their price point.
00:18:52.700 --> 00:19:00.970
Whereas, groups like us that are built around that mindset, we're able to manage our price point effectively in a pretty linear fashion.
00:19:01.599 --> 00:19:11.500
obviously inflation and things of that nature come up, and you end up having to raise prices slightly, but, you're not doubling or tripling or quadrupling your price because now token costs are so much more.
00:19:12.430 --> 00:19:15.059
and that's just one aspect of those pitfalls, right?
00:19:15.109 --> 00:19:18.099
I mean, to your point, there's a lot of them out there.
00:19:18.589 --> 00:19:23.440
I don't think they've been uncovered yet for a lot of these organizations to see.
00:19:24.009 --> 00:19:26.720
there's groups like us that have been doing it for a while.
00:19:26.720 --> 00:19:27.180
We've seen it.
00:19:27.190 --> 00:19:31.440
We've built some stuff internally in enterprises, which is how this organization started.
00:19:32.059 --> 00:19:34.519
we've seen a lot of those pitfalls, and so we've built for them.
00:19:35.740 --> 00:19:41.009
if you're an MSP, you're gonna start talking about AI in some way.
00:19:41.109 --> 00:19:44.029
What kind of content should MSPs be creating?
00:19:44.500 --> 00:19:53.220
right, wrong, or indifferent, the way that I've always operated in the sales world is, Identifying problem and pain points, and then trying to solve those pain points.
00:19:53.750 --> 00:19:58.400
in some sales organizations you see people that try to, square peg, round hole, right?
00:19:58.470 --> 00:20:01.190
And that doesn't necessarily work.
00:20:01.220 --> 00:20:06.359
My two cents is always going to be focusing on problems, like real-world problems that people are running into.
00:20:06.359 --> 00:20:13.410
So the things they should be talking about are, you know,"Hey, my customers are a law firm," for example.
00:20:13.809 --> 00:20:16.190
And, I just saw this the other day.
00:20:16.529 --> 00:20:19.299
law firms are predominantly like professional services orgs, right?
00:20:19.319 --> 00:20:20.329
They bill by time.
00:20:21.000 --> 00:20:35.599
Well, they use AI internally to make their time more efficient, but if they're billing for time and AI is making them more efficient, they're actually losing money because they're billing less hours for that time.
00:20:36.299 --> 00:20:57.349
So a blog post that I just recently saw was an MSP talking about how, they helped a law firm change the way that they were billing to make sure that they were still, billing the right amount from a revenue standpoint, still getting the right amount of dollars in the organization, still capturing the time savings from the AI solutions.
00:20:57.779 --> 00:21:00.000
So it's not always just about the technology, right?
00:21:00.000 --> 00:21:06.559
It's like, how do you use the technology, and how does that technology become relevant to your current business model?
00:21:06.559 --> 00:21:08.549
And does your business model need to change?
00:21:09.059 --> 00:21:31.329
And if so, as an MSP, we see a lot of different types of customers and a lot of different things that are happening, so we can bring some of those knowledge points and education points to bear and say,"Hey, not only can we help you from the technology piece, but we can help you as a business advisor," because functionally at the end of the day, that's what we do in sales, is advise people.
00:21:31.900 --> 00:21:35.609
it's not always just pushing the product and solving, the revenue goal for us.
00:21:35.609 --> 00:21:37.420
It's like, how do I solve a problem?
00:21:37.420 --> 00:21:54.200
And so to me, that's what the marketing and the, education in the space should be, is how have we, you know, as a person that delivers the service, how have we seen this change the market, and how have we seen AI impact it, and what can we do to help in that scenario?
00:21:54.200 --> 00:21:55.759
Or what have we done to help?
00:21:56.160 --> 00:22:06.720
I think that messaging goes a lot farther than, hand waving and saying like,"Hey, AI can do all of these great grandiose things," because sometimes it's not relevant, right?
00:22:08.723 --> 00:22:10.963
I think that's a great way to, wind down for the day.
00:22:11.423 --> 00:22:15.574
thanks for coming on Win and sharing your, thoughts with us today.
00:22:15.584 --> 00:22:18.824
where can people reach you and learn more about Fixify?
00:22:19.794 --> 00:22:20.054
Yeah.
00:22:20.054 --> 00:22:22.693
Actually, you can just go to the website, fixify.com.
00:22:22.723 --> 00:22:25.433
There's, ways to schedule demos with me.
00:22:25.433 --> 00:22:28.874
There's ways to grab, educational content and information.
00:22:29.433 --> 00:22:37.104
we actually have an AI chat bot that you can talk to that has real questions, and answers there, so, you can get a lot of information from her as well.
00:22:37.114 --> 00:22:40.394
If you go to the website, Fiona will pop up in the bottom right-hand corner.
00:22:40.493 --> 00:22:43.483
and you can have an actual real conversation with her.
00:22:43.773 --> 00:22:52.874
Tell her, what size organization you are, who you serve, what you do, and she can actually have real conversation about whether we're a good fit and how we would be able to help.
00:22:57.109 --> 00:22:58.180
Have a good afternoon, Matt
00:22:58.549 --> 00:22:58.809
Yep.
00:22:58.970 --> 00:22:59.430
Thanks
