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Humanising IT: We Need to Talk About IT is the podcast for IT leaders, service management professionals, and digital transformation teams who know that great IT is about more than process, tools, and frameworks.
Hosted by Katrina Macdermid and Wesley Eugene and brought to you by HIT Global, this podcast explores how to make IT service management more human, more effective, and more relevant in a world shaped by experience, AI, and constant change.
Each episode dives into the real conversations happening across modern IT, including:
- IT service management (ITSM)
- Human-centred design in IT
- ITIL and experience-led service management
- Digital employee experience
- Service desk and support leadership
- IT transformation and organisational change
- Humanising AI and modern service design
If you work in IT and care about creating services that actually work for the people who use them, this podcast is for you.
Whether you’re a CIO, IT leader, service manager, consultant, support professional, or transformation lead, Humanising IT: We Need to Talk About IT will challenge outdated thinking and help you rethink what better IT service really looks like.
Expect:
- Honest conversations
- Fresh perspectives on ITSM
- Practical insights you can apply
- Thought leadership from experienced voices in the industry
- A more human view of IT, service and experience
Subscribe to Humanising IT: We Need to Talk About IT for new episodes, expert insights, and modern thinking on the future of IT service management.
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Humanising IT - Episode 6
[00:00:00] Kat: And welcome to our next episode of We Need to Talk About IT, the Humanizing IT podcast with my co-host, Wesley Eugene. Hello, Wesley. How are you going?
[00:00:14] Wes: I'm doing well over here
[00:00:16] Kat: Good. Good. We'll talk about-
[00:00:18] Wes: How's it
[00:00:18] Kat: going, Chad? Yeah, I'm good. We'll talk about, um, how we are really global in a moment. Um, and really pleased to introduce our next guest, uh, Michael Kennedy.
[00:00:27] Hello, how are you going?
[00:00:29] Michael: I'm doing well, thank you.
[00:00:30] Kat: Good. Thanks for having me. Good. And, uh, and again, I'll explain how we met, but basically I'm in Melbourne, Australia, Wesley is in Atlanta in America, and Michael is in, uh, Singapore. Uh, so we are very, very disperse and we managed to get a time zone to suit, so thank you for your time.
[00:00:51] Um, everybody knows Wesley, so you don't need any further introductions, Wes. Uh, Michael, we briefly met, uh, on LinkedIn. It was only last week. Mm-hmm. You, uh, liked one of the posts that, um, we did, and we reached out to you and, and thanked you for liking our post, and we met, and we were having a very, very interesting conversation about your industry, which is recruitment- Mm-hmm
[00:01:16] and the impact AI is h- and continues to have on your industry. And I said to you, "Stop. We need to do a podcast." Like, 'cause it was so, so very interesting what you were telling me, and I wanted to share it and, and Wesley obviously when I, I spoke to him straight away, "Yep, we gotta do that podcast." So if you wouldn't mind introducing yourself, Michael, please.
[00:01:38] Michael: Okay. So, uh, Michael Kennedy. I've, I've worked in technology for over 25 years, and for the last 16 years of these I've worked for a fairly large, uh, global recruitment firm, um, most recently as their CIO. Um, so that's one hell of a journey over, over the 16 years to see the different waves recruitment has, has, has, has, has followed and, um, and, uh, and in the last f- last two, three years obviously been heavily disrupted by, by AI.
[00:02:05] Yeah, so very keen to talk about that, I
[00:02:08] Kat: think. Very much so. And as I said, we'll, we'll talk- Yeah ... uh, a little bit about the history of recruitment and what it used to look like. So what, in, back in the day- Mm ... um, how did recruitment work? I mean, I know in my day, and Wes, you're probably the same, we used to write a cover letter.
[00:02:25] Sure. Uh, we used to probably spend hours, if not days, retrofitting our resume to fit the job description. Um, we sent the resume in, um, and I don't mean to be disrespectful, Michael, but most of the time we never heard back.
[00:02:44] Michael: No.
[00:02:45] Kat: Um, which is a, always very frustrating, and I'm sure a lot of our listeners can relate to that.
[00:02:49] And then that was it, and maybe we got an interview. So how did it work?
[00:02:56] Wes: Well, I- Yeah ... I'd also add to that really quickly, on the candidate side, um- My, some of my best opportunities came through via executive recruiters.
[00:03:07] Kat: Mm.
[00:03:08] Wes: Some of my most glorious opportunities came through executive recruiters. Um, and so that was always amazing to get a, an, a LinkedIn outreach or an email by an executive recruiter, because if they're reaching out to you, you already fit the profile of what they're looking for.
[00:03:28] Uh, the probability of you landing a role is, like, at least 50%, I would say almost. Um, so long as everything else aligned for you. So I- it's not all a bad story. There's, there's, there's some great stories
[00:03:42] Kat: in there too. That's true, Wesley, but unfortunately I never got approached for an executive position, so.
[00:03:48] Um. So thank you for adding that in- But I can go into some select ... that different perspective. Thank you so much. Michael.
[00:03:55] Michael: Yeah. So, so going back, um, you know, 16 years ago, you could tell a busy recruitment office by the phone was ringing, right? People were talking to people, and you could tell there was a buzz and there was an activity around, you know, if the office was having a good day.
[00:04:09] Uh, it was like almost like a trading desk or something. It was exciting. You could hear what was going on. And obviously that's, that's changed now. Uh, but you know, and, and I think back then, uh, there was relationships and, and, and the, and there was exclusivity almost, I think that, uh, you know, not every recruitment agency had all the candidates, right?
[00:04:29] You had your own candidates, you, you built in your proprietary database. And I think, uh, over, over time, I mean, that's changed. I mean, LinkedIn wasn't around then. Um, so you could, you know, if you belonged to a particular agency, then they were doing their best to, to find you and, and you felt that they were on, on your side and, um, and they were really doing their best to find you a role.
[00:04:48] I think, um, that's shifted now. I don't think there's that exclusivity anymore. I don't think there's any loyalty anymore. I think anybody, uh, one thing I learned over the years is nobody really cares how they find a job as long as they find a job. And that, that leads to, um, you know, people nowadays just, you know, applying for everything, right?
[00:05:08] And, yeah.
[00:05:08] Kat: Mm.
[00:05:08] Michael: And,
[00:05:09] Kat: and what made a, a great recruiter back in the day?
[00:05:14] Michael: Um, conf- confidence, uh, some in- industry knowledge, some, you know, some, uh, someone that's come from that background as well w- was really, really helpful. Uh, ability to, you know, to build relationships, um- Yeah. Hard work, flexibility, all these things.
[00:05:33] Uh, trust, integrity, all, all the things that make a good, a good salesperson, I'd say mostly. Yeah. It,
[00:05:40] Kat: it was a- But what- ... it was a pretty tough gig sometimes, wasn't it, to be- Yeah. Yeah. Mm.
[00:05:45] Michael: It was. It's tough going, yeah. '
[00:05:47] Kat: Cause I, I guess I spent most of my career being a contractor. Uh, so I, I- Yeah ... I did a lot of work and I, I, y- you know, you kinda get to know your recruiters also because you- Of course
[00:05:57] you're transient and, you know, they, you kinda build a relationship with them. Yeah. Um. Yeah. Where did they spend most of their day back in the day?
[00:06:06] Michael: Um, not, not necessarily at their desk. They're right out meeting people. Mm-hmm. Um, and I think, you know, where I, where I worked, we, we always had suites of meeting rooms, and they were always busy.
[00:06:17] There was always candidates coming in, and there was a real buzz to, buzz to recruitment-
[00:06:21] Kat: Mm. Mm ...
[00:06:22] Michael: uh, continued maybe like that for a long, long time. So they, they spent their time out meeting people, really.
[00:06:28] Kat: Mm.
[00:06:28] Michael: Yeah.
[00:06:29] Kat: And, and as I said, I, I, you know, we'd write a, a cover letter. Would they sit there and read the letters manually?
[00:06:37] And how did they decide? I,
[00:06:41] Michael: I think, I think they would, but, but, uh, I think it was possible to.
[00:06:44] Kat: Mm. Yeah. Yeah. Yeah. And, and then as I said that, as we got talking, um, in our meeting last week, one thing you said to me was that today everybody writes the perfect cover letter.
[00:06:57] Michael: Mm.
[00:06:57] Kat: Because
[00:07:02] AI is doing it, rather than back in the day you'd sit there, um, as I said, for hours, if not days. What did you mean by that, Michael? Well, I,
[00:07:12] Michael: I'm-
[00:07:13] Kat: Mm ...
[00:07:13] Michael: with AI, so I, I mean, I think now if you look at the end-to-end recruitment now, I think from a, from a business perspective, AI is probably helping determining what the job is needed, so it's probably helping then determine the, the job advert.
[00:07:28] It's writing the advert as well. True. True. Then, um, then you've got someone with a... And these are easily available in the marketplace, uh, kind of AI kind of bots that will apply for every single job. So you've got an AI-generated job, an AI-generated advert, a GI- AI-generated application with an AI-generated CV and cover letter.
[00:07:48] I don't even think the cover letter matters anymore 'cause it's not-- You'd be filtered long before. A cover letter is a conversation, and I don't think there's an opportunity to have that conversation most. So you've got A- AI in one side, uh, completely automated AI from a client perspective, uh, then being met with AI on the other side to ingest it.
[00:08:08] Uh, that, that's what recruitment looks like now, I think.
[00:08:10] Kat: Mm.
[00:08:10] Wes: So given that, Michael, who fired the first shot? I mean, was it the candidates that started introducing a ton of AI slop of their, um, AI-generated cover letters and resumes, or was it the AI-enabled applicant tracking systems, um, that started this AI war?
[00:08:37] Who fired the first shot?
[00:08:39] Michael: That's interesting. I mean, the probably- almost went off at the same time, I'd say. I, I think because the technology emerged for both sides at the same time. Um, I think, um, I think like any business, uh, recruitment business is looking, was looking to AI as soon as it was available to build efficiencies and make things better internally, reduce time spent on administration.
[00:09:01] All the, all the things that any business would do. Uh, and, and, uh, but I think from a candid perspective, I mean, you know, the, the fact that, you know, you could... I mean, we all used to spend hours, you know, tailoring CVs and tailoring applications, and the fact that you- I could, I could do that in 10 seconds now, and probably better, right?
[00:09:19] So I think, um, I think it ha- I think it, it happened at the same time as technology allowed, uh, with all- Yeah ... with all these things, everybody used it to their advantage.
[00:09:28] Wes: Yeah.
[00:09:30] Kat: And, and I guess, you know, um, before we move to the present and the future- Yeah ... um, back in the day, my understanding was you had a company, they ne- they had a need to hire someone, they'd contact a recruitment agency.
[00:09:43] Um- Mm-hmm ... and essentially, for want of a better word, the, the recruiter was the middleman. Is... Do you think that has completely changed now, that whole value chain, if you will, of how the process of recruitment used to work?
[00:09:58] Michael: I, I think it, it is changing. I, I think that, you know, if there's... A re- recruiter has to become something else.
[00:10:05] This is maybe a little bit onto the future, but I think they've gotta be almost like a, a trust broker, and they've still got to have the relationships. But, um, you know, I think the admin's gone completely. Uh, that, that's all handled by AI. So I think the, the, the role of a recruiter is still there, but it, it's changing completely.
[00:10:22] It's, it's, it's judgment, it's, it's risk mitigation. They... Ex- hires are expensive, so I think you go to a recruitment agency now to, you know, to feel more secure in the decision you're making, um, rather than, uh, you know... I think it's possible not to use them, but I think, you know, they still add value.
[00:10:41] Kat: But are they reading the res- resumes or CVs that come through?
[00:10:46] Michael: Uh, they can't read all of them. I mean- Mm ... w- w- literally, I mean, you, you can have a role that maybe before you got, yeah, maybe 50 to 100 applicants, now you might get 1,000 now.
[00:10:57] Kat: Wow. Yeah. So how, how does that work? Like...
[00:11:02] Michael: Well, it's AI versus AI, right? So, uh, it gets, it gets, it gets filtered, and when you, you end up with a short, a shortlist, and that's where you get all the, the fairness, the ambiguity, the ethics and all these things, like who gets shortlisted and things on that, right?
[00:11:15] Right. That's- Well- ... that's difficult ...
[00:11:17] Kat: which leads on really nicely to our next topic. Um, I called it the AI earthquake. Um, but Wes, you're, uh, involved in a community, um, that is really o- on this train, if you will, of helping and trying to understand recruitment today. Um, tell us more about what the community you've created, Wes.
[00:11:41] Wes: Yeah, sure, Cat. So, um, I ran an experiment in the, in the last quarter of the year last year, and, um, in the fourth quarter. And The experiment was, you know, the hypothesis of the experiment was what would it look like to profile incredibly talented leaders and treat everyday talented leaders like they were a celebrity, right?
[00:12:14] Um, and so the reason I started running this experiment is part altruism because I was frustrated with the algorithmic gatekeepers that was disconnecting talented leaders from great opportunities. But the other part was honestly like, um, part activism as well because in the messaging, I would very deliberately call out the challenge in front of us that was f- that we're facing, um, because of AI-enabled, uh, bias, right?
[00:12:50] And, and the... Look, to be clear, I don't think AI is evil, but I think that the, uh, the unintentional, um, use and deployment or the immature use and deployment of this technology in the most human of processes, which is connecting people to other people, this doesn't seem to be a place that we should be delegating our judgment to machines, right?
[00:13:19] You are literally like... I'm a parent, right? Like, when I'm making a decision about who my daughter spends time with, I'm not delegating that decision to a machine. Like, when we organize communities of people, and that's what a company is, is a community of people organized around a purpose, that- that's the most human of processes.
[00:13:43] And so for us to just delegate that to machine and say it's okay for humans to be in the loop instead of leading the loop, it's a really terrible thing in my estimation. So anyway, off the soapbox, but this was a problem I was seeing, and I personally had experienced it because I was also, uh, um, looking through the market thinking about new opportunities for me, and, um, I was running into the same thing.
[00:14:12] So with all of that said, um, I created a community called Amplified because what happened was after I started spotlighting leaders, these leaders started talking to one another.
[00:14:25] Michael: Hmm.
[00:14:25] Wes: And they said, "Hey, Wes, we'd love to just have our own community." And I was like, "Okay, roger that." And so it-- they began to help one another, sending leads to one another in all of this.
[00:14:39] Um, so we were continuing to evolve that community. Um, but it wasn't just a feel-good exercise. Hmm. I'm happy to report that in Q4, which HR leaders have told me is a terrible time to do what I did But in Q4, when everybody's shutting down, um, one in three of the folks who participated in the process found a new opportunity within six to eight weeks.
[00:15:05] One in four found a new opportunity within eight to 12 weeks. And what that showed me was the power of visibility i- and human connection is the antidote to the algorithmic bias and gate- gatekeeping that we're seeing in the market today.
[00:15:23] Kat: So Wes and Michael, you've, um, prior to doing the podcast, we obviously had a meeting, but you both keep mentioning sort of bias.
[00:15:32] What's bias in recruitment mean?
[00:15:37] Michael: I, I mean, I mean, any, any geography has, uh, regulations around w-what you can discriminate against. So age, nationality, gender, uh, race, religion, all these things, and you're not allowed to make a judgment call on these things. And, but I think that, um, when you have a, 1,000 applicants for a role and, uh, and you have probably just a slider in order to control them when you get to the shortlist, I think there's, um, there's inherent bias coming in, coming across that, uh, which is discriminating against some of these, some of these areas.
[00:16:12] Kat: What's an example?
[00:16:13] Wes: Yeah.
[00:16:14] Michael: Uh, I, I, well, if you have, if you have, um, 1,000 applicants for a, a role in Singapore, for example, and I'm not saying this definitely would, would happen, you're, you're probably, you're probably, uh, uh, filtering against people that are foreign, for example. You're looking for locals where you, you shouldn't necessarily only be looking for locals.
[00:16:34] Yeah.
[00:16:35] Kat: But who's telling the AI- Yeah ... to only look for local?
[00:16:38] Michael: Uh, the person that needs to look at 20 CVs, not 1,000.
[00:16:43] Wes: Right. So I mean, the other thing, and Michael, I, I'd, um, love you to confirm or complicate this-
[00:16:51] Michael: Yeah ...
[00:16:51] Wes: is the very nature of AI is based on this concept of machine learning. Yeah. So we're literally, AI has the power it has because it's training on historical data.
[00:17:04] Michael: Yeah.
[00:17:04] Wes: Like, it's all about this data set, and the truth about the matter is that when we have these regulations come up that says, "Hey, we need to make sure that when, uh, someone who's differently abled than o- other folks, um, applies, that they have every opportunity to compete for the same job as an able-bodied w- person does."
[00:17:26] Mm-hmm. "Uh, when a woman, uh, competes for a job, she should have every ability to e- every opportunity to win the job just as a man." W- when we're looking at things like that, we only have these regulations because in the past there's been discrimination and there's been harm, right? Yes. So what for me that establishes is that history is a poor teacher to AI.
[00:17:51] Michael: Yeah.
[00:17:52] Wes: Right? History will lead AI to the wrong conclusions. Yeah. That like, I mean, history in the States, for example, would say the ideal candidate in e- for any executive role in a Fortune 500 company is white male, under 40, and fully able-bodied.
[00:18:11] Michael: Mm-hmm.
[00:18:12] Wes: That's just what history would say if you take a look at the history of CEOs of Fortune 500 companies in North America.
[00:18:20] Michael: Yeah.
[00:18:20] Wes: So history is a poor teacher, but yet this technology, its default design is to learn from history. Yeah. So without some intentional guardrails- It's going to have a lean or a bent towards identifying what's right or what's optimal based on historical trends and patterns.
[00:18:46] Michael: Yeah. Completely agree with that, Wesley.
[00:18:47] Yeah. Yeah. It's, um- Yeah ... u- under, under hiring the, the, the recruiters are looking for the shortest path to success typically. Yeah. Mm.
[00:18:57] Kat: And I, I guess, uh, in my, our industry, which is IT and IT service management, I, I think if I sort of turn a little bit for a moment in that I, I think our industry is slowly going to be disrupted.
[00:19:14] I think it's not there yet. I think you'd agree with me, Wes, we're not really catching up to what AI can do. Mm. Um, but roles will change in our industry, and I think, um... Wes, you're looking at me in a funny way. Please explain.
[00:19:30] Wes: Oh, I, I think it's, I think the tsunami has already started. Do you, um- The tsunami within tech has already started-
[00:19:36] Kat: In
[00:19:37] Wes: service
[00:19:37] Kat: management?
[00:19:38] in my opinion.
[00:19:40] Wes: Well, service management is, its day of reckoning is upon us. But go
[00:19:45] Michael: on. It, uh, in, in my, in my experience, service management always, always appears like low-hanging fruit for, uh, automation and things. Like, everybody's interested in, in doing that, so it's, it's almost inevitable that, uh, it gets, it gets, uh, more taken over.
[00:20:01] Yeah.
[00:20:02] Kat: Yeah. Yeah. I, I agree, but I, yes, so let's go with that. So I'll use the example of traditional knowledge management owner. Uh, what else? Problem incident. You know, those roles will invariably change, if not go. Uh, so- Mm-hmm ... what do we, how do we apply for jobs today? Because if you gotta get 1,000 today, you gotta get 2,000 probably, you know?
[00:20:24] You know, it, you know, should we be worried as in, in IT service management? Because as, Wes, if you say if we're gonna have this tsunami, um, there's gonna be a lot of people looking for work, um, do, how do we do that as a, in the recruitment now? What, what... Any thoughts, Michael?
[00:20:46] Michael: I, so I think the tsunami w- is on the way. I don't necessarily think it's here. I, I, I still see lots of service management type roles- Mm ... uh, around. Um, but how, how do, how do we apply when y- you, you, you basically have an algorithm applying for every single job that comes out on whole recruitment crew? Uh, if, if you're not gonna do that, then you need to, uh, you need to somehow build a relationship with, with hiring managers or, or, or, or find a way to speak to a human in the organization.
[00:21:14] Yeah. I think that, um, you know, if you're, if you're just going to LinkedIn and doing an easy apply now, you're, you're joining a, joining a very, very long list of identical applications, so I think it's, it's quite hard.
[00:21:25] Kat: Mm-hmm. Which goes back to what Wes said, it's about the human connection. Um- Yep.
[00:21:29] Michael: Abs- it's, yeah.
[00:21:32] Mm. And which, which, which is one of the key, the key tenets of service management right there. It's funny that, um, something that, um, something that requires a, a, a, a human to give good service is cited entirely by AI as well, likely. Yeah.
[00:21:44] Kat: Mm. Mm.
[00:21:45] Wes: It's an interesting conundrum, isn't it? Mm. Like, I- IT seems people who tend to, uh, be introverts, like gamers, uh, you know, what have you, um, more process-oriented, uh, sometimes a little less, you know, excited to be inf- customer facing-
[00:22:09] Michael: Yeah
[00:22:09] Wes: tend to migrate to IT.
[00:22:11] Michael: Yep.
[00:22:12] Wes: Those personalities, I've seen them over my career, but yet that's the very behavior that they have to change to be successful in this market.
[00:22:21] Michael: Yep.
[00:22:21] Wes: Is they have to actually engage, they have to press the flesh. Like digital networking is okay, but human, like in person, in real life connection is way better, and like this is where the effort needs to be.
[00:22:38] But it's, um, it's almost like re-pattern, re-patterning their mind. Yeah. And, uh, you know, it's, it's a big mindset shift.
[00:22:47] Kat: It is.
[00:22:48] Michael: Yeah.
[00:22:48] Kat: Yeah.
[00:22:49] Michael: Mm. Yeah. You've got, nobody can be introverted now and like and expect to... Do you need to be noticed, right? You have to be noticed.
[00:22:55] Kat: Mm.
[00:22:55] Wes: Yeah. Yeah,
[00:22:55] Michael: yeah. While you're just in a, in a, uh, in the, in the big, the big pool of other candidates, so you have to stand out in some way, and that's not traditionally what tech folk do.
[00:23:05] Kat: Mm.
[00:23:05] Michael: Yeah.
[00:23:05] Kat: Yeah, because I, I- Mm ... I think, uh, I mean, obviously we know a lot of people, and ones that have told us that they've applied for a role, as you said, Michael, via LinkedIn or, you know, traditional, and, you know, said, "We never, never, ever hear back from them." And I'm like, "But why bother then?" Because as you said, it's just going into this, this pool of- Well, that's it
[00:23:24] mm. I mean,
[00:23:25] Michael: I mean, you can, I mean you, like, I guess you can You can think you're doing a great job, you can spend hours the old-fashioned way creating something very special, very personal. Uh, but then you might, you might do that a couple of times and then you realize that actually I got the same response as if I'd just pressed apply.
[00:23:41] Wes: Mm.
[00:23:42] Michael: Uh, so y- I guess inevitably everybody, everybody will turn to, you know, just the easy way of applying. Um, and the, the answer is, uh, actually, you know, being out there speaking to people if you can. But that's hard to do that because traditionally, and going back in the days of recruitment, you'd apply for a role and you'd get a call from a recruiter and that, that would be your in, that would be the conversation you have.
[00:24:03] Yeah. Uh, I think it's really, really hard to have any engagement with a human around a job application these days.
[00:24:09] Kat: Mm. I
[00:24:09] Michael: mean, obviously some people do, people are getting hired, but, uh, you... the percentages, it's, it's a numbers game and it's very much against you now.
[00:24:17] Wes: Oh, yes. Yes. Absolutely. It's become h- the, the job market has become one big casino and everybody- Yeah.
[00:24:25] just like pulling slot machines.
[00:24:28] Michael: Yeah. But I, I, I mean, the, the, there are tools now in the market that will source roles for you to apply for, aut- tailor automatically and apply automatically. So you're even a- you can be applying for roles you don't even know you've applied for.
[00:24:44] Wes: This is true. This is true.
[00:24:46] And it's similar to Rain Man where you walk in and somebody has an unfair advantage, right? Like- Yeah. Yeah ... come in to the, to, to, to sit at the blackjack table with a system. Yeah.
[00:24:56] Michael: Yeah. Yeah.
[00:24:58] Kat: But, but I, I guess the positive side, um, is that this has created jobs. Would you
[00:25:07] Michael: agree?
[00:25:08] Kat: Yeah.
[00:25:08] Michael: Yeah, and, and, and I think that the other side, I think we're in a generally a bad market anyway, so I think that's, that's compounding things as well.
[00:25:17] I don't think it's all AI disruption that's causing the difficulties we're seeing now in the, in the job market. I think it's, there's a lot of, lot of factors at play, and I think this is just one. Yeah. A large factor, but not the only factor. Hmm.
[00:25:28] Wes: Uh, 100% agree.
[00:25:29] Kat: Hmm.
[00:25:30] Michael: Yeah.
[00:25:31] Wes: I mean, I honestly challenge people in my community to think a terrible thought, and I'll introduce it here.
[00:25:40] Hmm. What happens if your job just doesn't exist anymore- Mm ... period?
[00:25:47] Michael: Mm.
[00:25:47] Wes: Like if you were a, um, you know, if, if, if you were a knowledge manager and that role literally is just going away. So how do you reinvent yourself?
[00:26:03] Michael: Mm.
[00:26:03] Wes: Do you... And, and do all the answers have to be, "I need to rev- reinvent myself within IT"?
[00:26:11] Because knowledge managers in the, in, in, in, in, um, healthcare may still be in great demand, right?
[00:26:20] Michael: Yep.
[00:26:21] Wes: Um, so it's, it's really getting people to have some mental agility as well and, um-
[00:26:27] Kat: But I think where's knowledge- ...
[00:26:28] Wes: you know, reinventing yourselves.
[00:26:30] Kat: Sorry to interrupt. But I think, um, n- knowledge management, your skill that we used to have, it's a completely different skill that you need today.
[00:26:38] Like, I think a knowledge manager now needs to know how to do videos, how to do, um, instructional design. You know, do you know what I mean? It's a very... You know, traditionally a knowledge manager, you know, would write, write articles and, and with all due respect, and I was one of them, not very well. Um, you know, you know, pages and pages of a PDF document and things like that.
[00:27:02] Whereas I think now how we consume knowledge as humans is very different. Yeah. And so now we need to get those new skills. So that's what I mean, there's opportunity and as you said, whereas it's not if your job goes tomorrow, you... We used to say we have to update our resume. No, now we have to update what we do.
[00:27:19] Michael: Yeah.
[00:27:20] Wes: We have to update ourselves. Mm. Like, uh, you know, if I've been in health- if I've been in a particular industry within IT, like insurance... Oh, actually that's not a great example 'cause insurance IT is doing great. But, um, if I was let's say, um, uh, cons- retail and, and, you know, um, like consumer, consumer products and goods.
[00:27:42] Um, if I was in an IT role there and I saw a ton, a wave of automation coming away, um, to take my job away, how might I first think about, well, are there other industries that I could bring these same skills to?
[00:27:57] Kat: Mm.
[00:27:57] Michael: Mm.
[00:27:58] Wes: And then, you know, how might I further my, my thinking and my discovery to say, you know, are there other skills that I have that I've never really packaged together that may play well in a different space.
[00:28:17] It, but it, it really causes, it calls on us to be very creative, I think- Mm ... and to find that resilience, you know?
[00:28:25] Kat: Mm.
[00:28:25] Wes: People keep talking about the Model T coming in and taking away, uh, all the, the horse and buggy dri- jobs.
[00:28:32] Kat: Yeah. Mm.
[00:28:32] Wes: But like there was a transition of some sort- Yeah ... and people had to get creative about what was coming next.
[00:28:38] Kat: Mm. You know? But it, it's interesting, um, Wes, and, um, Mark just like... Wes and I speak about this quite often, and AI and the slow-moving wagon in IT service management because, you know, we say that really you don't need the level one anymore if you invest in AI, but companies are still training and employing, you know, a service desk analyst, and that's what I was saying earlier, Wes.
[00:29:06] I do s- I don't think that tsunami is, um, quite there yet.
[00:29:13] Michael: Yeah, I don't think so. Well,
[00:29:14] Wes: uh, yeah.
[00:29:15] Michael: So I, I think, I think that we, i- in my experience- Um, I think people still rather speak to a human if they can. Yeah. And I, I don't think, I don't think that disappears altogether. It might mean less humans, there might be a balance between automation and, and, and someone on a chat or on the phone, but, um, I think that that's still a, a, a strong preference, I'd say.
[00:29:38] Kat: I
[00:29:38] Wes: agree,
[00:29:39] Kat: but yeah- Yeah. I, I- Go, go on Wes. Yeah
[00:29:41] Wes: Yeah, I don't disagree with that. I do think that one quick cheat sheet, uh, from the IT service management world is, like, be part of the white glove service. Like because that's not going away so long as there's executives, there's gonna be this- ... VIP white glove service tier.
[00:29:57] Mm. Um, and it's always gonna require a human touch. Yeah,
[00:30:00] Kat: yeah. Yeah.
[00:30:01] Wes: It's not gonna replace that for a robot even. Yeah, yeah. So, um, you know, do that for sure as a, as a
[00:30:08] Kat: cheat code. But, but you know, I, I think it's a positive thing that, as I said, like, you know, CIOs are very smart people of, in I- you know, in IT obviously, and, and they know they can automate, automate, automate.
[00:30:18] But I think as you said, Michael, there is that pe- they still want that human connection. So I, I think that's, at the end of the day, it's, it's a positive thing. Very positive.
[00:30:26] Wes: The other thing that might slow down the tsunami is the rising cost of
[00:30:32] Kat: AI. Mm. Okay.
[00:30:34] Michael: Yeah.
[00:30:34] Wes: Because we're about to enter another reckoning where the cost of automation versus the cost of keeping things driven by humans, um, is gonna be a counterbalance, and we're going to have to, like, weigh that and say, "Yeah, nah, I think I'd rather some junior engineers over here-
[00:30:53] Kat: Mm
[00:30:53] Wes: instead of automating this-" Yeah ... 'cause the cost of the tokens is just too high."
[00:30:57] Michael: Especially, I mean, especially when organizations should have some ESG, um, it, it- they, they must have some targets there, and I think, I think that, um, it doesn't take much for a, you know, y- I think you can go too deep into it and, and get to, and be in a very vulnerable situation where, uh, you know, commercially and, uh, you know, I think if you're with one of the bigger vendors, you see with traditionally things like some of the big vendors and licensing and Microsoft licensing.
[00:31:23] You know, if you, if you're all in with Microsoft and suddenly it's 10% more expensive next year-
[00:31:27] Kat: Mm ...
[00:31:27] Michael: then you could be in trouble. I think there's, there's definitely the danger of that with AI as well, and, um, they can just turn, turn up the dial. Once, once everybody's in in the next couple of years, I think it could get very, very expensive for some people.
[00:31:39] And I, and I know that, um, in my own experience, you know, when we've looked at service management, I mean- We, we operate in some low-cost countries, you could say. Yeah. Uh, and it, it just hasn't been worth the investment, uh, which is quite a significant investment to overhaul, uh, our IT service management when we're already operating in a very lean and efficient manner.
[00:32:00] Kat: Exactly. Exactly. Mm-hmm. Yeah, yeah. So, um, just about time to wrap up. Uh, I've really enjoyed this episode. I'm sure our listeners have. It's been really informative, especially, and very pertinent in the role of AI in our industry also. And, um, thank you for your time. But before I wrap up, one thing that you did say, Michael, which I thought was-
[00:32:22] Michael: Mm-hmm
[00:32:22] Kat: quite interesting, when if all else fails, write a cover lever- letter. Yeah.
[00:32:29] Michael: You have to know this, right? I mean, I, I think that, um, I mean, you see people... You have to be an influencer on LinkedIn almost now to, to have any conversation with anybody, and that's not everybody's, everybody's cup of tea at all.
[00:32:42] Yeah. And especially for tech people, it's not in their nature to, to go out there and sell themselves. So I think, uh-
[00:32:47] Kat: Exactly ...
[00:32:49] Michael: yeah, yeah. Mm-hmm. I'm not sure this is the best advice, but hand-deliver the letter.
[00:32:55] Kat: It's something different, isn't it? Well,
[00:32:57] Michael: yeah.
[00:32:57] Wes: Yeah. It's absolutely different. Uh, I... So I, I love that suggestion, Michael, because, um, as we're moving on this race towards d- more digitization and more automation, things that are uniquely human, like receiving a handwritten note, become like a lost art form.
[00:33:21] Yeah. And they are gonna stand out.
[00:33:22] Michael: Mm-hmm. Yeah, and you can put your personality on that, right?
[00:33:25] Kat: Exactly. Bit of divergent thinking, I always...
[00:33:28] Wes: Absolutely. No, I love it.
[00:33:30] Kat: Yeah. Great stuff. All right. Thank you so much, guys. And, um, I'm sure we'll do a follow-up episode on this, and we'll speak to you soon. Thank you.
[00:33:42] Wes: Thank you. Thank you. Thank
[00:33:42] you.